Surveys help conversion because they reveal what analytics can’t: objections, missing info, and confusion.

By the end, you’ll have ready-to-launch customer feedback surveys, a question bank, and a workflow to turn answers into fixes/tests.

5 customer feedback survey types that actually improve conversions

The question bank (only the questions that uncover conversion blockers)

Product page surveys (clarity + trust)

• “What questions do you still have before buying?”
• “What’s stopping you from adding to cart today?”
• “What would make you feel more confident?”

Cart/checkout surveys (friction + anxiety)

• “What’s stopping you from completing your purchase?”
• “What feels unclear right now?”
• “What is your biggest concern about ordering today?”

Post-purchase surveys (why they bought + attribution)

• “How did you first hear about us?” (HDYHAU)
• “What was the main reason you chose us?”
• “What almost stopped you from buying?”
  (HDYHAU is widely used in post-purchase survey programs; question sets are common in Fairing/Yotpo content. )

Abandonment surveys (why they left)

• “What stopped you from finishing checkout?”
• “Were you trying to do something you couldn’t?”
• “What would have changed your mind today?”

Retention/returns surveys (fix downstream conversion killers)

• “What didn’t match your expectations?”
• “What would have prevented the return/cancellation?”

The post Customer Feedback Surveys: Templates and Questions to Improve Conversions appeared first on Invesp.

Most teams don’t set out to over-rely on A/B testing. It usually starts with a small win.

Someone tests a headline. Conversions go up a little. Then they test a button. Then a product image. Over time, that becomes the team’s default way of making decisions: pick one thing, run a test, wait for a winner.

That’s not a bad thing. A/B testing is useful. It helps teams reduce guesswork and make better decisions based on real behavior instead of opinions.

The problem starts when teams use A/B tests for everything.

A/B tests work well for clear, focused questions. But they’re much less useful for bigger problems like unclear messaging, weak product pages, confusing navigation, or pricing decisions that affect profit and repeat purchases. In those cases, teams can run many tests and still miss the real issue.

That’s where over-reliance becomes a CRO maturity problem.

This article explains why teams default to A/B testing, where it falls short, and what high-maturity teams do differently to achieve better results.

How A/B Testing Became the Default

A/B testing has become the default method for digital teams because it’s fast, simple, and provides a clear yes/no answer. Anyone on a marketing or product team can launch a test without needing a statistician, a researcher, or a complex analysis pipeline.

Experimentation platforms like FigPii reinforced this behavior. Their workflows make it effortless to spin up a test: pick a goal, create a variant, and hit launch. That convenience shaped an industry culture in which “experimentation” means “run an A/B test,” even when other methods might yield deeper insights.

Industry surveys show this clearly. 

According to statistics, 77% of all experiments are simple A/B tests (two variants), not multivariate or multi-treatment designs. This shows how strongly teams default to the simplest possible approach, regardless of whether it’s the most informative.

Big tech helped normalize this mindset. Microsoft’s Bing team famously ran an experiment in which merging two ad title lines into a single longer headline increased click-through rate enough to generate over $100M in additional annual revenue. Successes like these made A/B testing a cultural norm. 

Today, Microsoft runs 20,000+ controlled experiments a year across Bing alone, using tests to validate everything from minor UI tweaks to major ranking updates.

The Core Problems With Over-Reliance on A/B Tests

A/B testing is a useful tool, but it has limits. The problem is not the method itself. The problem is using it as the answer to every kind of conversion problem.

A/B Tests Answer Narrow, Small Questions

A/B tests are practical for micro-changes, such as headline tweaks, button styles, and minor layout shifts. But that’s also precisely why they limit teams. They are effective only for small, isolated decisions, not for meaningful shifts in product, pricing, or experience.

For example, A/B testing works well for small questions like: 

A/B tests are great for small questions like:

• “Does this headline perform better than that one?”
• “Will placing reviews higher on the page increase add-to-cart?”
• “Does a shorter checkout form reduce drop-off on that step?”
• “Does a different product image improve clicks?”
• “Which CTA wording gets more taps?”

These are small questions because they focus on a single element on a single page, and the potential outcome is usually a modest lift (1–2% at best).

The problem is that teams try to use A/B tests to answer big questions, the kind that decide whether the business actually grows:

• “Is our value proposition clear enough for first-time visitors?”
• “Is our navigation structured the way customers think?”
• “Are we pricing and discounting in a way that improves profit, not just conversion?”
• “Does our PDP tell a convincing story about why the product is worth the price?”
• “Should we redesign the checkout flow entirely?”

These questions involve multiple aspects of the experience, including pricing, messaging, navigation, and product mix. You cannot answer them by changing a single UI element.

Most Companies Lack Traffic for Statistical Power

Most ecommerce brands simply don’t have enough traffic to run reliable A/B tests. A/B tests only work when you have statistical power, i.e., enough visitors and conversions to tell whether the difference between Variant A and Variant B is real or just noise.

If the difference you’re testing is small (like a 1% or 2% lift), you need hundreds of thousands of visitors per variant to detect it reliably.

Most ecommerce sites don’t come close. Even brands doing 1-2 million sessions per month often can’t detect a small UI lift without running a test for 6-12 weeks, which slows the team’s ability to learn what works and make confident decisions.

This leads to three standard failure modes:

• False positives: A test looks like a “winner” when the effect is actually random noise.
• False negatives: A test shows “no difference,” even though the change might actually be better, but the site lacked sufficient data to detect it.
• Teams shipping inconclusive results: Because they can’t wait 8–10 weeks, they roll out whatever “looked good,” which creates a cycle of guesswork disguised as data.

They Tell You What Happened, Not Why

You see the result that one version “won,” but you don’t know what actually drove that behavior.

Was the page clearer?

Did users feel more confident?

Were they confused but nevertheless proceeded?

Did something unrelated happen at the same time?

Without knowing the real reason, teams start making decisions based on guesswork. You miss hidden UX problems, you repeat changes you don’t fully understand, and you end up trusting numbers that don’t tell the full story. That’s how A/B tests create blind spots and a false sense of certainty.

This problem is similar to the classic World War II survivorship-bias story.

When the military examined bullet holes in planes returning from missions, the fuselage appeared riddled with hits while engines seemed untouched. The initial instinct was to reinforce the areas with the most holes until statistician Abraham Wald pointed out the obvious: you only see the planes that survived. The ones hit in the engine never returned. The real insight was hidden in what wasn’t visible.

WWII aircraft with bullet holes mapped on returning planes, showing how A/B tests only show data from users who ‘survived’ the funnel, not those who dropped off. A/B tests work the same way. (Source)

They show you the behavior of people who made it through the funnel, the “survivors.” But the most important information is often in what you can’t see:

• Why people hesitated
• Where they got confused
• What they didn’t understand
• What made them abandon the experience altogether

The test result tells you Variant B won, but it doesn’t tell you whether it won because:

• The value proposition became clearer
• Users felt less anxious
• The layout reduced cognitive load
• The change accidentally nudged people forward
• Or, a completely unrelated variable influenced the outcome

You only see the outcome, not the mechanism.

And just like the WWII aircraft analysis, focusing only on the visible data (the converters) can lead you to reinforce the wrong parts of the experience. Without diagnosing why something worked or failed, you end up optimizing the bullet holes instead of fixing the real vulnerabilities.

To understand why a variant won or lost, you need more than the test result itself. A/B tests tell you what happened, but not what caused it. To find the reason, pair the result with behavior data and customer feedback.

Teams Run Tests on Fundamentally Broken Experiences

Many companies run A/B tests on pages that are already flawed (think, slow load times, confusing navigation, weak product information, unclear value propositions). With these issues, even a “winning” test doesn’t fix the real problem. It simply identifies the least harmful version of a bad experience.

You’ve probably seen this in your own funnels:

• The page loads in 4–6 seconds on mobile, but the team is testing button text.
• Users can’t understand the product, but the team is testing hero images.
• The navigation doesn’t match how customers actually shop, but the team is testing CTA color.
• Product pages lack clear sizing information or reviews, but the team is testing layout modifications.

This is why you only see small wins. The base experience is already weak, so no matter what you test, the improvement will always be tiny. You’re polishing something that actually needs to be rebuilt.

They Optimize Short-Term Uplifts, Not Long-Term Metrics

A/B tests measure immediate actions, such as clicks, add-to-cart, and purchases, within the same session.

But ecommerce businesses care about long-term outcomes:

• Customer lifetime value (LTV)
• Repeat purchases
• Margin and profitability
• Subscription retention

And these long-term outcomes often clash with what looks like a “win” in a short-term A/B test. In other words, something that lifts conversion today can easily hurt your profit, repeat purchases, or customer loyalty later, even though the test result looks positive in the moment.

Here’s what this looks like inside most ecommerce teams:

• A large discount often wins an A/B test because it increases immediate conversion. However, the company makes less money on each order, so overall profit declines even though the test “won.”

• A simplified checkout can increase purchases, but it may also make it easier for impulse buyers, fraudulent orders, or accidental purchases to slip through. None of these problems shows up in the A/B test results.

• Urgency or scarcity messages can boost short-term conversions, but they often reduce repeat purchases because customers feel pressured. The test looks successful, but loyalty drops.

• Showing more products on a page can increase clicks, but also overwhelm customers. This is the classic “choice overload” effect, demonstrated in the famous jam experiment by Iyengar and Lepper, where a larger assortment attracted more interest but led to fewer purchases. More options feel exciting in the moment, but they often reduce decision confidence and long-term value.

Jam experiment showing 30% purchases with 6 options vs. 3% with 24 options, showing how a variant that increases engagement can still reduce conversions, just like misleading A/B test ‘wins.’ (Image Source)

What High-Maturity Teams Do Instead

1. Use a Broader Experimentation Toolkit

A/B tests are not enough to answer many real business questions. In “Trustworthy Online Controlled Experiments,” Kohavi, Tang, and Xu show that many digital experiments produce tiny effect sizes and low statistical power, meaning a simple A/B test often can’t detect a meaningful impact.

This is why mature organizations routinely combine A/B tests with sequential tests, holdout groups, switchbacks, and quasi-experiments to get reliable answers.

Here’s how this plays out in practice:

• Sequential tests: Instead of splitting traffic, you run one version for a period of time, then the other. This helps when traffic is low or when you need to track what happens weeks later. For example, subscription companies often test onboarding flows in this way to determine which version retains more customers after 30 days.
• Holdout groups: You leave a small group of users on the old experience even after launching the new one. This shows whether the change actually improves long-term outcomes.
• Quasi-experiments: Helpful when clean randomization isn’t possible. Retailers often test pricing or merchandising by region or channel because splitting by user session would create noise.
• Switchback tests: The system alternates between Version A and Version B over time (e.g., hourly or daily) rather than splitting users. This is used when people affect one another’s experience. Ride-sharing and food-delivery companies use switchbacks to test matching and pricing systems because A/B tests are prone to breakdown under network effects.

Don’t force every decision into a binary A/B test. Match the experiment design to the nature of the problem.

Start with the business question, then choose the experiment that can truly answer it.

For example, if you want to know which onboarding flow retains more subscribers after 30 days, a sequential test works better than a short A/B test.

If you need to understand whether a new pricing model improves profit rather than just conversions, a holdout group will show the long-term impact.

If you’re testing merchandising or pricing by market, a quasi-experiment avoids the confusion of showing different prices to the same users.

And if you’re testing algorithms in systems where users interact with one another (like matching, ranking, or recommendations), a switchback test gives cleaner results than a normal split.

Improve Hypothesis Quality Through Research

Many experiments fail before they even start because of a weak hypothesis. If your idea comes from a random backlog item or internal opinion, your test is basically a coin toss. High-maturity teams reduce that risk by grounding hypotheses in real user evidence first.

Here’s what it looks like in practice.

Before launching a test, collect inputs from sources like:

• Session recordings and heatmaps: These tools show how users actually behave on key pages. Recordings let you watch real sessions (scrolling, clicks, pauses, backtracking, rage clicks). Heatmaps show where attention clusters and where users ignore important elements. For example, in the FigPii heatmap below, attention is concentrated around plan cards, helping identify what users see, skip, and where to place high-impact decision content.

• Funnel step drop-off data: This tells you where users abandon the journey between key steps (PDP → cart → shipping → payment → order confirmation). The best way to proceed is to define a single clean funnel, segment by device and traffic source, and compare where the drop-off is highest. Then, inspect only that step deeply before testing.

• On-site search logs: Search logs reveal what users want but cannot find quickly through navigation. This is high-intent data straight from the customer. To discover search logs, pull top search terms for the past 30–60 days, identify “high-frequency + low-result-click” queries, and map them to missing products, weak labels, or poor synonym handling.

• Customer support tickets and chat transcripts: Support tickets and chat logs show where customers are confused in their own words. If people repeatedly ask, “Will this arrive by Friday?” or “Can I return sale items?”, your delivery and returns information is insufficiently clear. Review the last 4–8 weeks of tickets, group them by theme, and prioritize the most frequent, revenue-impacting issues. Then test clearer delivery and returns messaging near the CTA and at checkout, and track checkout completion plus support-contact rate.

• Review mining and post-purchase feedback: Reviews tell you what customers expected versus what they actually experienced after buying. Extract recurring phrases from reviews, especially 3-star reviews (often balanced and diagnostic), and compare themes with PDP copy claims.

• Quick user interviews or usability tests: These explain the “why” behind behavior that analytics alone cannot explain. You hear intent, uncertainty, and decision criteria directly. Recruit 5–8 users from your target segment, give them realistic tasks (“Find a jacket under $150 and checkout”), ask them to think aloud, and note hesitation points and trust concerns.

Once you collect these inputs, the next step is to convert them into testable, evidence-led hypotheses.

A good hypothesis has four parts:

• Problem: What friction are users facing?
• Evidence: What data proves this friction exists?
• Change: What are you changing to solve it?
• Expected impact: Which behavior should improve if you’re right?

Here’s a format you can use when creating your hypothesis:

Because [evidence from research],
we believe [specific user problem],
so we will [specific experience change],
and expect [metric + direction + segment] to improve.

Here’s what it will look like in practice:

Because support tickets and session recordings show users hesitate at checkout when delivery timing is unclear, we believe uncertainty about arrival dates is reducing order completion.
We will show delivery-date estimates on PDP, cart, and checkout.
We expect checkout completion rate for mobile users to increase and delivery-related support tickets to decrease.

This is much stronger than vague ideas like “test CTA copy” or “try a new layout.”

Test Bigger Levers

Most teams keep testing easy things (button text, colors, tiny copy edits) because they’re quick to ship. That keeps the testing calendar full, but it rarely changes revenue in a meaningful way.

If you want bigger results, test changes that affect actual buying decisions, including what users understand, trust, compare, and choose.

