Understanding AI and Its Capabilities in Marketing

AI in marketing unfolds in two main varieties: generative AI and analytics AI. Generative AI excels at creating content, whether it's crafting compelling ad copy, generating images, or even formulating engaging social media posts. Generative AI tools like ChatGPT, Google Gemini, and Anthropic’s Claude offer marketing teams the ability to produce innovative and original content at scale.

Analytics AI focuses on the descriptive, diagnostic, predictive, and prescriptive facets of data analysis. This aspect of AI dives deep into the data your marketing campaigns generate, providing benchmark data, insights, helps your team understand what strategies are resonating with your audience, and identifies who your most engaged segments are. It doesn’t stop there; data-analytics can also identify opportunities for strategic shifts to enhance your marketing efforts based on data-driven insights.

By harnessing both types of AI, marketing teams can not only create captivating content but also continuously refine their strategies based on a thorough understanding of performance data and audience preferences. This dual approach empowers marketers to make informed decisions, ensuring that every piece of content not only reaches the target audience but also resonates with them, driving engagement and ultimately, increasing ROI. Our team takes an Agile marketing approach that tests, measures and iterates our way to moving the graphs ‘up and to the right’.

Benefits of Leveraging AI in Marketing

Integrating AI into marketing strategies can significantly enhance the effectiveness and efficiency of your campaigns. Here are key use cases:

1. Enhanced Personalization: AI's ability to analyze vast amounts of data in real-time allows for hyper-personalized marketing efforts. Tailoring content and messaging to individual preferences leads to higher engagement rates, higher conversion rates and customer satisfaction.

2. Predictive Analytics: AI excels in predicting future consumer behaviors based on historical data. This enables marketers to anticipate needs and trends, adjusting strategies proactively to stay ahead of the curve. This is where an Agile strategy can shine.

3. Optimized Customer Journeys: By understanding each touchpoint's effectiveness, AI can map out the most effective paths to conversion, ensuring that marketing resources are allocated to the highest impact efforts.

4. Improved ROI: The efficiency and effectiveness gains from AI-driven marketing directly contribute to improved return on investment. By targeting the right audience with the right message at the right time, marketing spend is optimized for maximum impact.

5. Automated Decision-Making: AI systems can automate routine decision-making processes, freeing up human marketers to focus on creative and strategic tasks. This not only speeds up operations but also reduces the potential for human error.

By tapping into these benefits, marketing teams can not only achieve higher operational efficiency but also drive more meaningful engagement with their audience, leading to sustained business growth. And while all of that sounds amazing, are you muttering to yourself, “OK, but where do I start? What do I need to do to start getting results?” 

Strategies for Implementing AI in Marketing Efforts

To effectively leverage AI in marketing, the first step is to determine if your use case actually needs AI or if what it really needs is a spreadsheet. After that's out of the way, a well thought out strategy and tactical execution plan is essential. Here’s how marketing teams can integrate AI into their efforts:

• Audit Existing Tools and Processes: Start by assessing your current marketing tools and processes to identify opportunities for AI integration. It can be overwhelming, but the right partners can make it easy.

• Set Clear Objectives: Define what you aim to achieve with AI, whether it’s improving customer engagement, increasing sales, or enhancing content creation. Clear objectives guide your AI strategy and implementation.

• Choose the Right Tech: Based on your objectives, select AI tools that align with your goals. Whether it’s chatbots for customer service, predictive analytics for campaign optimization, or content generation tools for marketing materials, the right technology is key.

• Implement AI Gradually: Introduce AI technologies gradually to avoid overwhelming your team and systems. Start with pilot projects to test and learn from AI implementations before rolling them out at scale.

• Train Your Team: Ensure your marketing team is well-equipped to use AI tools effectively. Invest in training and development to build AI literacy and skills within your team.

• Monitor and Optimize: Continuously monitor the performance of AI-driven initiatives. Use insights gained to refine and optimize your strategy, ensuring AI implementations deliver the desired outcomes.