Here’s what to test instead of micro-tweaks:

• Clarity of offer: Can a first-time visitor understand what you sell, who it’s for, and why it’s worth the price in 5 seconds? Test: hero copy, PDP headline/subhead, benefit framing, proof placement.
• Decision information on PDP: Are price, delivery timeline, returns, size/fit, and reviews easy to find before users scroll too much? Test: reorder PDP blocks so top objections are answered earlier.
• Findability (navigation + collection pages): Can users reach the right product in 2–3 clicks? Test: category labels, filters, sort defaults, collection structure.
• Offer design (pricing + bundles): Are you helping users choose the best-value option without forcing discounts? Test: bundles, quantity breaks, “most popular” anchoring, subscription framing.
• Checkout friction: Where do people pause or abandon because of uncertainty or effort? Test: guest checkout, fewer fields, clearer shipping/returns near CTA, upfront total cost.

This is also what you see in well-known experimentation programs.

For example, In Trustworthy Online Controlled Experiments, Kohavi, Tang, and Xu describe a Bing experiment where the team changed the ad layout in search results.

Instead of showing a short blue headline on one line and the first description line separately below it, they merged them into one longer, more informative headline. This made the ad easier to scan and helped users decide faster which result to click. The test produced a reported 12% increase in revenue (estimated at over $100M annually in the US at that time), and the effect was repeated in follow-up runs.

Although this example is from search ads, the same principle applies to ecommerce: changes to how users evaluate options (message clarity, information order, comparison cues) usually outperform cosmetic UI tweaks.

This Bing experiment shows that even small UI changes can create an outsized impact when they improve a core decision moment rather than a peripheral design detail (Source)

Tie Experiments to Business Outcomes

Many teams don’t pick metrics based on business value. They pick whatever is easiest to measure and easiest to move.

Data make this visible: over 90% of experiments focus on just five primary metrics, including CTA clicks, revenue, checkout, registration, and add-to-cart. In fact, CTA clicks alone account for 34.8% of primary metrics, followed by revenue (28.2%) and checkout (16.2%).

But the same chart shows the trap, i.e., the most commonly targeted metrics don’t necessarily have the highest expected impact (expected impact being defined as win rate × uplift).

For example, revenue and checkout show low expected impact (0.4% and 0.7%), despite being among the most common goals. Meanwhile, metrics tied to how people find and evaluate products, such as menu/navigation (6.0%) and scroll/engagement (3.5%), show higher expected impact but are rarely selected as the primary goal (menu/nav is only 1.4% of experiments).

The goal is to avoid this exact scenario—aiming at metrics that are common, not necessarily the ones most likely to move the business.

So what do high-maturity teams do differently? They make the experiment answer the business question first, then select metrics that align with that outcome.

Here are some best practices to align your experiments with business outcomes:

• Pick one north star outcome (OEC), not 20 random metrics. Don’t judge a test by 10 different numbers. If you look at enough metrics, something will go up, and you’ll call it a win even if the business didn’t improve. Choose one primary metric that matters to the business, like revenue per visitor, profit per visitor/order, or renewal/retention (for subscriptions). Track clicks and add-to-cart only as supporting signals to explain why the main metric moved, not to decide the winner.

• Add guardrails so you don’t “win” the wrong way. Add 2–4 guardrails you will not allow to worsen—typically profit/margin, returns/refunds, fraud/chargebacks, cancellations, and support tickets (use NPS or complaint rate only if you trust the data). Write a clear decision rule in the test brief, such as “Ship only if the primary metric improves and margin does not drop, and return rate does not rise.” Then check guardrails during the test (margin/fraud show up fast) and again 14–30 days later (returns and support issues lag).

• Design tests to capture longer-term impact. If the thing you care about happens later (like repeat orders, retention, profit, or customer lifetime value), a short A/B test won’t give you the full picture. It only shows what happened right away. A simple fix is to keep a small group of customers on the old version even after you roll out the new one. This gives you a clean comparison a few weeks later, so you can see whether the new version actually improved the business or just created a short-term spike. This is especially useful for pricing changes, discount rules, loyalty programs, personalization, subscription onboarding, and free shipping thresholds, as these often boost conversions quickly but can affect profit, repeat buying, and customer behavior over time.

• Use high-leverage metrics when the experience is fundamentally broken. If your site has basic problems (slow pages, confusing navigation, unclear shipping/returns, missing size info, or reviews), small A/B tests won’t help much. You can test button text all day, but people still won’t buy if they don’t trust the page or can’t find what they need. In this situation, focus your testing on fixing the big problems first, then measure results using business metrics like revenue per visitor, profit per order, or checkout completion (not just clicks).

• Use the same test template every time. Don’t decide how to judge a test after the results come in. Before the test starts, write down the same four things every time: (1) the main result you want to improve (for example, revenue per visitor or checkout completion), (2) the numbers you do not want to worsen (for example, returns, fraud, cancellations, support tickets, or profit margin), (3) the rule for what counts as a win (for example, “Ship only if checkout completion goes up and profit/returns do not get worse”), and (4) when you will check again after launch (usually 14–30 days later, or longer for subscriptions). This keeps teams from calling a test a success just because one number went up.

If you do just this, your program stops shipping “wins” that hurt profitability, loyalty, or customer experience, and your experimentation starts compounding.

Beyond A/B Testing Mistakes: Build a Stronger Experimentation Program

A/B testing is still one of the most useful tools in CRO. It helps you test ideas, reduce guesswork, and make decisions based on real user behavior.

Most “A/B testing mistakes” happen when teams try to use A/B tests for everything, even when the real problem is bigger than a page tweak. If you’re running lots of tests but seeing only small wins, it usually means you’re testing low-leverage changes, starting with weak hypotheses, or measuring success with the wrong metrics.

To strengthen your program, focus on a few basics:

• Define a primary business metric plus guardrails before you launch
• Start with user research (recordings, funnels, search logs, support tickets)
• Write hypotheses tied to a specific user problem
• Test higher-impact changes (messaging clarity, templates, IA, pricing/bundles, checkout friction)

If you want help spotting what’s holding your testing program back, Invesp can run a CRO audit of your experimentation process. We review your recent tests, pipeline, research inputs, and metrics, then deliver a prioritized list of the highest-leverage opportunities, so your next tests are more likely to drive meaningful growth.

FAQs about building a complete experimentation program

A/B testing vs. multi-armed bandits: which should I use and when?

Use A/B testing when you want a clean, reliable answer and you care about learning (what worked and why). Use multi-armed bandit tests when your main goal is to maximize results during test runs (for example, by sending more traffic to better-performing variants). Bandits are best for ongoing optimizations, while A/B tests are better for decisions you’ll roll out long-term.

What should we test first if our program isn’t producing wins?

If your program isn’t producing wins, the issue is usually not A/B testing itself. It is that your team is testing small changes or guessing instead of solving real buyer problems. Start by choosing one step in the journey where you lose the most people, such as product page to cart, cart to checkout, or shipping to payment. Watch 10 to 20 session recordings from that step and read recent support tickets to see what customers are confused about. Pick one or two clear blockers, such as unclear delivery timing or hard-to-find return information, and run a test to fix them. Measure the result using revenue or profit per visitor, not clicks.

How many experiments should we run per month at our traffic level?

Run as many experiments as your traffic can support without forcing short, unreliable tests. In practice, that means fewer, higher-quality tests (meaning tests based on a clear user problem, a specific hypothesis, and a change that can realistically move revenue), not small cosmetic tweaks. If you cannot reach enough conversions per variant in a reasonable time, run fewer tests at once and focus on bigger levers. Use a sample size calculator and a cap test duration, often 2 to 4 weeks, to avoid slow, misleading results.

Do we need multivariate testing, or is A/B/n enough?

Most teams do not need multivariate testing. It requires very high traffic because you are splitting users across many combinations, so tests often take too long or become unreliable. A/B/n is usually enough: test a few strong variants that reflect different ideas, then iterate based on what you learn. Use multivariate only when you have massive traffic, and you are specifically trying to measure how multiple page elements interact.

The post A/B Testing Mistakes: Why Teams Rely on A/B Tests (What to Do Instead) appeared first on Invesp.

Imagine walking into a bookstore where every shelf you pass seems to have the exact book you’ve been looking for. The store knows exactly what you love to read—before you even realize it yourself. It’s like your favorite shopkeeper can predict your next purchase, offering suggestions that feel perfectly tailored to you.

Like that bookstore, AI allows websites to anticipate user preferences, fine-tune interactions, and optimize experiences in real time—all with one goal: improving conversions. By automating data collection, AI gathers relevant information and provides insightful analytics that enhance user experiences and drive better decision-making in Conversion Rate Optimization (CRO).

Whether through personalized content, real-time adjustments, or predictive analytics, AI is helping businesses create unique, seamless customer journeys, ultimately boosting their bottom line. So, how does AI make this happen? Let’s discover.

What Is AI Conversion Rate Optimization?

AI conversion rate optimization (AI CRO) entails using AI to identify conversion friction faster, prioritize what to test, personalize experiences, and improve results such as conversion rate, revenue per visitor, and trial-to-paid conversion.

In plain terms: AI helps you spot patterns in behavior data that are hard to catch manually, then helps you act on them. It does not replace your CRO strategy. It speeds up insight generation and improves execution quality when your tracking and testing processes are solid.

AI vs. Traditional CRO

Traditional CRO typically involves manual analysis, heuristic reviews, and A/B tests run sequentially. It works, but it is often slow and bandwidth-heavy.

Here are some ways AI can help you maximize your CRO efforts and boost conversion rates:

• Faster diagnosis: AI can cluster behavior and VOC signals (session patterns, search terms, support tickets) so your team finds friction faster.
• Smarter prioritization: Instead of random backlog ideas, AI helps rank opportunities by likely impact and segment behavior.
• More relevant experiences: AI can personalize content, offers, or next-step guidance based on intent signals.

Sephora, for example, uses AI to recommend beauty products based on a customer’s preferences, past purchases, and even skin type.

Sephora AI-based product recommendations

Their virtual artist tool leverages AI to help customers “try on” makeup virtually, improving the chances that they’ll convert and make a purchase.

Sephora’s AI-based virtual makeup try-on tool for a better user experience (Source)

It’s not just about what AI can do for your business but for your customers. A personalized experience can make visitors feel more understood and valued, and more likely to complete a purchase.

AI-Powered Tools for CRO

In CRO, having the right tools is like having a well-stocked toolbox for a home renovation project. That said, AI-powered tools are like a more sophisticated version of hammers and nails in this context—they allow you to identify what your audience wants and requires and fine-tune your website accordingly to boost conversion rates.

Here’s a breakdown of some powerful AI tools you can use to optimize your site for better user experience, personalized content, and, ultimately, more conversions. 

1. Personalization Engines

Personalization is central to CRO, and AI-powered personalization engines help you deliver tailored experiences for each visitor.

Integrating AI-powered personalization engines with Google Analytics can provide deeper insights into user behavior and improve content personalization.

How It Works: AI tools can analyze user behavior in real time, including which pages they visit, which products they browse, and their past interactions with your site. Based on this data, they personalize the content users see, such as product recommendations or customized landing pages.

For example, OddBalls, one of the UK’s top underwear brands, uses AI Wishlist to display recently viewed items dynamically. After a visitor views at least three products, the AI creates a targeted on-site notification with tailored recommendations.

AI-based recommendations (Source)

This personalized nudge boosts engagement and encourages conversions by reminding customers of items they’ve shown interest in.

Pro tip: If you’re an e-commerce store, implement a personalization engine to show relevant products to each customer based on their browsing history. For a blog or content site, personalize articles or resources based on user behavior (e.g., show related articles based on what they’ve already read).

2. AI for A/B Testing

Traditional A/B testing is great, but AI takes it to the next level by running multiple variations and adjusting content in real-time. It’s like having a marketing team that runs experiments 24/7.

How It Works: AI tools like FigPii use AI to provide personalized testing recommendations based on user behavior and preferences. 

3. AI-Driven Chatbots

AI-powered chatbots are one of the easiest ways to engage users and guide them down the conversion funnel. These bots use natural language processing to understand user questions and provide instant responses.

How It Works: Tools like Intercom and Drift provide AI-driven chatbots that automatically answer customer questions, guide users through the buying process, and suggest products or services based on the user’s intent. 

They’re available 24/7 and offer personalized customer support that mimics the human experience, which is impossible with regular, algorithm-driven chatbots. 

Even governmental organizations are embracing AI chatbots. For example, Liverpool City Council implemented a virtual assistant to address common pain points in their digital channels. 

Liverpool City Council uses AI chatbot to address citizens’ queries (Source)

The bot helps citizens resolve queries about council tax and benefits in real-time, showing just how effective AI chatbots can be when it comes to replicating human-like customer support.  

4. AI for Predictive Analytics

Predictive analytics uses AI to analyze past user behavior and predict future actions. It’s like having a crystal ball that helps you understand when a customer is about to leave your site or is ready to convert.

How It Works: AI tools like Pendo or HubSpot use machine learning to analyze data and predict outcomes. For instance, if a user has shown interest in a product but hasn’t yet made a purchase, the AI might indicate that they will likely abandon the cart. It can then trigger a remarketing campaign or a personalized discount to help close the sale.

AI-Powered Heatmaps to Analyze User Behavior

Heatmaps visually represent where users click, scroll, or spend time on your page. AI takes this further by analyzing the data and offering insights on optimizing those areas.

How It Works: Tools like FigPii or Crazy Egg use AI to generate heatmaps and analyze user interactions. They provide data on which sections of your pages attract the most attention and where users drop off. AI algorithms also suggest changes to improve user flow and increase conversions.

FigPii heatmaps showing how users behave on your site (Source)

6. Dynamic Content Optimization

AI can dynamically change content based on who’s visiting your site. This means you can display different banners, product offers, or even pricing based on user data, like location or past behavior.

Here’s an example of dynamic content where the brand uses it to change the user’s first name when they land on the site, making the experience more personal. 

Dynamic content used for personalization (Source)

How It Works: AI tools like Unbounce or Convert allow you to show personalized content based on a user’s past interactions or demographic details. This creates a more engaging, relevant experience for the user, leading to higher chances of conversion.

Building a Data-Driven Optimization Culture

Embracing a data-driven culture of constant optimization is key to staying ahead of the curve. AI-powered CRO can help businesses optimize conversion rates with precision and efficiency. A data-driven culture can help businesses make informed decisions and allocate resources effectively. By leveraging AI, businesses can analyze large datasets, identify patterns, and make data-driven decisions to optimize their website and marketing campaigns.

Imagine having a team of data scientists working around the clock to analyze your website’s performance and suggest improvements. This is what AI brings to the table. By fostering a data-driven culture, businesses can continuously optimize their conversion rates and stay ahead of the competition. AI tools can analyze vast amounts of data in real-time, providing actionable insights that help businesses make informed decisions. This not only improves conversion rates but also enhances the overall user experience.

Identifying Opportunities for Improvement

AI-powered data analysis can identify patterns, trends, and anomalies that human analysis might miss. By analyzing user behavior data, businesses can identify areas for improvement and optimize their conversion funnels. AI can help businesses identify user drop-off points and target data-driven improvements. By leveraging AI, businesses can create a seamless experience that keeps users engaged and moving down the conversion funnel, boosting conversion rates.