• Stay Informed: The field of AI is rapidly evolving. Keep abreast of the latest developments and trends in AI technology to ensure your marketing strategies remain cutting-edge.

Marketing teams can harness the power of AI to not only enhance their marketing efforts but also drive significant growth and improvements in ROI.

Best Practices for Leveraging AI in Marketing

For marketing teams aiming to become data driven and maximize the impact of AI, adhering to best practices is crucial. Here are some strategies to ensure AI integration is both effective and efficient:

• Start with a Strong Data Foundation: Quality AI outcomes depend on quality data. Ensure your data is clean, comprehensive, and structured in a way that AI tools can utilize effectively.

• Focus on Customer Privacy: Always prioritize customer privacy when implementing AI in marketing. Transparently communicate how customer data is used and safeguarded.

• Experiment and Iterate: AI thrives on experimentation. Don’t be afraid to test different AI applications and learn from their outcomes. Use these insights to iteratively refine your AI strategies. We call this ‘playing in traffic’

• Align AI with Business Goals: Ensure that your AI initiatives are directly aligned with broader business objectives. This alignment ensures that AI contributes to tangible business outcomes.

• Collaborate Across Teams: AI implementation should be a cross-functional effort, involving collaboration between marketing, IT, data science, and other relevant departments to ensure holistic success.

• Monitor Performance and Impact: Regularly review the performance of your AI tools and their impact on marketing goals. Use these reviews to adjust strategies as needed for optimal results.

• Stay Ahead of Trends: The AI landscape is constantly evolving. Stay informed about the latest AI developments and how they can be applied to marketing to keep your strategies ahead of the curve. Newsletters: TLDR, Inside and our podcast Sound BITES (shameless plug) are good places to start.

Embracing Data-Driven Marketing for Growth

Becoming more data-driven and leveraging AI in marketing offers an unparalleled opportunity to enhance ROI, drive efficiency, and foster deeper connections with customers. Teams can unlock powerful insights, automate complex processes, and deliver personalized customer experiences at scale. While challenges such as data privacy, integration complexities, and the need for ongoing education exist, the potential benefits far outweigh these hurdles. And while it might seem overwhelming, we can help. We have experience transforming product and marketing teams into data-driven machines that unlock revenue and margin growth. Laying a strong foundation now will pay dividends while your competitors try to catch up. 

Get on our calendar to talk through how your team can unlock more growth with data.

Discovery Call

https://www.nanochomp.com/discoverycall

What’s harder is figuring out where to start and how to get quick wins under the belt while wading through a sea of buzzwords and “5 steps to…  ” guides that really don’t get you any closer to getting started, leave you more confused, and somehow, on an email list that floods your inbox with subpar content three times a week. 

That said, here are 5 steps questions you should ask before starting your next data/AI project. And since all of your projects should be data driven, these are the 5 questions you should ask before you start any project.

1 - What are you trying to achieve?

It sounds obvious, I know. But, maybe because it seems so obvious that a lot of people skip this step. 

Stepping back and simply stating “What are we actually trying to do?” is a powerful first step to get the team on the same page. 

You can break that down further: “What problem do you have that you are trying to solve?” and “What is the goal and what tests should we deploy first?” These questions also align the team on what data should be collected to help validate (or de-validate) your hypothesis. 

Without knowing what you want to achieve you might succeed at getting the right answer to the wrong question. We talk about it in an episode of our podcast Sound BITES.

I overuse this phrase but here it is anyway: If you don’t know where you are going, any direction will get you there.

2 - What are you doing now?

Conduct a quick audit of what you’re currently doing and how.

You need to determine if:

• you currently have the data to analyze or if you need to go looking for it

• there is another stakeholder who you need to work with to get the right outcome

• this a greenfield project where you need to start collecting fresh data to get moving on the path 

Understanding what activity is currently taking place, what data has been and is being collected, understanding where it lives and how to get it can save you a ton of duplication of effort. 

Many times the answer to this question is: “Nothing yet” and that’s okay, too. You gotta start somewhere. 