Think of AI as a detective that can spot clues and patterns that are invisible to the naked eye. By analyzing user behavior data, AI can identify where users are dropping off in the conversion funnel and suggest targeted improvements. For example, if users are abandoning their carts at a specific point, AI can analyze the data to determine why and suggest changes to reduce drop-offs. This helps businesses create a more engaging and seamless user experience, ultimately boosting conversion rates.

Testing and Validation

AI-powered testing tools can accelerate the testing process by enabling multi-variant testing and real-time personalization. By leveraging AI, businesses can test multiple design variations at once, with AI adapting each one based on user behavior in real-time. AI can help businesses explore “what if” scenarios to help refine their strategies before making major changes. By leveraging AI, businesses can make data-driven decisions and optimize their conversion funnels with precision and efficiency.

Imagine being able to test multiple versions of your website simultaneously and see which one performs best in real-time. This is the power of AI in testing and validation. AI-powered tools can run multi-variant tests, analyzing user behavior to determine which design elements drive the most conversions. This allows businesses to make data-driven decisions and optimize their conversion funnels with precision. AI can also simulate “what if” scenarios, helping businesses refine their strategies before implementing major changes. This not only saves time and resources but also ensures that the changes made are based on solid data.

How AI Improves Data-Driven Decision Making

Imagine being a chess grandmaster who can see ten moves ahead. That’s what AI brings to businesses—clarity, foresight, and the power to act with precision. 

Instead of relying on gut feelings or delayed reports, AI enables real-time decisions that keep you ahead of the competition.

• Real-time data analysis and insights: AI analyzes data the moment it’s generated, highlighting trends or anomalies instantly. Take Domino’s Pizza as an example. Their Domino’s AnyWare system uses AI to track customer orders across platforms—apps, voice assistants, or even smart TVs—and analyzes real-time data to optimize delivery routes. The result? Faster deliveries and happier customers.

• Predictive analytics for forecasting customer behavior: AI doesn’t just analyze—it forecasts. As we’ve seen above in this article, Sephora uses predictive analytics to anticipate customer needs and suggest products customers are likely to purchase next based on past behavior. This not only boosts sales but strengthens loyalty by making shoppers feel understood.

• AI-driven precise targeting: Forget broad targeting—AI identifies micro-segments that drive better results. For example, Stitch Fix’s Outfit Creation Model (OCM) uses customer purchase history and current inventory to create personalized outfit suggestions, shared through emails, ads, and feeds. These hyper-relevant recommendations keep clients engaged and drive repeat business.

StichFix’s OCM model (Source)

Pro tip: Use AI to segment audiences by behavior or preferences and craft personalized campaigns that resonate with each group.

AI-Driven Personalization and User Experience

Say you walk into your favorite coffee shop, and the barista already knows your order. Now scale that level of personalization to millions of users online—this is how AI works to help you craft tailored experiences for your audience that make them feel valued.

• Creating personalized journeys based on user behavior: AI creates personalized journeys by analyzing vast amounts of user behavior data, such as browsing history, search queries, time spent on pages, and purchase patterns. Machine learning algorithms then identify patterns, preferences, and intent to deliver content or offers tailored to each user.

• Adaptive website design and content customization: Websites powered by AI adjust in real time to match user preferences. For instance, Spotify dynamically updates its homepage with playlists based on individual listening habits to keep users engaged and inspire customer loyalty. 

Spotify dynamic playlist (Source)

• Enhancing the customer experience through AI chatbots and virtual assistants: AI chatbots deliver frictionless support, answering questions and guiding users to solutions 24/7. 

Conclusion: The Future of CRO is AI-Driven

As businesses and customers strive for better customer experiences, AI appears to be an invaluable tool. It allows brands to move beyond basic metrics and dive deep into real-time data to predict customer behavior, perform automated data analysis, personalize content, and optimize every touchpoint on a website. 

The ability to adapt in real-time, automate complex processes, and tailor experiences for each user isn’t just a luxury anymore—it’s an expectation.

By using AI-powered CRO tools, businesses can analyze user data more deeply than ever before, leading to a personalized customer journey and a tailored marketing strategy. This leads to AI-driven conversion rate optimization and the creation of meaningful customer connections. The future is clear: as AI technology evolves, so too will the possibilities for creating more personalized, engaging, and optimized experiences for every user who visits your site. 

The post AI Conversion Rate Optimization (AI CRO): Framework, Tools, and Real Examples appeared first on Invesp.

A common misconception is that you only have to perform a conversion audit when something seems wrong on your website. 

But when you think about it, a CRO audit is very similar to a health check-up. 

Regular medical check-ups can help you stay on top of your health. 

Likewise, regular conversion rate optimization audits can help your website perform better in terms of conversions. 

Just like you don’t have to see a doctor when sick, you also don’t need to perform conversion audits only when your cart abandonment rate is high. 

You can also conduct CRO audits when you want to uncover revenue opportunities, improve the visitor’s online experience, and when you want to keep your CRO strategy up to date. 

Take this as a friendly reminder: If you are not regularly performing conversion audits, you’re leaving money on the table. 

In this post, we are going to take a deep dive into:

• What a conversion audit is, 
• Where should you perform it, 
• What you need to perform it,  
• And when you should perform it. 

Let’s get into it…

What is a CRO Audit? 

A Conversion Rate Optimization (CRO) audit is like a health check-up for your online store. Instead of measuring blood pressure or cholesterol, it examines the key parts of your site that influence conversions—things like your product pages, checkout flow, navigation, page speed, and analytics setup.

These are the areas that determine whether visitors move smoothly from browsing to buying, or abandon the process along the way.

Step-by-Step CRO Audit Framework

Step 1: Gather Quantitative Data

Before you dive into fixing pages, you need hard numbers. A CRO audit should start with quantitative data: the “what” of user behavior. 

Numbers won’t tell why people drop off, but they’ll tell where and how much revenue you’re losing.

To get that clarity, you’ll want to start with the following three essentials: 

• Analytics setup: Making sure tools like GA4 record what shoppers do: which pages they visit, when they add to cart, and if they buy. Without this, you’re guessing where people drop off.
  
• Conversion goals and benchmarks: These metrics tell how well your site is performing compared to your past numbers and industry standards. For example, if 2 out of every 100 visitors buy something from you (a 2% conversion rate), but the industry average is closer to 3%, you know you’re leaving sales on the table.
  
• Page performance metrics (Core Web Vitals & speed): This measures how fast your site loads and how smooth it feels when people interact with it.

Analytics Setup (GA4 events)

The first step in your CRO audit is to see how people move through your store. That’s what analytics setup is all about: configuring your tools so you can track every stage of the shopping journey, from browsing a product to completing a purchase. Without this, you’re just guessing where drop-offs happen.

The most common tool for this is Google Analytics 4 (GA4). Out of the box, GA4 tracks page views and some engagement, but for ecommerce, you need to go further by capturing shopping-specific actions (called events).

At a minimum, these four shopping-specific actions or events should be:

• view_item: fires when a visitor lands on a product detail page.
• add_to_cart: fires when they click “Add to Cart.”
• begin_checkout: fires when the checkout process starts.
• purchase: fires when payment is completed.

These events tell how many people progress from one step to the next and where they drop off.

For example, if 10,000 people view a product, 3,000 add it to cart, 1,200 begin checkout, and 600 complete purchase, you instantly know:

• Your product pages are strong (30% add-to-cart rate).
• But your checkout process is leaky (only 50% of users who begin checkout complete it).

That insight tells you where to focus your audit efforts.

But how do you set up these events? 

There are two common ways to get GA4 ecommerce events working:

1. Directly in your platform (easiest): 

If you’re on Shopify, WooCommerce, or BigCommerce, GA4 integrations are usually built in. Setup is simple:

• Get your Measurement ID. GA4 will generate an ID that looks like G-XXXXXXXXXX.

GA4 Web Stream details page showing Measurement ID (G-XXXXXXXXX) (Source)

• Add it to your platform. For example, if using Shopify, go to Settings → Customer Events → Google Analytics and paste in the ID. WooCommerce and BigCommerce have similar fields.
• Enable Enhanced Ecommerce. This makes sure product views, add-to-cart actions, and purchases are tracked automatically.
  

Note: You can follow these steps for a detailed step-by-step GA4 setup. 

2. Use Google Tag Manager (GTM) for custom setups:

If your platform doesn’t have built-in support, or you want to track additional “micro-conversions” (like clicks on size guides or coupon use), you’ll need Google Tag Manager (GTM). GTM is a free tool that sits between your site and GA4, letting you control exactly what gets tracked.

Here’s a simplified setup flow:

• Install GTM on your site. Add the GTM container snippet to your site’s <head> and <body>.
• Create a GA4 Event Tag. In GTM, go to Tags → New → GA4 Event. Give it a name like add_to_cart and enter your GA4 Measurement ID.

Example of a GA4 Event setup in GTM (here for view_item_list). You’d do the same for add_to_cart, begin_checkout, and purchase (Source)

• Set a Trigger. A trigger tells GTM when to fire the event. In the screenshot example, the event is view_item_list, which fires whenever a shopper views a product list (like a category page). 
• Repeat for Other Events:  For example: view_item → trigger when a product page loads. begin_checkout → trigger when the checkout page loads. purchase → trigger when the order confirmation page loads
• Test in Preview Mode. GTM lets you simulate actions to make sure each event fires properly.
• Publish the Container. Once tested, publish it, so your events now flow into GA4.

Note: For a full walkthrough, check out this GA4 Ecommerce Tracking Guide.

Conversion goals and benchmarks

Once your tracking is in place, the next step is knowing what “good” looks like. Conversion goals and benchmarks help determine whether your site is underperforming or overperforming compared to both your historical performance and industry standards.

Here’s how you can set up your conversion goals and benchmarks:

• Calculate your current conversion rate. Divide the number of purchases by the total number of visitors, and then multiply the result by 100. For example: 200 purchases ÷ 10,000 visitors = 2% conversion rate.
  
  
• Compare with industry benchmarks.
  

• • Cart Abandonment Rate: According to the Baymard Institute, the average global cart abandonment rate is 70.19% (Baymard).
    
  • Ecommerce Conversion Rate: Across industries, typical conversion rates fall around 2% (Tidio).

Average conversion rates vary dramatically by industry—from just 0.6% in home furniture to 4.6% in food & beverage (Source).

• Set realistic goals. If you’re at 2% today, aim for 2.5% in the next quarter instead of shooting for 5% overnight.

Pro tip: Don’t just track the final purchase. Also set goals for micro-conversions, such as add-to-cart clicks, email sign-ups, or checkout starts. You can capture these the same way you set up purchase events earlier (through your platform’s GA4 integration or GTM). Tracking them provides early signals of progress and reveals exactly where shoppers drop off.

Page performance metrics (Core web vitals and speed)

The third piece of your quantitative audit is site performance. Even if your offers are strong, a slow or unstable site will deter shoppers. Google refers to the key measures of performance as Core Web Vitals, and they’re now both a ranking factor and a conversion driver.

When you audit performance, focus on three Core Web Vitals:

• Largest Contentful Paint (LCP): how quickly the main product or hero image or headline loads. Target: < 2.5s.
  
• Interaction to Next Paint (INP): how fast the site responds to clicks, taps, and input across the page. Target: under 200ms.
• Cumulative Layout Shift (CLS): how stable the page is as it loads (no buttons shifting mid-click). Target: < 0.1.

Google’s core web vitals (Source)

You can check these using free tools like PageSpeed Insights or Search Console’s Core Web Vitals report. Always test mobile first, since that’s where most users drop off.

These tools show you exactly how fast your site loads (LCP), how responsive it feels (INP), and whether the layout shifts while loading (CLS).

These numbers will make the problem concrete. For example, PageSpeed Insights might indicate that your product pages have an LCP of 3.8 seconds on mobile, which is well above the 2.5-second target. That’s a clear signal that those pages are costing you sales.

Once you know which metric is failing, you can act: compress images if LCP is too high, remove heavy scripts if INP is slow, or fix shifting elements if CLS is poor. Then rerun the test to confirm improvements.

Step 2: Collect Qualitative Insights

Step 1 provided you with the data: how many people add items to their cart, start checkout, complete their purchase, and whether slow site speed is hindering them along the way.

But numbers alone can’t tell you why people abandon a product, leave the cart, or bounce from checkout.

That’s where qualitative insights come in. 

Qualitative insight tools show you the human side of the story, including what visitors see, think, and feel as they interact with your store. Combined with quantitative data, they provide a comprehensive picture of conversion barriers.

Here are the core methods to focus on to collect qualitative insights: 

Heatmaps, session replays, and scroll tracking

Heatmaps are one of the most useful tools in a CRO audit, as they show you how visitors actually interact with your site’s elements. While analytics (Step 1) told you how many people dropped off between product views and purchases, setting up heatmaps helps you uncover why that happens.

Heatmaps visualize visitor behavior using color codes:

• Red / Orange = high engagement (lots of clicks, taps, or attention)
  
  
• Yellow / Green = moderate engagement
  
  
• Blue = little or no engagement

This helps you instantly see what captures attention and what gets ignored.

There are three main types of heatmaps you’ll use in a CRO audit: click heat maps, scroll heat maps, and movement heat maps. 

• Click heat maps:

Click heat maps show you where people click or tap on a page.

For example, in the click map below, you can see strong red clusters on the brand logo and form fields, while the body copy stays blue. This indicates that visitors are paying more attention to the form than the messaging—a sign that your copy may need to be shorter or placed closer to the CTA.

• Scroll maps:

Scroll-based heatmaps reveal how far down the page people scroll. 

Take this scroll map below, for example. 

The bright red at the top means everyone sees the hero, but the fade to yellow and green further down shows most users never reach the reviews section. If your social proof is buried here, you’ll want to bring it higher.

• Movement heatmaps:

Movement heatmaps track where users hover their mouse (on desktop). 

It’s not perfect, but it often indicates where people are paying attention.

In the move map below, clusters around the headlines and form are expected, but the scattered red hot spots on plain text signal confusion, which means people tried clicking on text that wasn’t clickable. Turning that into links or clarifying the design can remove friction.

Finally, if heatmaps are the snapshot, session replays are the movie. Setting up session replays lets you watch real visitor journeys in real-time, showing where someone hovered, clicked repeatedly, or gave up. 

For instance, a replay might show a shopper rage-clicking a broken “Apply Coupon” button, or zooming in and out on mobile because the text is too small. These are frustrations you’d never spot from numbers alone.

Now, the question is: how do you set up heatmaps and session replays? 

Luckily, setting up heatmaps and session replays is straightforward. All-in-one CRO tools, such as FigPii, make it easy to track clicks, scrolls, and movements, and also record session replays, allowing you to watch real user journeys. 

The setup typically involves adding a small tracking script to your site, after which data collection begins automatically.

You don’t need to configure every detail yourself. Most platforms, like FigPii, offer step-by-step guides that walk you through the process of installing heatmaps, enabling scroll tracking, and turning on replays. 

Once set up, you’ll start seeing exactly how users interact with your store, and those insights become the foundation for spotting usability issues and testing ideas in your CRO audit.

Customer surveys & exit polls

Heatmaps and replays show you what people do on the page. But they can’t tell you what’s going on in the shopper’s head, including the doubts, questions, or reasons they didn’t complete a purchase. 

That’s where surveys and exit polls come in.

• On-page surveys help you capture feedback while users are still browsing. For example, you can ask: “What’s missing on this page?” or “What information would help you make a decision?”
• Exit polls trigger when someone is about to leave (like moving the mouse toward the browser’s close button). A simple question like “What stopped you from completing your order today?” can surface issues you’d never see in analytics.

​​The key is to keep surveys and polls short and respectful of the user’s time. Instead of a 10-question form, ask one or two questions that get straight to the point. 

For example:

• On a product page: “What’s stopping you from adding this product to your cart?”
  
  
• On a checkout page: “What nearly stopped you from completing your order today?”
  
  
• Post-purchase: “What almost kept you from buying, and what made you decide to go ahead?”

These single-line questions are quick for shoppers to answer, but they provide highly actionable insights. If 20% of respondents say “I wasn’t sure about the sizing,” you instantly know your size guide needs to be more visible.

A great example comes from our own Invesp CRO case study. Faced with a high abandonment rate, the team combined customer interviews and expert reviews to identify areas of friction in the checkout flow. 

This qualitative research revealed that users required additional reassurance to complete their purchases. Based on these insights, our team added urgency elements (such as “free shipping” and “only a few items left” prompts) and conducted an A/B test.

This image shows a checkout variation shaped by user interviews, where urgency cues (“Only 3 left”) boosted conversions by 17% (Source: Invesp CRO case study)

The results were striking:

• Conversion rate improved by 17%
  
  
• Average order value rose by 4%
  
  
• Engagement with key elements (gift wrapping, quantity, CTA) increased significantly.

This demonstrates how a couple of well-placed questions or interviews can uncover blockers that heatmaps alone would miss, directly leading to improved conversion rates.

Pro tip: Leverage tools like FigPii or Qualaroo to run polls and surveys. They make the setup simple: you choose the page, set the timing or exit intent, and start collecting responses.

User testing and interviews

While surveys and exit polls capture quick, in-the-moment reactions, user testing and interviews go deeper. Instead of asking a single question at checkout, you’re watching or talking to customers as they interact with your site in real time. This provides context that you can’t get from a pop-up survey.

Here’s how they work in a CRO audit:

In user testing, you recruit real shoppers (or people who fit your audience) and ask them to complete tasks like “find a product under $50 and check out”—and observe where they struggle. 

Even a handful of tests can reveal patterns: Nielsen Norman Group found that testing with just five users often uncovers 85% of usability issues, making it a high-impact method that requires a modest budget. 

Tools like UserTesting.com, Maze, or Useberry make this simple to run remotely.

Customer interviews go further by uncovering the thoughts behind the clicks. These are one-on-one conversations where you ask open-ended questions such as:

• “What almost stopped you from buying from us?”
  
• “How do you usually decide between two similar products?”
  
• “What information would make you feel more confident ordering?”

Unlike surveys, interviews capture tone, hesitation, and context. For example, a shopper might say, “I was ready to buy but wasn’t sure I could return it if it didn’t fit,” which directly highlights the need for a clearer returns policy.

That said, the key is to talk to the right people. Prioritize the following when recruiting people to interview: 

• Recent customers: ask why they chose you and what nearly stopped them.
• Cart abandoners: If you can reach them via email or remarketing, ask what held them back.
• Target audience lookalikes: Use tools like UserInterviews.com or social groups and ask what they’d need to see to make a purchase.

Recruitment can be as simple as emailing recent buyers with a $20 gift card offer for a 20-minute call, or letting a testing platform handle it. Either way, ensure that participants resemble your actual customers, as insights from the wrong audience won’t help you optimize.

Step 3: Prioritize High-Impact Pages

By now, you’ve got two powerful layers of insight:

• Step 1 (the numbers): where people drop off and how many make it through to purchase.
  
• Step 2 (the reasons): what trips them up, from missing info to confusing layouts.

The next step is focus. You can’t fix everything at once, so you need to prioritize the pages and flows that will make the most significant difference to revenue.

How to Run a CRO Audit on Product Pages 

The product page is the stage in the customer journey where visitors make the decision to purchase or not. This means whatever you do on product pages can make or break conversions. This is something to consider when conducting conversion audits on product pages. 

When it comes to product pages, there are four elements that you should focus on in order to make them convert more visitors into customers: 

• The product 
• The brand 
• Page design and user experience 
• Product page copy 

The product is the main center of attraction and the reason why people visited your website. It should be presented in a that alleviates fears and concerns that visitors might have. Using high-quality images and featured videos that show how to use the product may help answer questions that your potential customers have before they purchase your product. 

The brand is fundamental and it shouldn’t be an afterthought, even on product pages. Not everyone who purchases from you will go through your homepage, so its important to use your product pages to show your customers who you are and what you stand for. 

The page design and user experience can also impact conversions on your product pages. Visitors expect product pages to have a certain layout and features – if you arrange things in a different way, this might cause trust issues, and this will ultimately affect conversions. 

The product page copy is important because it is always the power of words that compel people to make a purchase. The more complex the product you’re selling, the more you need to have a product page copy that alleviates the fears and doubts that visitors might have.  

So, how do you assess your product page to make sure that these four elements are helping you convert more visits into sales? Here’s what you should look at…

Product Images 

How many product images do you have per product page? 

One or two images are not enough. 

Are your product photos giving customers enough visual information about the product? Are they showing the product from different angles? 

Another thing to look at when it comes to product images is linking the photos to product variants. This applies when the product has multiple variants (different colors, scents, etc). 

According to the Founder of ICEE Social, Mark Perini, 

“My experience as a web designer has taught me that when it comes to ecommerce, people DO judge a book by its cover, so invest in solid product photography.”

Product Descriptions 

Product descriptions are probably one of the most underutilized or overlooked elements on product pages. 

Over and over again, we’ve seen plenty of eCommerce sites that copy the product descriptions from their suppliers. This is a mistake you should avoid at all costs. 

A product description is an opportunity for you to show your potential customers how the product benefits them. So, we often recommend that you connect your product features to your benefits as this will influence a customer to buy. 

Here’s an example of how Apple connects iPod features to the iPod benefits: 

There are many ways you can make your product descriptions compelling. Another way of going about it is storytelling – you can talk about the history of your product in a captivating way that shows how unique your product is. Great product descriptions that incorporate storytelling anticipate the customer questions and they provide as many details as possible.

• What materials is the product made from? 
• What are the care instructions? 
• Where was the product made? 
• What is the weight of the product? 

– weave the answers to these questions to make your product descriptions more useful. Even if you’re telling a story about your product, you should always be thinking about the customer and not the product.

Clear Call-to-action (CTA)

Is your CTA button prominently displayed and working on different screen sizes and browsers? This is something you should always check before you publish your CTAs. 

The general rule of thumb is to place the CTA button above the fold, right under the product description. 

If a visitor lands on your product page, and your CTA button is not one of the first things they notice, then there’s a problem. Although your CTA button goes under your product descriptions, it shouldn’t be pushed to below the fold area. Another thing to remember is to avoid surrounding it with lots of distracting elements, and also use contrasting colors to make it stand out. 

​​Don’t try to be wordy or clever with CTAs. Keep your text short and sweet and straight to the point. The goal of your product pages is to get customers to press buy, short texts like ‘Add to Cart or Submit Order’ will do.

When a visitor clicks on your CTA, where does it take them? Check that all links are working properly and they are taking your visitor to the cart page. 

Social Proof 

When people can’t physically engage with your product, they will more likely have pre-existing fears and doubts about your product. Fortunately, social proof can help you overcome customer objections. 

Featuring social proof on your product pages can help move potential customers from inspiration to consideration and from consideration purchase. In fact, customers are six times more likely to buy a product if the page has social media pictures. 

There are different ways you can inject social proof into product pages: 

• Indicate how many people have already purchased the product. 
• Display customer testimonials, reviews, and ratings. 
• Display user-generated visuals of your product. 
• Highlight product awards and expert reviews. 

It is also important to think of where you will place these social proof elements. You want them to position in areas where customers can view them. 

We recommend that you place elements like ratings and the number of reviews above the fold. Customer testimonials and reviews can be positioned right under product descriptions. 

How to Run a CRO Audit on Cart Pages 

The ultimate goal of a cart page is to make customers complete a purchase. 

But from what we have seen over the years, customers also use cart pages as a tool for price comparisons, a wishlist, and also a place to refine selections of a product.

So, how do you maximize the number of conversions on this page? First of all, you start by ensuring that your cart page has these 3 elements: 

• Clear 
• Simple 
• Fast 

Clear means that there are no other distracting elements on your cart page that may deflate the focus of your customers. Every piece of information or element you add on this page should be clear enough to propel visitors into making a purchase. Be clear about your shipping and return policy. 

Simplicity often leads to success in eCommerce. Why? Because a confused user won’t make a purchase. Great cart pages have a simplified copy and design so there’s no room for confusion. 

Fast cart pages translate to a better user experience. And slow cart pages kill conversions. Stats show that 40% of customers will abandon a site if it takes more than 3 seconds to load. 

With that said, here are some of the questions you should seek to answer when auditing the cart page: 

1. When you offer one mode of payment, a high cart abandonment rate is inevitable. So, how many different payment options have you made available to your users? 
2. If anything, customers hate hidden shipping costs. So, is the information regarding shipping costs and return policy clear enough for customers to understand?
3. Remember, online customers have pre-existing concerns about the product. Do you have a live chat feature that will provide answers right away when a potential customer is on the cart page? 
4. Many users than before are now using their mobile devices to browse and shop on eCommerce sites. So, have you checked to see if your website is responsive on mobile? How does your text appear on mobile devices? Are your product images clear on mobile devices? 
5. How easy is it to checkout? How long does it take for users to complete the checkout process? The longer it takes, the higher the abandonment rate will be. 
6. Another unnecessary barrier common in cart pages is asking customers to sign up before they complete their purchase. Do you do the same or do you have a guest login option on your cart checkout process? 
7. Since you’re asking users about their card details, is there anything on your cart pages that will make them trust you? 

Conclusion

Let’s suppose you want to improve your conversion rate, user experience, reduce your cart abandonment rate, or explore revenue opportunities on your eCommerce website. 

In that case, you will significantly find value in conducting a conversion audit, no matter when you do it. But if you want the long-term success of your eCommerce website, you will have to perform a CRO audit regularly. 

Think of a CRO audit as a health check of your website. It can be done anytime to identify current problem areas, conversion leaks, and revenue opportunities on your website. 

The post Conducting an Ecommerce CRO Audit: A Step-by-Step Guide appeared first on Invesp.

Imagine you’re shopping online for a new pair of shoes. You visit an online store, but that e-commerce category page is overwhelming. There are too many options, filters aren’t helpful, and the page takes forever to load. Frustrated, you leave the site without making a purchase. 

Now, flip the scenario. You land on an ecommerce store with well-organized category and product pages that allow you to filter by style, size, and price ranges, with clear product images and descriptions. You find exactly what you’re looking for in minutes, and checkout is a breeze.

This is the difference an effective e-commerce category page design can make.

Learn how to create ecommerce product category pages that deliver a smooth shopping experience and boost sales. 

1. Define Clear Objectives

When creating effective e-commerce category pages, defining clear objectives is essential. 

This means knowing your target audience and setting goals for how you want your category pages to perform. It will also help you meet your audiences’ expectations and increase conversion rates. 

How will you identify your target audience’s needs? Here are some tips: 

• Use Customer Data: Look at your customers’ browsing history, previous purchases, and on-site search queries. This helps you understand what customers look for when visiting your site.
• Conduct Surveys: Ask customers directly what they expect from your category pages. Are they looking for more filters? Do they want faster loading times?
• Analyze Competitors: Look at similar businesses to see how their category pages are organized. Are they offering features that make browsing easier or faster? Are there ideas you can adapt or improve upon?
• Keyword Research: Research what keywords your audience uses when searching for products. This helps with on-page SEO and ensures your category pages are aligned with customer intent.

Once you identify your target audience and what they expect from your category pages, it’s time to set clear, measurable objectives for how you want your category pages to perform. These goals should focus on both user experience and business outcomes. 

Here are the metrics to consider when setting up clear goals: 

• Conversion rate: Track how many visitors to your category pages end up making a purchase. 
• Bounce Rate: Set a goal to reduce visitors leaving after viewing a category page without clicking further. If users leave too quickly, consider improving the page layout, product visibility, or filters.
• Average Session Duration: Track how long users spend on your category pages. The longer they spend, the more likely they will find something they like. Use features like filtering options and related products to keep them engaged. For example, Sephora uses engaging filters and user reviews within its category pages to keep shoppers browsing longer.

In addition, you should also consider “Revenue per Visitor.” This means setting targets for how much revenue each visitor to your category pages generates. You can improve this by adding upsell or cross-sell opportunities directly on the page.

2. Optimize Page Layout

A well-structured e-commerce category page is more than just a digital storefront—it’s the first point of contact that your customers will have with your products. Naturally, the category page layout can significantly influence user experience, conversion rates, and overall revenue. 

So, how will you ensure your category pages offer a smooth shopping experience to your audience? Here are some tips: 

Header (Clear Category Title): 

Your category title should be clear and precise so shoppers know what they’re browsing. Aside from the user experience, a well-written title will boost your SEO.

Glossier’s category page is a great example here. For their skincare section, they use simple, precise titles like “Face” and “Eyes” instead of complicated, technical terms.

This helps users quickly identify what they are browsing, improving user experience and boosting SEO because these titles match common search queries.

Filters and Sorting Options: 

Filters and sorting tools are beneficial when hundreds of products are listed on your category page. Depending on your product, add filters like size, color, brand, and price range to help users find what they need.

For example, H&M offers detailed filter options, including size, color, price, and specific details like sleeve length, neckline, occasion, and material type. This allows users to narrow their search precisely, making the shopping experience faster and more personalized.

Product Listings: 

Focus on showcasing clean, high-quality images that allow shoppers to zoom in. Accompany these with short, informative product descriptions highlighting key features and their benefits. 

Ganni, a contemporary fashion brand, is an excellent example of an effective e-commerce category page. Its website features high-quality, detailed images from multiple angles, allowing customers to zoom in and examine items closely—all from the category page itself. 

These images are complemented by concise, informative descriptions highlighting key features and benefits, such as material and fit. 

Overall, this approach helps shoppers understand and appreciate the product right from the category page, elevating their overall shopping experience.

Enhance Call-to-Actions (CTAs): 

Every product on the category page should have a clear CTA like “Add to Cart” or “View Details.” At the same time, make sure your CTAs are easy to spot and encourage users to take the next step.