3 - What does success look like? 

Knowing up front what a win looks like and establishing how success is being measured can make or break your project. 

For some projects, the success criteria may be as simple as “establish a baseline to measure future activity.” 

In Agile teams this strategy makes sense because you are constantly trying new things and seeing if it was successful relative to the previous test. Whatever your objective, you should align the team around minimum success criteria so everyone knows what sport we are playing and what a goal looks like. Doing so also prevents success drift; not every project will be a home run, especially as you are trying new things and learning, but retroactively moving the goal posts can destroy your credibility. 

Test, learn and iterate, but don’t lie to yourself about the outcome or else that iterate phase won’t be nearly as impactful.

4 - What are you going to do with the results?

Step 1 - collect data

Step 2 - ??? 

Step 3 - profit

What action will you take based on what the data is telling you? 

If the answer is “I don’t know” then you need to go back to the drawing board and consider if you need to collect that piece of data at all. This is probably the most overlooked item on the list. We work so hard to align the team on the objective and success criteria to start collecting data, that we somehow forget to define what action we should take.

Before you collect anything you should state: 

• If the data says X, we will try this next 

• If the data says Y, we will do this next 

This ultimately removes emotion later when you invariably get a result you didn’t expect. 

Too many times we’ve seen great projects that require a ton of resources to get off the ground, stall when the team doesn’t know what action to take based on the data and instead keeps doing the same thing while watching a dashboard that has become meaningless while they hope the direction of the chart changes at some point. 

Hope is an awful strategy and an even worse tactic.

5 - What resources and internal buy-in do you have or need?

Speaking of those resources, what resources will your project require? 

What stakeholder support do you need from inside and outside of your organization? Are you in a large organization with strict data governance and the data team buried in the IT branch of the org? It might be time to get to know that team for more than just fixing your misbehaving computer (did you turn it off and back on?)

Internal buy- in is much easier with the right relationships, and it  can make or break any initiative. Asking the right questions so you can get a sense for what’s possible is a good place to start, and helping the cross-functional teams understand what you are trying to accomplish (see #1) as well as what you are going to do with the results (see #4) generally helps with buy-in. 

Beyond internal resources you very likely have external vendors, strategy teams, data analytics as a service providers, and agencies in your solution stack to get on the same page

Bonus

We recommend you start with smaller projects that could have potential for quick success with low risk. 

Are there any quick wins we can get to demonstrate value, get momentum, get a feel for the process, and scale into stickier problems with higher risk? You might find that your project may not require any AI at all to get early value and quick wins while giving you a path to layer in some of that robot magic later.

“Quick wins” are defined as high impact, low effort projects. Identifying a few of these will buy a lot of confidence with the team and stakeholders, and should give some freedom to tackle more complicated projects later.

TLDR (too long, didn’t read)

To boil it down to a tweet: Have a clear objective, know what success looks like, understand that everything is iterative and quick wins will lead to long term success.

• What are you trying to achieve?

• What are you doing now?

• What does success look like? 

• What are you going to do with the results?

• What resources and internal buy-in do you have or need?

While some of this may seem obvious, more often than not one of these 5 questions go unanswered at the start of high-stakes data projects leading to poor results. But that won’t be you. No way. You are already 80% more likely to succeed by asking and answering just a few questions before you start your journey.

Have any best practices for your AI and data projects? Let us know we would love to hear what you think and have you on our podcast to talk through it.

Let’s kick off this blog post by getting on the same page with a few terms. We love TLAs like KPI and OKR, but if no one knows what we’re talking about we all lose:

1. TLA - A three-letter acronym for “three-letter acronym”

2. KPI - Key performance indicator. KPIs are essential to effectively managing your business and knowing what’s happening. They are the diagnostic beacons that can tell us if things are going as expected. 

3. OKR - Objectives and key results. OKRs take KPIs a bit further and force you to state your objective, followed by what key results would be indicators of success.