Maintain a Clean and Uncluttered Design: 

More clutter can overwhelm shoppers and prevent them from leaving your site. On the other hand, a simple, minimalist design helps highlight the products and speeds up the page’s loading time.

Most importantly, remember to optimize your category pages for mobile devices. Statistics suggest that nearly 79% of e-commerce sales by 2025 will come from mobile devices.

Clearly, having a responsive, mobile-friendly layout is the need of the hour. 

Take Mujjo, for example, a Dutch brand specializing in premium leather tech accessories like gloves and phone cases. 

Mujjo’s e-commerce website showcases a minimalist, clean design that emphasizes its products with high-quality images and plenty of white space. The category pages are free of distractions, which allows customers to focus on the products themselves.

Pro tip: Test your category pages across various devices and screen sizes. Make sure the layout is easy to scroll, with large enough buttons and easy-to-read text on mobile.

3. Enhance User Experience

Imagine you walk into a store, but instead of neatly organized aisles, you find products scattered everywhere. You see shirts mixed in with shoes, electronics piled up in the corner, and no signs to help you find what you’re looking for. 

How long would you stick around? Probably not very long!

That’s how your website visitors will feel if they search a cluttered category page without any clear navigation path or proper filters and sorting options (as we’ve discussed in the above section). 

Improving your navigation is the first thing to cover when enhancing user experience. 

Make sure your category pages have easy-to-use menus and clear breadcrumb trails.

This will help users understand where they are and allow them to move between categories quickly. 

As a rule of thumb, adding a “Back to Top” button on longer pages is a great way to prevent users from scrolling endlessly.

Other key elements to enhance user experience include: 

• Clear, High-Quality Images: Add sharp, well-lit product images to highlight essential features. When applicable, include different angles or variations.
• Dynamic Recommendations: Use AI to recommend products based on browsing history or past purchases, increasing the likelihood of conversion.
• Optimized Page Load Speed: Compress images and minimize plugins to ensure fast load times. A slow page could lead to higher bounce rates.
• Responsive Layout: Ensure your category pages adapt well to various screen sizes and filters and menus are touch-friendly on mobile devices.

4. Create Engaging Content

Effective e-commerce category pages aren’t just about displaying products—they need engaging content that captures attention, informs customers, and drives them to purchase. 

The critical components of this are category descriptions and promotions. 

Your category description should be written in a way that both users and search engines can decipher the page’s purpose. For that, you need to: 

• Be clear and concise and organize categories logically
• Incorporate the right keywords (more on this later)
• Highlight key benefits 
• Add a human touch with a conversational tone to create a connection with your audience. 

Consider Magic Spoon, a brand that sells high-protein, low-carb cereals. Their category page’s content offers clarity, relevant keywords, benefits, and a personal touch.

Their category pages are clear, using titles like “Cereal Variety Packs” and incorporating SEO-friendly keywords such as “healthy cereal” and “keto-friendly.”

This mix of clarity, SEO, and engaging language makes their pages both user-friendly and optimized for search engines.

At the same time, add an extra touch and give a nudge to your visitors by offering them discounts. 

Shoppers love a good deal, and your category page is perfect for showing off promotions. This draws attention and gives them a reason to explore the category further.

Take ASOS, an online fashion retailer known for strategically placing discounts and promotions on specific category pages. 

ASOS often highlights limited-time offers like “30% off edit” accompanied with “Limited time only. While stocks last. Selected styles marked down on-site” at the top of particular category pages. 

This not only catches shoppers’ attention but also encourages them to explore more within that category, increasing engagement and conversion rates. 

ASOS also mentioned “Free Worldwide Delivery,” which enhances the shopping experience and further encourages the website visitors to make use of the discounts and offers displayed on the category page. 

5. Implement SEO Best Practices

Once you beautify your ecommerce category page and optimize it for easy navigation and mobile devices, it’s time to make it easily discoverable on search engines. 

The first step is to research targeted keywords your customers are searching for and incorporate them in your product titles, web page headlines, subheadings, product descriptions, and more. 

For example, if you’re selling shoes, a women’s shoe category page could target keywords like “women’s running shoes,” “comfortable shoes for women,” or “stylish women’s flats.”

You can use tools like Google Keyword Planner, Ahrefs, or SEMrush to find the best keywords for your category pages.

For example, if you want to research keywords using SEMrush, log in to SEMrush and go to the “Keyword Overview” section. 

Follow these steps next: 

• Enter a keyword related to your category (e.g., “women’s shoes”).
• Analyze suggestions based on search volume, competition, and relevance. For example, “comfortable women’s walking shoes” might be less competitive than “women’s running shoes.”
• Check keyword variations and questions to find long-tail keywords or subheadings, like “best running shoes for women.”
• Export the data and use the most relevant terms in your product titles, descriptions, and headlines.

But that’s not all. 

You must also optimize your title tag and meta description to include your primary keyword. The meta description should be under 160 characters, concise, and persuasive.

Make sure you also add: 

• Alt text with keywords to all images 
• Add internal links to other relevant pages or intermediary category pages within your website
• Schema markup to your category pages to help search engines understand your content better

6. Analyze and Adjust

After your e-commerce category pages are live, you must continuously analyze them to keep them effective. This involves tracking user behavior to understand what’s working and what’s not. 

A conversion optimization tool like FigPii can be beneficial. It provides access to heatmaps, session replays, and A/B testing features that show how customers interact with your pages.

Here’s everything you can monitor and continuously optimize based on the results you get: 

• Monitor Key Metrics: Track bounce rates, conversion rates, and time spent on the page. If people are leaving quickly, your page might need adjustments.
• A/B Testing: Test different layouts, product arrangements, or filters to see what resonates with your audience. FigPii makes it easy to run these tests.
• Session Replays: Use session replays to watch real users navigate your category pages, providing insights into confusing areas or barriers to purchase.
• Heatmaps: See where users click the most. If critical areas are ignored, you may need to reposition buttons or products.

Your Turn to Create Effective Ecommerce Category Pages!

Your ecommerce category pages in your ecommerce website are the path for guiding customers to the right products and boosting sales. 

A well-structured page with organized product categories improves user experience, reduces bounce rates, and increases conversions. By focusing on clear objectives, optimized layouts, relevant categories, and continuous improvement through data analysis, you can ensure your category pages are easy to navigate and help customers find what they need quickly. 

The post How to Create Effective Ecommerce Category Pages appeared first on Invesp.

In the ever-evolving ecommerce business market, staying ahead is about more than just keeping pace with today’s trends. Your traditional marketing efforts won’t suffice, either.

You must monitor changing trends and develop long-term and effective growth marketing strategies to improve customer lifetime value and stay ahead of the competition.

A future-proof e-commerce growth marketing strategy is built on deep market analysis, insightful consumer understanding, cutting-edge technology, and a focus on customer experience.

This article will discuss future-proof ecommerce growth marketing strategies in detail, along with tips and examples from successful brands you can emulate.

Market Analysis and Consumer Insights

For an e-commerce growth marketing strategy to be truly future-proof, you must base your approach on solid market analysis and consumer insights.

It will help you understand your target audience, anticipate market changes, and adapt your strategies accordingly.

But where do you begin?

Here are some best practices for conducting market analysis and consumer insights to create a solid growth marketing strategy for business growth:

Understanding your target audience:

The first step in crafting a future-proof strategy is to thoroughly understand your customers, what they value, and how they prefer to shop.

Here’s a quick overview of how to achieve this:

• Conduct Surveys and Feedback Forms. Regularly engage with your customers through surveys and feedback forms to gather insights about their preferences, pain points, and experiences with your brand.

• Utilize Social Media Listening. Monitor social media platforms for mentions of your brand, competitors, and industry trends. You can utilize tools like Hootsuite or Sprout Social to understand customer sentiment and identify emerging trends.

• Analyze Customer Reviews and Testimonials. Seek customer reviews and testimonials to determine what customers appreciate about your brand. Don’t forget to consider the areas that you can improve.

• Segment Your Audience. Categorize your customer base into different segments based on demographics, purchasing behavior, and preferences. This will help you create tailored campaigns based on each group’s unique needs.

• Use Behavioral Analysis Tools. Leverage modern-day behavior analysis tools like FigPii that come with heatmaps, session recordings, and A/B testing, among other features, to show how users interact with your website. For example, if heatmaps show that customers consistently ignore your main call-to-action, it might be time to test a new placement or design.

• Stay Updated with Industry Reports and Research. Subscribe to industry newsletters, attend webinars, and read market research reports to keep abreast of broader consumer trends and preferences.

• Engage with Customers Directly. Nothing beats direct interaction and understanding your customers. Host virtual Q&A sessions, engage in comments on social media, or even conduct one-on-one interviews with willing customers to get in-depth insights.

Demographics also play a crucial role in understanding your audience’s purchasing patterns.

For example, statistics suggest that Millennials and Gen Z prefer brands that stand for sustainability and ethical practices. A study by the World Economic Forum suggests that 75% of Generation Z (born between the nineties and the noughties, roughly spanning 1995 to 2010) prioritize sustainable purchases over brand names.

Conduct a competitive analysis.

Competitor analysis gives you insights into how your competitors conduct business and their products, prices, strengths, weaknesses, market share, and marketing strategies.

This will help you reveal market gaps that your ecommerce business can fill.

Amazon’s rise to dominance in ecommerce is partly due to its ability to identify and exploit gaps in the market, including faster delivery times, which also led to the creation of Amazon Prime.

Pro Tip: Conduct a SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) on competitors to gain insights into areas where your brand can differentiate itself.

(Source)

Keep abreast of market trends

Keeping abreast of market trends is paramount if you want to keep up with your competitors, stay innovative, and remain at the top of the market for years.

To do that, subscribe to all prominent platforms that regularly release industry-related reports and conduct market research. Some reputable market research firms you should read include Gartner, Forrester, Nielsen, and McKinsey.

They provide in-depth analysis, forecasts, and insights into consumer behavior, technological advancements, and industry shifts.

Another great tip is to identify and follow industry thought leaders, influencers, brands, and professionals in your industry on LinkedIn, Twitter, and industry-specific forums. They often share valuable insights, trends, and commentary on the industry landscape.

For instance, Invesp frequently posts conversion optimization tips and insights on their Twitter account.

This practice provides invaluable information for industry professionals, offering a glimpse into current best practices and future trends within the sector.

For example, Invesp’s Twitter handle routinely shares their conversion optimization tips and experiences.

Such information is incredibly useful for industry professionals, offering a glimpse into current practices and potential future trends.

At the same time, sign up for newsletters and publications that focus on your industry. Sources like The Wall Street Journal, Bloomberg, and industry publications such as TechCrunch for tech or Ad Age for marketing and advertising offer valuable news and analysis.

Invest in Technology and Infrastructure

If you want to craft a future-proof ecommerce growth marketing strategy, you must invest in technology that will help you stay afloat for years.

This investment supports current operational needs and positions a business to adapt to and capitalize on future market changes and consumer behaviors.

Scalable ecommerce platforms

As an ecommerce business, you should first invest in reputable, scalable, and secure ecommerce platforms.

Shopify and Magento stand out as scalable ecommerce platforms that you can use to grow and keep your business future-proof.

Shopify, for instance, supports millions of businesses in over 175 countries, offering a user-friendly interface, customizable templates, and support for growth.

Magento, with its open-source technology, provides businesses with a flexible ecommerce solution that can be scaled and customized to their specific needs.

Data analytics and customer insights platforms

One way you can stay future-proof is by continuing to meet your customers’ changing demands.

For example, customers’ demand for personalization in marketing and customer support continues to increase over time. You must stay mindful of these changing marketing trends and customer expectations to keep your business afloat.

Investing in credible data analytics tools will help your businesses stay updated with the latest customer data, which will help you drive decisions and personalize the customer experience.

For example, Stitch Fix, an online personal styling service, uses AI and machine learning to tailor its clothing selections to individual customer preferences, sizes, and styles.

How Artificial Intelligence Is Changing And Augmenting Retail The Amazing Case Of Stichfix

This technology-driven approach has revolutionized personal shopping by creating a highly personalized and efficient service.

Optimize for mobile devices.

The world is now turning largely to mobile devices over desktop sites. The trend continues to flow in the same direction for the coming years.

According to Statista, smartphones constituted around 78 percent of retail site traffic globally in the fourth quarter of 2023. What’s more, mobile alone was responsible for generating two-thirds of online shopping orders.

Optimizing your ecommerce site for mobile devices is one of the biggest parts of making your business future-proof. Not just future-proof, but looking at the numbers, it’s clear that optimizing for mobile commerce is also non-negotiable in the present context.

Automation for efficiency and personalization

Automation is another strategy every business is going out of its way to adopt.

Automation tools help you streamline operations, reduce costs, and enable personalized customer experiences.

As an ecommerce business, you might want to invest in the following automation tools to keep your growth marketing strategy future-proof:  

• Customer Relationship Management (CRM) Tools: Automate customer interactions, sales tracking, and customer data management to enhance the customer experience and improve retention. Example tools include Salesforce and HubSpot.

• Email Marketing Automation Platforms: Send targeted, personalized emails to different segments of your audience at scheduled times or based on specific triggers. For example, you can use Mailchimp and ActiveCampaign.

• Inventory Management Systems: Automatically update stock levels, track orders, and manage supply chain operations. Tools like Zoho Inventory and Shopify Inventory Management can help you minimize stockouts and overstock.

• Chatbots and Customer Service Automation: Provide instant responses to customer inquiries, automate common support requests, and offer a personalized shopping experience. Examples include Intercom and ManyChat.

• Ecommerce Analytics Tools: Collect and analyze data on customer behavior, sales trends, and website performance to inform business decisions. Google Analytics and FigPii are powerful tools for these purposes.

• Payment and Invoice Automation Systems: Simplify the checkout process, automate invoice generation, and manage transactions securely. Stripe and PayPal offer robust solutions for automating payment processes.

Implement Omnichannel Marketing

Gone are the days when you had to launch your product and run an email campaign to engage your customers.

Customers demand a more integrated and personalized shopping experience across all major platforms and devices.

They want the convenience of shopping directly on Instagram and the ease of browsing through a mobile app while also seeking the experience of a full-fledged desktop site.

A practical omnichannel approach can enhance customer satisfaction, increase loyalty, and drive sales by meeting consumers where they are.

If you look at omnichannel statistics and trends, businesses with strong omnichannel customer engagement strategies retain, on average, 89% of their customers, compared to 33% for those with weak omnichannel strategies.

With the number of online channels continuing to increase, the demand for an omnichannel strategy is also likely to increase.

So, if you still haven’t cultivated an omnichannel marketing strategy for your ecommerce business, it’s time to start now to make it future-proof.

When crafting an omnichannel marketing strategy, remember these key components:

• Consistent Brand Experience: Your brand messaging, aesthetics, and values should be consistent across all channels. Every touchpoint should reflect your brand’s messaging and value, from your website and social media to mobile apps and physical stores.

• Integrated Shopping Experience: Customers should be able to switch between channels without hassle throughout the entire customer journey. This includes browsing, shopping, and completing purchases interchangeably in-store, online, mobile apps, or social media platforms.

• Personalized Customer Interactions: Utilize customer data to tailor interactions and recommendations across all touchpoints, making each customer feel understood and valued.

You can take notes from Disney’s approach to omnichannel.

From their website to the “My Disney Experience” app, they’ve integrated every aspect of the customer journey.

Disney’s Omnichannel Experience (Source)

The app serves as a central hub for planning a visit to the parks, from purchasing tickets to booking FastPasses, all synced with RFID wristbands for in-park experiences, creating a seamless and personalized customer experience.

Create High-quality, Evergreen Content

Creating high-quality, evergreen content is a must-do if you want to stay relevant and generate leads from the same content for years.

This type of content is like the gift that keeps giving – it stays relevant and valuable over time, draws in traffic, generates leads, and establishes your brand’s credibility long after it hits publish.

Here are some tips to help you create high-quality, evergreen content:

• Choose Timeless Topics: Stick to topics that won’t expire faster than milk. Think how-to guides, product care instructions, or the ABCs of your industry – content that your audience will always find useful.

• Quality is Key: Aim for content that’s so good that readers can’t help but share it. Make sure it’s thorough, well-researched, and dressed to impress. The goal is to be the best answer out there.

• SEO is Your Best Friend: Optimize your content for search engines with savvy keyword research. Remember, it’s a balancing act – you’re writing for humans first, search engines second.

• Keep it Fresh: Regularly update your content to keep it relevant. A little refresh now and then can boost its ranking and show search engines that your content isn’t gathering dust.

The best example of this type of content is wikiHow Guides.

WikiHow has got you covered with step-by-step guides on everything under the sun. Their content is the definition of evergreen.

Invoke Customer Loyalty

As many as 73% of consumers say a good experience is key in influencing their brand loyalties, highlighting the importance of a customer-first approach in this new competitive market.

Once you garner enough loyal customers, they also become your brand advocates. This means they’re loyal to your brand and bring more potential customers for you through positive word-of-mouth.

Now, the question is, how will you turn leads into loyal customers who will continue to buy from you?

Of course, offering them top-notch products and customer service is paramount. But beyond that, you have to make them feel special every time they interact with your brand. You need to make them feel so special and understand that they wouldn’t dream of going anywhere else.

How will you make your customers feel special enough to become loyal to your brand? Here are some tips:

• User-Friendly Website Design: Make sure your site is easy to navigate, loads fast, and is mobile-friendly. A seamless experience keeps frustration at bay and encourages browsing.

• Personalization: Use customer data to tailor the shopping experience. From personalized emails to product recommendations, show your customers you know what they like.

• Top-Notch Customer Service: Be there for your customers with multiple support channels (live chat, email, phone). Quick and helpful responses can turn a complaint into a compliment.

• Reward Programs: Offer points, discounts, or special perks as part of a loyalty program. It’s a great way to say “thanks” and encourage repeat business.

• Exclusive Offers: Give your loyal customers first dibs on sales, new products, or exclusive content. It makes them feel valued and keeps them coming back.

Performance Analysis and Optimization

Performance analysis and optimization are other important factors that will help your e-commerce growth marketing strategy to be future-proof.

It entails measuring how well your strategies work, learning from the data, and tweaking your approach to boost performance.

Before diving into data, you need to know what success looks like for your ecommerce business – which includes setting clear key performance indicators (KPIs). Common KPIs include conversion rates, average order value, and customer acquisition cost.

Once you know which growth marketing metrics and KPIs matter the most for your business, it’s time to keep an eye on them.

One of the best ways to measure them is through analytics tools like Google Analytics and customer behavior analysis platforms like FigPii.

Google Analytics offers a treasure trove of insights, from which pages your visitors linger on to where they drop off. On the other hand, FigPii will help you understand customer behavior through features like heatmaps, polls, and A/B testing.

By visualizing how users interact with your site, you can make informed decisions to enhance the user experience, ultimately leading to improved performance metrics.

Beyond numbers, customer feedback can offer qualitative insights into what’s working and what’s not. Use surveys or feedback widgets to gather this valuable information.

Securing Your Ecommerce Growth Marketing Strategy

Successful growth marketers setting out to craft a future-proof ecommerce growth marketing strategy should focus on building a foundation that can adapt to and capitalize on the ever-evolving trends.

Every effort should be geared toward sustainable growth, from leveraging deep market insights and cutting-edge technology to creating a seamless customer experience and nurturing loyalty.

By staying informed, being adaptable, and continually seeking to understand and meet your customers’ needs, your ecommerce business can not only survive but thrive in the future marketplace.

The post How To Craft An E-commerce Growth Marketing Strategy appeared first on Invesp.

1. Define the purpose of your category page

Before you change layouts, add buttons, or run tests, you need to answer one basic question:

What should this category page help the visitor do right now?

Most brands create ecommerce category pages to serve one of three roles: helping visitors browse, decide, or buy. Each role demands a different design approach.

Browsing-focused category pages

On browsing-focused category pages, visitors are still answering: “What options exist here, and where should I look next?”

When you introduce conversion actions (like “Add to Cart”) at this stage, you’re asking them to answer a different question: “Am I ready to buy this specific thing?”

That creates decision conflict.

Instead of moving forward, the visitor now has to:

• Pause scanning

• Evaluate something they weren’t prepared to evaluate

• Either reject the action or back out to regain orientation

That interruption is what causes friction, not the button itself.

When an interface demands a higher-commitment decision than the user is ready to make, users slow down, backtrack, or abandon rather than comply.

On browsing-focused category pages, the page should instead prioritize:

• Clear subcategories that reduce mental load

• Strong visual hierarchy to support scanning

• Filters that help narrow options without overwhelming

2. What actions do visitors want to take on a category page?

It is not enough to think about what actions you want your visitors to take, you have to consider what actions a visitor expects to find on a category page. For example, I do not buy a product from the category page. I must click on the actual product, and visit its own page to read more details about it before I add it to my shopping cart. Other visitors might already know what they are looking for and having an “add to cart button” on the category page will simplify their order process. The intersection of items between actions you want the visitors to take and actions they themselves want to take provides a list of features and possible actions you should have on a category page.

3. Evaluate your category pages analytics data

Once you’ve determined the purpose of your page, one of the first things you should do when considering category pages is examining your analytics data to understand how well you current design is working for you. We usually expect category pages to have an exit rate similar or close to the site average. If you notice that your category pages are suffering from high exit rates this is an indication that visitors are exiting your website as opposed to continuing to navigate to product pages. Something in the design is not working all too well.

4. The minimum in creating category pages

Grouping your products into top level categories should be straight forward. On most websites, you should to take down that grouping at least one level further. A category such as Electronics is too large and should be broken down further into subcategories. The question is how much further you need to break down these subcategories. In general, we do not recommend having more than 3 levels of sub-categories under each of the top level categories. As the visitor is navigating through any of the categories, you should highlight some of the items listed in its “child” categories.

5. Determine the main features people ask for when shopping for your products

Consumers sometimes look for specific features when shopping for some products. For examples, if you sell TV sets, then the size and resolution of the different sets matters to many consumers. Sometimes the brand name or manufacturer information is important to visitors. When I shop for books, I am always looking for new releases. Each of these features represents additional ways to filter and regroup products within a category.

Circuit city uses a variety of features (category, screen size, resolution, etc) on their category page to allow visitors to further navigate to the section of the site most appropriate for them.

6. List the why visitors buy your products

what are the top needs visitors express when they shop for your products? When I am shopping for books, I need to get audio books so I can download them on my IPod. So, in that case, the type of media book available matters a lot to me.

BestBuy.com’s desktop section allows visitor to identify the needs they have for buying a desktop (Basic, photo & music, entertainment, gaming, etc).

Similar to the features of the products, the reason people buy a product will also provide you with additional ways to break down your category pages further.

7. Help the user select the appropriate subcategory:

If your product is complex, visitors might need some help deciding which product or subcategory is appropriate for them. A category page should provide a way for visitors determine the appropriate decision. You can provide buying guides or wizards that help the visitor determine which subcategory is most appropriate for his or her situation.

8. Let testing tell you what works and what does not

By following each of the steps above, you will be able to provide users with a variety of ways to interact with your category pages. But nothing is set in stone. Let your analytics as well as heat maps tell you which categorization most users are clicking on and which ones they do not use. I remember one client who added a “need base” filtration to the top section of his category pages. The team was very proud of it but visitor were not clicking on it. Two weeks later we removed that filter to use something else!

Any other recommendations or techniques you used on your website?

The post Ecommerce Category Page Design: Best Practices, Examples, and Tests That Work in 2026 appeared first on Invesp.

Most website polls pop up mid-scroll, block your view, and ask you something vague like “How are we doing today?”

And yet… when done right, a single well-timed poll can uncover the exact reason your visitors aren’t converting.

At Invesp, we’ve seen this play out countless times. A checkout page with strong traffic but low completion rates. A landing page where people linger but don’t click. A poll, placed thoughtfully and backed by behavioral data, can tell you why.

As Khalid often says, “Polls give you a few data points from many people and that’s their power. They’re not a replacement for qualitative research, but they sharpen it.”

In 2025, as third-party cookies fade and customer behavior becomes more fragmented than ever, polls have regained new relevance. They’re one of the last, direct ways to collect zero-party data (information users choose to share) while they’re actively engaging with your site.

In this guide, we’ll show you how to design, time, and phrase polls that actually help you increase conversions not irritate your visitors. You’ll learn:

• When to run a poll (and when not to)

• How to craft data-driven questions that yield actionable insights

• The types of poll questions that reveal motivators, barriers, and missed opportunities

• And how to integrate poll findings into your wider CRO strategy

Polls don’t have to be noise. When used with intention, they become a mirror, reflecting the truth behind your data.

Poll questions: where to begin

Writing poll questions is not about brainstorming a list of questions and typing them out on the poll software you intend to use. The process is not a pushover, prior to the exercise, a lot of research has to be done. Most Digital Marketers begin thinking about writing poll questions the very moment they need immediate feedback. 

But that’s far from the best way of coming up with poll questions. 

Instead, you need to have done enough research beforehand to enable you to come up with effective questions that will guarantee actionable feedback. The first question you need to ask yourself is, “What kinds of insights do we want from this poll?” 

To answer this question, take a step back and consider other CRO activities — Heuristic Evaluations, Analytics assessment, Heatmap, and Video Recording Analysis, Usability Testing, and customer interviews. The information that we derive from these activities allows us to make assumptions that are then further confirmed through polling.

For instance, after conducting 10 customer interviews, most respondents say that they typically go through a job change before subscribing to a specific service. In order to confirm this over a wider range of customers, a poll could be launched to ask if customers have recently experienced a job change.

Understanding who you are polling

Casting a wide net is never a good idea with polling. You need to determine the goal —who you are targeting with the poll (members, nonmembers, certain demographics, etc. 

Assuming that the poll is to be set on an e-commerce site, do you know the buyer’s journey stage that your targeted audience is in? It may be time-consuming upfront to track your visitors’ activities on your websites, but digital marketers need to understand the website traffic in relation to where visitors are in the buyer’s journey so that they can write poll questions that resonate with visitors. 

As you may know, at any given time, your web visitors are all at different stages in their journeys towards a purchase. People do not always follow the sequence of the buying journey, some visitors may skip other stages, and this makes this process a bit challenging. 

With that said, here are the five stages of the buyer’s journey are:

• Awareness stage
• Consideration stage
• Decision stage 
• Action stage
• Post action stage  

How then do you decipher the buyer stage that your web visitors are in? 

Well, Hubspot suggests this: 

Segment and report on the different types of website traffic, you can create a funnel-type dashboard to see your entire pipeline segmented by buyer’s journey stage. 

Here is a brief discussion on how you can tell what stage of the buyer’s journey your website visitors are in. 

• Awareness stage: most of your visitors are in this stage. They are aware of the products or services you are offering. So when they visit your website, they interact with your content, searching and looking for answers. 
• Consideration stage: the amount of this type of website visitors is significantly lesser than those on the awareness stage. They usually visit your product pages, benefits or features pages and the “About Us” page. 
• Decision stage: this kind of visitors spend time at your pricing page, visit the “Contact Us” page and go through your case studies deciding whether to make a purchase or not.
• Action: these visitors know your product or service and they know exactly what it would take to become a customer. They are easy to identify because they complete a purchase. 
• Post-action stage: this depends on the products you are because some products are a once-in-a-lifetime purchase. In such cases, you do not have to expect customers to come back.   

If you do not know the phase that your targeted audience is in, you may be at risk of asking the wrong questions, asking the right questions to the wrong users, or even worse, setting up a poll on the wrong page. 

Now that you have a clearly defined goal and you have figured out the phase which your targeted visitors are in, then you have to determine the type of poll you intend to run. Generally, there are four main types of polls: 

• A poll that appears seconds after page loads
• A poll that appears after a short delay. 
• A poll that appears when the user intends to exit the page by closing the browser tab. 
• A poll that appears when users reach the bottom of the page.    

Data-driven poll questions  

Most of Digital Marketers are still challenged when it comes to writing effective data-driven poll questions. Much of that challenge can be traced back to a failure to collect and use data to inform your user research techniques.  

The truth is, poll questions shouldn’t be crafted based on gut-feelings or assumptions. It’s much more effective to let your users’ behavior drive the creation of your poll questions — or else you risk coming up with irrelevant questions that visitors don’t really relate to. And if you are aiming to get genuine valuable feedback from your website visitors, the data you use to write poll questions has to be accurate as well as relevant to your goals. 

Single Grain gave a sweet explanation of data-driven approach: 

The data-driven approach focuses on creating high-quality posts that solve the audience’s problems or issues they care about by offering proof and backing up every claim with scientific findings, data, and up-to-date research.

Crafting data-driven poll questions doesn’t have to be overly complicated. Often times, the power of data is limited to measuring the effectiveness of campaigns and tracking how health the brand is, but smart Digital Marketers know that data can give you ideas on how to craft poll questions. 

Having said that, here are the different types of poll questions: 

• Poll questions on motivators
• Poll questions on barriers 
• Poll questions on hooks 
• Poll questions uncovering missing content 
• Poll questions that solicit feedback 
• Poll questions on satisfaction 

Poll questions on motivators

Basically, motivator questions can help you understand why are people coming to your site. The feedback you get from these types of questions helps you know where your real value as a brand is.  

Allow me to share with you a short story: I remember sitting aside two of my colleagues, a two months ago, and watching hundreds of session replay videos of a website of one of our clients in the e-commerce space. The aim was to see if users were seeing the CTAs on the site. 

So, as we watched the videos, we noticed that some users were scrolling aimlessly without clicking on any button. Some visitors would just open a page, and that’s it, no mouse movements —if you ask any optimizer, such behavior is suspicious. I mean, imagine someone walks into your store and suddenly they stand still for quite some time. 

After having seen such surprising behaviors, we were curious and we wanted to understand the motives. To do this, we set a poll that asked visitors to give an explanation of why they were on the site.   