While teams are now trained to be data-driven and collect data, somewhere along the way we started substituting data collection for actual decision making. Instead of making decisions based on the data, teams are flying the “mission accomplished” banner for simply collecting it and taking a look once a week or so. We would argue that just stating your KPIs, and even collecting that data just isn’t enough, and in many cases not even necessary. 

“Wait, did you just say collecting data isn’t necessary?”

What I mean is, collecting the wrong data can be worse than collecting no data at all. Creating tons of digital exhaust to export as a CSV and contort into a pivot table is a waste of effort if it doesn’t get you closer to your objective or isn’t action-oriented. 

So, getting the right data is just as important as having a good objective. But before we go down the path of collecting data, cleaning it, making a beautiful dashboard and smugly smiling when we see it move up and to the right, we need to ask a fundamental question:

“What action will I take depending on what this data tells me?” 

If the answer is “Nothing” or “I’m not sure,” it might be a bad metric, or you need to step back and think through your action. It’s not as daunting as it sounds. With a good objective in place the KPIs and action plans almost write themselves.

Data Driven in 5 Steps

1) Start with an Objective

Any good initiative must be rooted in a testable plan with clear objectives.

What do you want to accomplish? Before we mindlessly jot down revenue, margin, reach and customer acquisition cost as the KPIs we’ll track, let’s think about what we’re trying to accomplish, what we want to test and what we want to optimize. 

It helps to state your core assumptions that helped you land on that path. We find that teams think they’re aligned, but when you ask a few “why’s” you realize that teammates had different assumptions and assumed everyone else had them as well. Get these on the table for better results and more successful data-driven projects.

2) Define KPIs

Great, we have an objective in place, we thoughtfully built our assumptions and we know what we want to accomplish. Now we can start defining what KPIs and metrics matter. What data will give us the best chance of proving our success criteria, validating our effort and guiding our team’s activity?

It’s worth asking yourself “Is there a better metric?”  Many times a ratio of metrics is a much better KPI to track than singular metrics. “Revenue” might be a good metric, “# of customers” might be a good metric, too, but “revenue per customer” is likely better to track if we’re trying to optimize customer lifetime value and acquisition costs.

You might also consider a hero metric. You might see this called the “One Metric That Matters” (OMTM). This is your keystone metric that drives most of your team’s activity. It’s worth noting that this will change over time depending on the problem you are trying to solve, so don’t hold on to a metric that is no longer useful for the objective at hand. As a cautionary tale, we have even seen teams inadvertently set KPIs that directly conflict with achieving their OMTM. To prevent that trainwreck, we lean into radical transparency to make sure everyone knows not only what the team is doing, but why they are doing it. 

3) What Actions Will You Take

It may sound obvious, but repeatedly we see teams tracking metrics with no plan on what action they will take. Stating your action plan before you get started can help you make actual progress. This step is the up,up,down,down,left,right,left,right,B,A,select,start of successful data projects.

State what action you will take based on what the data tells you.

Since we all love formulas, this should get you started:

• If the KPI goes above X, we will do Y

• If the KPI goes below X, we will do W

• If the KPI is flat, we will do Z

4) Collect and Analyze

It’s extremely hard to be data driven without, you know, data. So, we’ll need to determine what data to collect to help us validate our assumption. Oh, and a non-minor consideration: where we’re going to get it from. With your objective in hand and the KPIs you want to track, you’re well on your way to knowing what you need. 

Business data is often siloed, incoherent, underutilized and unoptimized, so getting your hands on it can be a little tricky. Data sources like your company’s sales data, inventory levels and cost structure are probably scattered throughout your organization, so it may take a little finesse to secure. Other data like web traffic, digital ad campaign results, customer cohort data will live in Google Analytics (GA), Facebook Ad Manager (FB), and Linkedin (LI) with various stakeholders holding the keys to the gates.

While we love nothing more than clean datasets imported into Numpy and processed with Matplotlib, Scikitlearn and Tensorflow then beautifully displayed with Plotly for data viz <insert drool emoji>, it’s OK to start with a spreadsheet and a dream. Treat this stage like a pilot/minimum viable product and trickle in the AI and automation as you go and prove value. 

We know we say “when you’re ready to trickle in AI and automation” like it’s no big thing, and that’s because it doesn’t have to be. When you’re ready to build your approachable AI strategy, we know people who can help. If something is measurable, repeatable and rule-based you should let a robot do it. Life is too short to use pivot tables all day.

5) Iterate

After you analyze your data you can see what’s working, try new things and see how they are performing vs your baseline. You should constantly test, collect new data and make tweaks based on what you learn. Making incremental improvements with each pass through the process will prevent you from suffering the slow death of “Well, it worked before so it will keep working” fallacy.

TLDR (too long, didn’t read)

KPIs without a strategy or a plan don't help; if you don't have an action plan for the data you're collecting, what's the point? And not only could it result in a lot of wasted effort, it may actually steer you in the wrong direction.

If you’re listening to the data you’ll have your finger on the pulse of what’s working, and if you have an action plan for your KPIs (and you actually execute that plan) you’ll see results that’ll help inform your next move. 

1) State your objective, 2) define your KPIs, 3) build your data-driven action plan, 4) collect and analyze the data, 5) iterate

Buzzwords - check

5-step process - check 

Contra cheat code - check

Let me know how you approach initiatives and how your teams are navigating this digital transformation. We would love to hear about it or even have you as a podcast guest. 

In the meantime, if you love AI buzzwords, check out this short Business Leaders Guide to Data and ML at the bottom of the page

We jumped at the opportunity to participate in this webinar. Not because we love webinars (listen, they’re effective and informative, but we wouldn’t call it a love affair), but because we have conversations with customers every day about how we can help them get on first base when it comes to creating a culture and infrastructure that’s ready for AI. Going from zero to AI not only takes time, but clear objectives and a sound strategy. Because like any project or initiative, jumping into the deep end only makes sense if you know what you’re doing after you jump. 

A few questions from the webinar resonated with us because they just so happen to resemble questions we hear from clients every day. Don’t feel like watching a recording? No sweat; we pulled the highlights from it, without the “Um’s” “Great question’s” and “Can you hear me’s?” we’ve grown to love over the last year and a half. 

Question 1: Have we moved past the need to sell the merits of AI? Or are you finding that it’s a given that AI provides unique insight to help humans work more efficiently and effectively?

In our experience,  AI is a word that’s used pretty frequently, and while we see people nod their heads, they don’t really understand what it means and how it can be applied to their industry. 

In marketing, for instance, the industry understands the importance of data, but many marketers don’t really know what to do with that data, who to talk to about leveraging it, and how to apply that data to make better business decisions. In fact, it’s why we started this company. We’ve worked at multi-million and billion-dollar companies with large marketing teams, campaigns and subsequently, data. But deriving meaningful insights from that was hard. It was in a black box that was only made accessible with a little bit of Google Analytics, dashboards that gave you an insight into the past with no recommendations for what to do next, and a data scientist to help translate it all for you.  

So, while people are familiar with the term AI, we’ve found that many groups don’t know how it applies to them, and if they do, how to make it work for their business. Before we sell the merits of AI, we have to educate first. 

For us, when we work with clients, it’s a three-step process: awareness, access, and action: awareness of the capabilities and benefits of AI, access to tools and resources that can take your AI product from concept to reality, and taking action on your sound AI project and executing. 

Question 2: Are companies achieving their AI goals?

We hate to answer a question with a question, but, how many companies have AI goals to begin with? 

From NewVantage Partners’ 2021 Big Data and AI executive survey, there’s still some work to be done when it comes to companies making the most of their data: 

So, while a lot of us are creating digital exhaust,  there is a serious gap in a qualified workforce with the right skillset to interpret that data to get an outcome.

We believe leadership teams might be the most gapped here from an awareness standpoint. Proactive leaders, especially in places like the Bay, Austin and Boston might be there. But right now it’s challenging to find people outside of those areas in computer science to hire.