One thing about using data is that it guards against biases.  Odds are extremely good that we would have tailored a completely irrelevant question that would have led us to get misleading feedback, thanks to session replay data. 

Knowing the answers to these questions will not only help you to understand certain user behavior, but you will be able to uncover the hidden value of your client’s business. 

Poll questions on barriers 

There are several reasons that may cause visitors not to convert on a website. Fears, uncertainties, and doubts also make the list. Polling your visitors can help you to pinpoint the exact barriers they are facing on your site. Reducing their FUDs will not only earn you the trust of your customers, but it can also ultimately increase your conversion rate

Suppose you are going through the reports on Google Analytics and it reveals to you that a number of visitors are exiting your website in one of the funnel pages. Chances are, you will assume that there is a usability problem. 

But to confirm this assumption, you can launch a poll to ask your customers if there is anything preventing them from making a purchase or if there is anything on the site that doesn’t work the way they expected it to.

This poll can be set on the exact funnel page with the highest exit rate. From the responses you get, you can come up with an optimization solution by implementing the customer’s recommendations. 

Depending on what your qualitative or quantitative data tells you, here are some of the poll questions on barriers you can use: 

• Is there anything preventing you from completing your purchase?
• What’s the one thing that nearly stopped you from placing your order?
• Was there anything about this checkout process that we should improve?
• What prevented you from doing what you came to the site to do?
• What was your biggest fear or concern about using us?
• What was your biggest fear or concern about purchasing from us?
• If you did not make a purchase today, can you tell us why not?
• What would’ve convinced you to complete the purchase of the item(s) in your cart?
• Do you have any questions before you complete your purchase?
• What could we do to make our website more useful?
• Is there anything on this site that doesn’t work the way you expected it to?

Poll questions on Hooks

Hooks are the exact reasons why your visitors prefer buying your products rather than from your competitors. So poll questions on hooks seek to reveal the reasons behind the purchase. 

Answers to these questions can give crucial insights about key features of your products that got them hooked, the valuable persuasion techniques that you were not aware of and they can also help you identify areas of improvement.  

To make you understand, let’s say that a Google Analytics report indicates that most of your conversions, this week, were made by returning visitors. In such a case, you may need to ask your visitors: Why did you choose to buy our products over others? Or this: What is the thing you like the most about our products?

Notice one thing, both questions are facilitated by the information gathered from GA. The questions are targeted towards specific customers who have made a purchase. If it wasn’t for the data we saw in GA, do you think we may have thought of asking such questions? 

Polls uncovering missing content

One of the worst mistakes you can make as a Digital Marketer is assuming that the information you are providing on your site is enough. The truth is, you can’t be so sure unless you get a confirmation from the exact people who use your website.   

But you can’t just throw a question to them from nowhere. You can ask your visitors about missing content if you notice a suspicious behavior may be when assessing other CRO activities. 

To show you what I mean, let’s say you are conducting a usability test, and you notice that some of your participants are struggling to find the information you tasked them to find. But in order to see if other users are facing the same challenge, you can launch a poll on your website asking more visitors if they are able to find what they are looking for. 

From this kind of polls, you are likely to get shocking responses —as some people may say that they are not seeing the information which is clearly shown on the page. 

Below is a list of some of our favorite questions that we use on polls that aim to unveil the missing content. They may not work for you unless they are backed by the data derived from other CRO activities.  

For category pages:

• What other products would you like to see us offer?
• How can we enhance the selection on the page?
• Were you able to find the products/information you were looking for?
• What other information would you like to see on this page?
• Do you use the filtration to look for the items you want on the page?
• Is the filtration on the page easy to use?

For Product Pages

• What other information would you like to see on this page?
• Is the description and product information sufficient on this page?
• Are you able to locate all the information you need on this page?
• Are the images sufficient for the product?
• What can we do to improve this page?

Poll questions that solicit feedback

A poll question that solicits feedback is exactly what it is —they ask visitors about their opinions on a specific feature, product or service. 

Digital Marketers and Salespeople usually use these types of questions when they are not sure about the quality of their services or when they have introduced a new feature on the site. 

For instance, suppose you have done a heuristic assessment of your website’s user interface, and you have detected some usability issues that you think your users are facing when they are interacting with your site. But to be sure, you can run a poll that asks visitors a question like this: what can we improve on our site to make it more user-friendly? 

Or maybe let’s say your website provides three services, and the Google Analytics data reveals to you that users are acquiring two services. You may consider discontinuing offering the service that is not getting much attention, but before you and your team make any final conclusions, set a poll and ask for your users’ feedback. In this scenario, you can ask this question: 

How would you feel if we discontinued offering [service name]?    

Poll questions on satisfaction 

Poll questions on satisfaction are meant to solicit responses that show what visitors are probably thinking about your website. By asking these types of questions, you can also get to know if your current customers are going to recommend your products or services to their friends.

But in order to ask these questions, it’s best if you look into your analytics data and see what is the percentage of new visitors vs. returning visitors. If the data shows a low percentage of returning users, then you have to further investigate by launching a poll that asks this question: does the content on our website meet your expectations? 

 Here are some of the questions you can use to measure customer satisfaction: 

• How likely would you recommend our product/service to your friends?
• Could you please rate your website experience today from 1 (poor) to 5 (very good)?
• How did you enjoy your website experience today?
• Did our website meet your expectations?
• Is there anything on this site that doesn’t work the way you expected it to?

Poll questions to validate data findings 

One of the more important roles for polling at Invesp is when we detect there is a particular trend in data and information customers are providing and we need to validate it. 

For example, for every project, we conduct interviews with customers. For one particular client, the customers spoke of the competing elements when determining the reason for the purchase, as well as the emotional connection that leads them to subscribe to our client’s service. 

We only interview a handful of customers, so in order to validate the information we run a poll to understand whether or not the majority of customers share the same experiences. We can then safely use the information in marketing materials and CRO changes on the site. 

Wrapping up…

So, there you have it. Yes, poll pop-ups may be annoying, but they don’t have to be, you just have to be strategically about how you come up with them and where you place them. Allow data to take the lead, then you will most likely get useful insights. There is actually a ton of data to draw from when working on poll questions.

The post Guide to Creating Website Polls That Actually Increase Conversions appeared first on Invesp.

Most teams waste time testing low-impact ideas. This playbook helps you focus your CRO roadmap on what actually lifts conversions.

The Four Phases of a CRO Program (The SHIP model)

A successful onversion optimization project follows the same rhythm:

• Scrutinize stage: You conduct various activities to determine possible testing areas on a platform or campaign.
• Hypothesis: You create a hypothesis for each of the testing ideas identified during the “scrutinize phase.”
• Implement: You validate your hypothesis through an AB or usability test.
• Propagate: you look for insights, share them within the organization and across marketing channels and verticals.

Think of it as a continuous loop rather than a one-time project. Each phase feeds the next, creating a compound effect on your site’s revenue and learnings.

1. Scrutinize — Gather Data and Identify Issues

Your goal here is to uncover why visitors aren’t converting not just where they drop off. Most marketers jump straight to testing without understanding the root cause. The Scrutinize phase fixes that by combining data, observation, and empathy to find what’s holding users back.

Think of your website as a sales conversation. When conversions stall, something in that conversation is breaking down. The Scrutinize phase is where you identify which part.

Here’s how to do it step-by-step:

Step 1. Start with quantitative data (the “what”)

Use your analytics to spot friction points.

• In GA4, check where users drop in your funnel, product pages with high exits, CTAs with low click-throughs, or forms with high abandonment.
• Use server-side or event-based tracking to fill gaps left by cookie loss — especially for checkout or login flows.
• Add scroll-depth and click tracking to see which sections lose attention.

Bugs, usability issues, and conversion blockers

I will take a quick detour to talk about different items we uncover as we conduct a conversion rate audit for a website.

1. Website bugs: areas where the website is broken and not functioning as expected. You should classify the bugs you identified in terms of priority (P1: blockers to P4: small items). Bugs are typically put into the “fix it right away” bucket.
2. Website usability issues: issues where website usability is not ideal. Usability issues are typically classified as either “fix it right away” or “research opportunities” buckets.
3. Conversion blockers: issues that relate to persuading visitors to convert. Conversion issues are typically classified as “research opportunities” bucket.

Many conversion consultants focus their effort on identify bugs and usability issues on a website and rarely pay close attention to conversion issues. Without getting into a philosophical debate, I firmly believe that is a vast difference between creating a user-friendly website and a highly converting site.

Usability issues:

1. Fixing usability issue on a website creates a user-friendly website.
2. Usability issues focus on making the site easier to use
3. Usability issues focus on top of mind issues for website users

Conversion issues:

1. Fixing conversion issues on a website creates a user-friendly website (Similar to fixing usability issues)
2. Conversion issues focus on making the site more persuasive
3. Conversion issues focus on psychological items that persuade visitors to convert

Every usability issue is a conversion issue but not the other way around.

Beyond problems – adding new website features

CROs focus a lot on issues that stop visitors from converting on a website. However, your research during the scrutinize phase should expand beyond that to include possible new features that you can implement on the platform to further enhance conversions.

Understanding your initial AB test plans: the research opportunities list

It is not enough to identify research opportunities list for a website. You will need to go a step further and determine our initial test hypothesis for each item in the list. The initial test hypothesis identifies how we think the particular issue could be tested/fixed.

A hypothesis is a predictive statement about a possible change on the page and its impact on your conversion rate.

Now, notice how I used the term “initial hypothesis.”

An initial hypothesis is the first stab our team takes on how we should address a potential problem on the website/webpage.

Example of initial hypothesis:

“Adding social proof will enhance the visitor trust in the website and increase conversions”

We use the initial hypothesis to help us assess each line item on our research opportunities list. When we decide to implement a particular test, we further develop our initial hypothesis to a

“concrete hypothesis.” Let’s take the initial hypothesis above and see the concrete hypothesis for it:

Based on qualitative data collected from online polling, we observed that website users do not trust the brand and are unaware of how many users are using it. Adding social proof on the homepage will increase visitors trust and improve conversion rates by 10%.

A concrete hypothesis

• states how we identified the issue
• indicates the problem identified on the page
• states the potential impact of making the fix (we set an actual numerical goal for the test)

Now, that you have your research opportunities list and each item has an initial hypothesis attached to it, we are ready to go through the exercise of prioritization items on our research opportunities list.

Prioritizing your AB testing ideas (the research opportunities list)

CRO practitioners have used several frameworks to classify testing ideas. I will cover some of the common frameworks and suggest a new model use.

Karl E. Wiegers explains:

 “When setting priorities, you need to balance the business benefit that each function provides against its cost and any implications it has for the product’s architectural foundation future evolution.”

Pie by Widerfunnel

Pie framework evaluates items based on three different factors: potential, importance, and effort.

1. Potential: Not all of your testing ideas will present the same potential in terms of increasing conversion rates. A good example of this is testing different color of a CTA on a page (no real impact to little effects) compared to changing page layout to emphasize value proposition.

While the potential is significant, it is very subjective. What I might think will have a significant impact on bottom line, someone else might think it will have no effect.

2. Importance: How important is the page you are optimizing?

The Widerfunnel team defines Importance as follows:

“How valuable is the traffic to the pages? Your most important pages are the ones with the highest volume and the costliest traffic. You may have identified pages that perform terribly, but if they don’t have a significant volume of expensive traffic, they aren’t testing priorities.”

According to Chris Goward:

“How do I figure out where to test first?”It’s a smart question to ask. You can’t test all pages at once. With limited time and resources to commit and, most importantly, limited traffic to allocate to each test, test prioritization is an important part of your conversion optimization plan.”

3. Ease: How easy is it to implement the test? Widerfunnel defines ease as:

There are two elements to consider when it comes to ease:

• Technical implementation
• Organizational or political barriers”

Both of these elements impact how easy it is to implement a testing idea, albeit, they are somewhat subjective.

Hotwire framework

Pauline Marol, the Lead Product Manager for optimization at Hotwire introduced this model back in 2015.

Here are the elements in this framework:

• Main Metric
• Location
• Fold
• Targeting
• New Information
• Benchmarking
• Conversion Veins
• Strategic Topic
• Mobile
• Opaque

What I like most about this model is the specificity it provides the potential problem and potential fix. It also brings the idea of how strategic a test to the overall business objective for a business. According to Pauline Marol: 

“Prioritization is a critical part when building an efficient, impactful testing program. Creating a framework to make smarter choices and thinking deeply about the key factors will make your program successful in the long term.”

PXL framework from CXL

The PXL framework uses the following criteria to score items on your research opportunities list:

• Is the change above the fold? Changes above the fold are noticed by more people, thus increasing the likelihood of the test having an impact
• Is the change noticeable in under 5 seconds? How fast does a user notice the change?
• Does it add or remove anything? The idea is that “removing distractions” or “adding key information: will have more impact
• Does the test run on high traffic pages? Changes to “high traffic page(s)” will have a larger impact on the bottom line.
• Designed to increase user motivation: does the introduction of your solution increase visitor motivation? Highly motivated visitors are more likely to convert
• How was the problem identified?
  • User testing
  • Quantitative data
  • Qualitative data (polls, surveys, etc.).
  • Mouse tracking heat maps or eye tracking
• Ease of implementation

The PXL framework is a step in the right direction.  Peep listed three main advantages to using it:

1. It makes any “potential” or “impact” rating more objective
2. It helps to foster a data-informed culture
3. It makes “ease of implementation” rating more objective

The central theme is the focus on trying to establish a more accurate model to score different line items on your list.

I believe that there is room for improvement for the following reasons:

1. All of the prioritization frameworks use a mix of points to score the identified issue and the potential fix. But a single problem could have multiple possible solutions to it. And each potential solution should be assessed with a different score.
2. A potential problem could be identified in various ways which give it a higher score. But does identifying a problem in 4 ways make that problem a more significant issue compared to a problem identified in 3 different ways? At some point, adding more ways to how a problem is detected should not give the problem more weight.
3. There is not enough focus on how a potential solution could impact visitors view of the website. PXL does an excellent job of using motivation, but there are other criteria that we should consider when scoring a possible solution.
4. The models do not distinguish enough between the different types of pages (top of the funnel, mid of the of the funnel and bottom of the funnel
5. Finally, the models use “high traffic pages” as a way to score a problem. Since analytics gives a specific number to identify what is a high traffic page, we should use that.

Invesp Prioritization framework

Let me state this again; a particular problem can have multiple initial hypotheses of how we can fix it. Some of our team members like to call these as testing ideas. This is important because each problem and each initial hypothesis are called out as separate line items in our prioritization framework.

You can address a single research opportunity in different ways that require different time to implement and will have a different impact on the bottom line.