In our world, if you want a marketer or strategist who knows how to deploy AI solutions, who knows the art of the possible, you may struggle outside of the IoT or growth hacking community to find that person . 

That’s why 90% of our job has been increasing awareness and making these concepts accessible to make teams and their workforce successful. When we work with clients and teams that have the basic skills and understanding it really helps start the project on third base. 

And, if you think it’s only the small companies who have gaps in this area, it’s not. The massive companies do, too.  We work with companies that build everything from the cars you drive, medical devices to even the software that runs most of the internet, and they’re still struggling to forget a data culture. 

 The bottom line is that being gapped in this space right now is normal and acceptable. But not doing anything to develop skills in this space isn’t acceptable in 2021. Feel like getting started by reading a “Data 101” primer for business leaders? Read our free guide.

Question 3: What does AI transformation really look like, and what you should do to get started?

First thing’s first, we should set expectations: transforming your company into a data-driven organization successfully deploying AI projects won’t happen overnight.

Think about it. A social media manager job didn’t exist in 2005. iOS app developer and Cloud architects didn’t exist, either. Now these positions are some of the highest paying jobs out there. This’ll be the case with AI. 

We don’t say this to make you feel scared or intimidated. We don’t want people who don’t have those skills to be intimidated, but empowered. That’s why, with our friends at Censia, we put together a really great plan to give you a starting point on how to develop some of that knowledge and empower you. All you need to do is sign up for the webinar and you’'ll receive a 12-month plan for enhancing your brains with AI knowledge.

Interested in getting on first base and starting your data journey? You guessed it, we can help with that.

“OK, you Buzzfeed-imitating, listicle-loving, self-important data and marketing nerds. Enough.” 

And while that argument definitely has *some* merit, hear us out. Data, machine learning, AI, Agile marketing -- these are all fun buzzwords, but what happens when you need to apply these terms? What happens when you need to go from buzzword to application? 

Not everyone has the time or money to enroll in 12-week intensives or watch every online course on the internet, which is why we assembled a list of our favorite books, podcasts, newsletters, and vibes to put some meat on the bone of those buzzwords and onto first base. We peppered in some of our favorite “just for fun” items on the list because that’s where we get inspired and enter the right headspace to come up with the next big idea. Or blog post. Same thing. Now, onto the list.

Books

Hacking Growth

What Lean Startup did to product development, Hacking Growth does for finding market fit and capturing market share. What happens when you take cross-This book walks through the process with case studies that show the results. The data isn’t debatable; it works.

The Startup Way

It’s pretty hard to walk through the halls of your office (even if you have been locked at home the last year and a half) without someone mentioning The Lean Startup. In his new book, The Startup Way, Reis takes his modern classic and explains how to apply those strategies, even in large corporations, complete with great case studies and fresh inspiration. 

The Future’s Faster Than You Think

The world changes faster than anyone realizes. In one person’s lifetime they could have seen the first flight at Kitty Hawk and the International Space Station. What happens over the next 10 years as AI, IoT, robotics, virtual reality and blockchain change what we thought was possible? The future is coming fast and we couldn’t be more excited.

Essentialism: The Disciplined Pursuit of Less

Do you accept every meeting you’re invited to, start tasks that you don’t finish, and feel overwhelmed by it all? Essentialism was a life changer for us. We guarantee this book will help you make the most of your time, all while feeling less burnt out. 

Small Giants

We all know the story of how Netflix went from a startup to a streaming giant, or how Whole Foods transformed from a crunchy granola specialty store in Austin to an Amazon-owned supermarket chain. And those are amazing stories. But what about the companies who don’t want to be the next Netflix or Whole Foods? What about the smaller businesses who love being small? Who love being connected to the community and to their employees? This book highlights some of those companies, and what they’re doing to be a successful big small guy.

Podcasts

Business Wars 

How did the Coca-Cola and Pepsi rivalry begin? What started the burger war between McDonald’s and Burger King? When did Netflix dominate Blockbuster? Part-history lesson, part-business primer, this podcast recounts business’ biggest rivalries, while indirectly bestowing insightful nuggets of business wisdom along the way. You’d be surprised how much you and your business can relate to the inner workings of a hamburger company.  