Next is the criteria we use to evaluate each research opportunity:

1. What is the potential Impact?
2. Is the problem above the fold?
3. Was the problem discovered through expert review?
4. Was the problem identified through qualitative research?
5. Was the problem identified through user testing?
6. Was the problem identified through analytics?
7. Was the problem identified through heatmaps/Video recording?
8. Known top competitor feature?
9. Does the test idea enhance primary conversion goal?
10. Is implementing the change easy (politically, LOE)?
11. Adding or removing an element?
12. Does the test idea increase visitor trust?
13. Does the test idea reduce FUDs?
14. Does the test idea incentivize visitors to act right away?
15. Does the test idea increase engagement?
16. What type of change?
17. What type of page?
18. The percentage of page views

Not all of these items carry the same weight.

Let’s discuss some of these elements:

1. Potential Impact: we do think that this is a subjective measure. However, we did not delete it. The value of the impact is high (score of 4), mid-impact (score of 2) and low impact (score of 1).
2. Is the problem above the fold: where did you uncover the problem? The higher the location of the problem on a page, the more likely visitors will notice it.
3. How did you discover the problem: most CROs will conduct a mix of activities to uncover issues on a site. Each of these activities should be called out. These are
4. Expert review (some might refer to it as heuristic analysis),
5. Analytics data
6. Heatmap/session
7. Qualitative data
8. User testing

Most conversion blockers are uncovered through a combination of the above elements. So, we decided to take a weighted average as follows:

If an item discovered through one method                     score of 3

If an item identified through two methods                      score of 6

If an item identified through three methods                    score of 9

If an item identified through four or five methods        score of 12

4. Known competitive feature: there are instances where you want to test an item because you observed that one of your competitors have implemented. By no means should you understand this as a way to copy your competitors, but you should not ignore them either.
5. Does the test idea enhance primary conversion goal: what is the primary conversion goal for the page? Is your testing idea going to increase that conversion goal?
6. Is implementing the change easy (politically, LOE)?
7. Adding or removing an element: Your test can do several things at the same time:

Add or remove an element: scored at 3

Replace an element: scored at 2

Change the location of an element: scored at 1

Emphasize an element: scored at 1

8. Evaluation of visitor-centric factors that would impact how a visitor perceives a page:

• Does the test idea increase visitor trust?
• Does the test idea reduce FUDs?
• Does the test idea incentivize visitors to act right away?
• Does the test idea increase engagement?

Two or more elements gives you a score of 6. One gives you a score of 3.

9. Type of change: This focuses on the testing idea at hand. Are you:

• Focused on an element level (changing a single element) scored at 1
• Focused on page level (changing layout or several elements on the page) scored at 2
• Focused on visitor flow around the website scored at 3

10. Type of page: How is the page classified in your funnel?

• Top of funnel page scored at 1
• Mid-funnel page scored at 2
• Bottom of the funnel page scored at 5
• Global Change scored at 5

11. % of page views: By looking at the % of unique page views the page gets compared to the overall website page views, you can select one of the following values:

Is there a perfect prioritization framework?

I do not think there is a perfect framework out there. We continue to tweak this framework as we work on different projects. On a recent project, our team identified close to 200 research opportunities on a project. We ran it through a previous version of the framework and looked at the results. Some of the top items confused us. It did not make sense that we should start with them. We went back and reworked some of the formulas. I am sure that someone can take the same framework and tweak it further. According to Chris Goward:

“There are no standard rules for which pages are best to prioritize. Your website lives in a unique target market, including factors like your competition, seasonality, and internal cultural environment; all of these affects how your site is used and should be optimized. The priority rating you give each of your potential test pages will depend on this unique business environment.

It is a step in the right direction. We tried to build on some of the already existing frameworks out there and add more elements that impact prioritization on our different projects.

You can download the excel for the prioritization framework from here.

As always, if you have suggestions, please do let’s know!

Frequently Asked Questions

What is Conversion Rate Optimization (CRO)?

• Answer: Conversion Rate Optimization, or CRO, is the practice of increasing the percentage of website visitors who take a desired action, such as making a purchase or filling out a form. It involves analyzing user behavior and implementing changes to improve the user experience and boost conversions.

What is a Conversion Funnel?

• Answer: A conversion funnel is a series of steps that a website visitor goes through before completing a desired action. It usually starts with attracting the visitor to the site and ends with them taking an action like making a purchase.

What is A/B Testing?

• Answer: A/B testing is a method where you compare two versions of a webpage or app against each other to determine which one performs better in terms of conversions.

How Do I Prioritize My A/B Testing Ideas?

• Answer: Prioritizing A/B testing ideas involves evaluating the potential impact, ease of implementation, and relevance of each test. Frameworks like PIE (Potential, Importance, Ease) or the Invesp Prioritization Framework can help in this process.

What are FUDs in CRO?

• Answer: FUDs stand for Fears, Uncertainties, and Doubts. These are psychological barriers that can prevent a visitor from converting. Identifying and addressing FUDs can significantly improve your conversion rate.

What Does ‘Above the Fold’ Mean?

• Answer: ‘Above the fold’ refers to the portion of a webpage that is visible without scrolling. Elements placed here are more likely to be seen by visitors and therefore have a higher impact on conversions.

How Long Does It Take to See Results from CRO?

• Answer: The time it takes to see results from CRO can vary widely depending on the changes made and the metrics you’re tracking. However, a good rule of thumb is to allow at least a few weeks for meaningful patterns to emerge.

The post Creating A Conversion Roadmap: How to Prioritize Conversion Problems on Your Website appeared first on Invesp.

Your site is getting healthy traffic, your campaigns are performing well, but conversions just aren’t where they should be. You open your analytics dashboard and see a familiar pattern—visitors browse a few pages, maybe add something to the cart, and then… drop off.

At that moment, one question keeps coming up: Where do we start optimizing?

Do you fix the landing pages where visitors first arrive? The product pages where they hesitate? Or the checkout that seems to lose the most customers?

This is the challenge every marketer and CRO team faces. Beyond just running A/B tests, optimizing conversion funnels is about deciding where those tests will make the biggest difference.

In this guide, we’ll break down how the conversion funnel actually works, what happens at each stage, and how CRO experts decide where to begin.

Understanding the Conversion Funnel

A conversion funnel shows how visitors move through your website before they buy or complete a goal, such as signing up or requesting a demo.

A conversion funnel tracks every step:

• People first land on your site (awareness).

• Some browse your products or services (interest).

• A smaller group adds items to the cart or signs up (consideration).

• And only a few finally make a purchase or convert (action).

By mapping this journey, you can see where people stop (whether on product pages, forms, or checkout)  and focus your optimization there.

Tools like Google Analytics 4’s Funnel Exploration or FigPii help you see this in action. They let you plot each step of your customer journey. For example, product view > add to cart > checkout > purchase—and then show how many users drop off at every stage. If you notice that 60% of visitors abandon the cart page, that’s a clear signal that your checkout flow needs fixing.

It’s called a funnel because the number of people shrinks at each step. For example, Shopify data shows the average ecommerce conversion rate is only 2.5-3%, meaning most visitors drop off somewhere along the way.

Once you’ve mapped your funnel, it helps to break it into clear sections. Every website, whether ecommerce or SaaS, has three broad stages: from discovering your brand to becoming a paying customer. Understanding these stages is key before deciding where to optimize first.

The Three Stages of the Conversion Funnel

The conversion funnel is usually divided into three parts:

1. Top of the Funnel (Awareness): when people first discover you.

2. Middle of the Funnel (Consideration): when they compare and learn more.

3. Bottom of the Funnel (Decision): when they’re ready to act or buy.

Each stage has a different goal, a different user mindset, and its own optimization focus. Let’s look at what happens at each one.

Top of the Funnel (Persuasion)

This is the first contact visitors have with your brand, usually through an ad, blog post, or landing page. They’re curious but not yet convinced. Your goal here is simple: help them understand why you exist and why they should care.

At this stage, people are forming their first impression. The visuals, copy, and tone should all work together to build curiosity and trust. For example, Lakkadhaara, a handcrafted furniture brand, uses its homepage and Instagram ads to attract first-time visitors.

Once you click their Instagram ad, you’re directed to a landing page with phrases like “Handcrafted Luxury” and “Made in India,” highlighting craftsmanship and identity rather than pushing a sale. What’s more, their imagery, featuring warm lighting, solid-wood textures, and styled interiors, draws users in emotionally before they even view a product detail page.

That’s the essence of top-of-funnel persuasion: create awareness and emotional connection first, then guide users deeper. Keep your landing pages fast, clear, and aligned with the ad or keyword that drove people to them. The copy should highlight your value and end with a single explicit action, like read more, explore collections, or learn about your brand story.

Metric to watch: Bounce rate or time on page. If visitors leave quickly, your first impression isn’t strong enough.

Middle of the Funnel (Informational)

At this stage, people already know who you are and are comparing options. They read product details, pricing pages, or guides. Your job is to build trust and answer objections. Add FAQs, customer stories, or comparison tables that make it easy to evaluate your offer.

Metric to watch: Product-page engagement or demo-request rate. Rising engagement shows growing confidence.

Bottom of the Funnel (Where Conversions Happen)

Now visitors are ready to buy, but they can still change their minds. Even small points of friction here (long forms, surprise fees, poor mobile layout) can kill conversions.

Encourage them to take the final action by making your checkout or sign-up flows short and predictable. Reinforce trust with security badges, reviews, and transparent pricing.

Metric to watch: Cart-abandonment rate or form-completion rate. These tell you how smooth your final step really is.

Where to Start Optimizing Your Conversion Funnel (Expert Insights)

Now that you know what a conversion funnel looks like and how it works from top to bottom, which part of the funnel should you optimize first? To answer this, we reached out to a few conversion rate optimization experts and asked them the same question. Here’s what they had to say: 

Bottom-Up Approach — Spencer Gray’s View

Spencer Gray believes that the bottom of the funnel is often the best starting point, especially when traffic isn’t the problem.

Spencer Gray Senior CRO Specialist at 97th Floor/h4>

“If traffic isn’t an issue and you are getting enough visitors at the bottom of the funnel, we always test there first,” says Gray. “We work bottom-up because our job is to increase conversions, not make the home page pretty. Once the bottom is optimized, we move backward.”

Gray’s approach focuses on immediate ROI: fixing leaks where purchase intent is highest. Optimizing checkout, cart flows, and payment clarity often delivers the fastest measurable gains. He also notes that funnel optimization is cyclical, so after improving checkout, revisit the top of the funnel to ensure traffic quality keeps pace.

Start Where the Data Points You — Brian Massey’s Approach

For Brian Massey, Conversion Scientist at Conversion Sciences, there’s no fixed entry point. The funnel itself and the data within it will tell you where to begin.

Brian Massey Conversion Scientist at Conversion Sciences

“We let the data tell us where we should start,” explains Massey. “If we see people abandoning landing or category pages, we start there. If add-to-cart rates are low, we focus on product pages. It depends on where the problem is.”

Instead of making assumptions, Massey looks at quantitative data, such as funnel visualization reports in GA4 or session recordings in CRO tools like FigPii to locate where users most often drop off or hesitate.

Here’s what this means in practice: 

• If analytics show a high exit rate on category pages, that suggests users aren’t finding relevant products easily, which could point to poor filtering or unclear product hierarchy.

• If add-to-cart rates are low despite good traffic, the issue might lie in how value propositions or product details are presented.

• If checkout abandonment spikes, it could mean hidden fees, too many form fields, or low trust signals at the payment step.

Massey’s approach is diagnostic: begin with data to pinpoint what’s broken before deciding how to fix it. Only after identifying the precise friction point does his team design hypotheses and tests. This process prevents teams from optimizing pages based on assumptions or internal preference rather than measurable evidence.

Prioritize by ROI and Effort — Iqbal Ali’s Approach

Iqbal Ali, creator of A/B Decisions, agrees that data should drive optimization, but he emphasizes an equally important step: weighing each opportunity by its impact and effort.

Iqbal Ali, Creator of A/B Decisions

“I’d start by analyzing the whole funnel to see where the major drop-offs happen,” says Ali. “But what I test first depends on the potential ROI and ease of implementation. If there’s a clear issue with a quick fix and high payoff, that’s where I begin.

In practical terms, Ali’s approach involves funnel mapping first, prioritization second. He recommends using quantitative data, such as conversion paths, session durations, and bounce and exit rates, to pinpoint problem areas, and then layering on a prioritization framework to decide which of those problems to tackle first.

For example:

• If data shows a high drop-off between the product page and the add-to-cart stage, the team might brainstorm several possible causes, like unclear pricing, missing trust signals, and slow-loading images. Among these, a simple content or design tweak (like clarifying pricing or reordering information hierarchy) would likely rank high on ROI and low on effort.

• By contrast, a checkout redesign might also improve conversions but could require weeks of development and QA. In Ali’s view, that would fall lower on the immediate testing list.

Optimize All Ends of the Funnel — Abi Hough’s Approach

Abi Hough, a seasoned CRO consultant, cautions against treating the conversion funnel as something you move through step by step. In her experience, focusing exclusively on one end of the funnel, whether it’s traffic acquisition or checkout optimization, almost always leads to missed opportunities elsewhere.

Abi Hough, CRO Expert

“You should start at both ends,” says Hough. “It’s pointless fixing ads if checkout is broken and equally pointless fixing checkout if your ads take people to irrelevant pages.”

Hough recommends improving both ends of the funnel simultaneously rather than waiting to finish one before starting the other.

Start by splitting your focus into two tracks:

• One team (or workflow) improves acquisition by ensuring ads, offers, and landing pages clearly match what visitors expect.

• The other focuses on conversion — fixing checkout issues, improving trust signals, and reducing page load times.

Her rule of thumb is straightforward: let user research decide what to fix first. If analytics or testing reveals a bug that prevents users from completing checkout, fix it immediately. But once it’s fixed, go back to the top of the funnel and check whether your ads and landing pages are attracting the right audience in the first place.

Your Turn to Start Optimizing Conversion Funnels

There isn’t a single “right” place to begin optimizing your conversion funnel. It depends on what your data and research reveal about how visitors move through your site. The most effective CRO programs combine data analysis, prioritization, and continuous learning.

Here’s a simple process you can follow:

• Step 1: Use funnel analytics in GA4, FigPii, or Hotjar to identify where users drop off or hesitate.

• Step 2: Prioritize opportunities using frameworks like ICE (Impact, Confidence, Effort) or PIE (Potential, Importance, Ease) to determine which tests to run first.

• Step 3: Fix high-impact blockers fast, like checkout bugs, broken CTAs, confusing navigation, or unclear pricing, before moving to creative experiments.

• Step 4: Work on both ends of the funnel simultaneously: align your ad and landing page messaging while improving the checkout flow and trust elements.

• Step 5: Revisit your funnel quarterly. As campaigns, offers, and user behavior evolve, new bottlenecks will appear.

Conversion optimization is a cycle of diagnosing, testing, and refining. The more regularly you review your funnel, the easier it becomes to find quick wins and sustain long-term gains.

If you’d like a partner to help uncover your funnel’s biggest opportunities and design data-driven experiments that consistently lift conversions, Invesp’s CRO experts can help. We’ve spent over 15 years optimizing funnels for global brands, so you can skip the guesswork and focus on growth—start by getting your free conversion assessment.

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