CMO Moves

This podcast interviews CMOs from some of the largest companies out there. Do you think your marketing challenges are super frustrating and unique to your dysfunctional organization? Turns out some of the biggest companies have the same challenges. Listen to see how they overcame it and how they made it to the CMO chair, and some advice for what can get you there, too. 

Heavyweight

Ever have a moment from your past that you wish you could go back and re-examine? Explain? Make amends? Jonathan Goldstein’s podcast Heavyweight does just that. The storytelling is witty, endearing and entertaining, and highlights the messy and beautiful nature of human relationships, all of which are relatable in both life and business. 

Vibes

J. Cole - The Off-Season

If you’re reading this blog you probably know that we’re pretty big fans of hip hop. So we were prett-y excited when J. Cole recently launched his sixth album, The Off Season. If you’re motivated or inspired by music, give this album a try; the beats are good and some of his lyrics might motivate you, too.

Newsletters

The Daily Stoic

Need a dose of perspective each morning? Same. We subscribe to The Daily Stoic because it often reframes current events, feelings, situations, whatever, through the lens of famous stoics Marcus Aurelius, Seneca and Epictetus. Those “big problems” you have? The stoics had them too, but approaching your problems in a new way has helped provide some calm, especially after the last year. 

What’d we miss? What should we know about? Leave us a comment so we can add these to our reading and listening lists.

Spend a few minutes scrolling on Instagram and you’ll see a strong contingent of your followers promoting their side hustle, startup or other vague entrepreneurial venture. And that’s amazing. Thirty years ago if you called yourself an “entrepreneur” you were probably characterized as a sketchy businessperson or someone who couldn’t hold down a “steady” job.

But, today? If you don’t know someone who’s starting a business, who’s an early employee in a startup or using the word “hustle” in their social feed, something’s awry. 

And that’s because over the years it’s become easier than ever to test and launch a project... so people have. The barrier to entry is lower so the uptake rate is higher and the risk is lower. Gone are the days of needing to spend $100,000 to even try to make something work. Today, a weekend, a computer and $200 will do.

The bottom line is that startups and entrepreneurship has been legitimized, and with that comes venture capital. Funding. The talent you need to make your innovation a reality. 

So how do you...get that funding? Aside from endless outreach, Linkedin messages, calling in favors and networking events, you need a solid story to tell prospective clients and investors. You need a pitch deck. But if they’re so important, why do so many pitch decks...well...suck? 

Often, it’s not the pitch deck that sucks. It’s the company’s weak value proposition that sets up that pitch deck. 

So, how do you craft a killer proposition that can have your potential investors writing checks instead of scratching heads? 

Before we ponder that question, let’s back up.

What’s a value proposition and why does it matter so much?

In short, a value proposition is:

A simple, clear statement that states why your customer should buy your product or service. The value proposition seeks to succinctly describe how your offering delivers value to your customers, and what specifically makes your product unique. 

Your value proposition should be your company’s North Star. It should be your “gut check” when you’re contemplating an initiative. It should help guide all of your company’s activity. 

How do you craft it?

While there are a few methods you can use to develop your value proposition, we prefer the simplicity of the Steve Blank formula. Blank is a former Google employee (It’s a tiny startup. Heard of it?) and he now runs the Lean Startup Circle. He created this formula after he noticed companies were highlighting product/service features in their value propositions rather than the benefit to the customer. His formula puts customer benefits front and center, and distills everything into one sentence:

Easy enough, right? 

Not so fast. Your value proposition, when articulated for public consumption, is your company’s first impression of your offering. Your value proposition forces you to succinctly describe what you do, to explain it in a way that your Grandma could understand. And it differentiates you from your competitors. It describes the reason for your company’s existence. All in a few lines. 

Phew. Sorry for making it sound so daunting, but that’s because we think it’s important for people to nail down. After all, if you can’t clearly articulate what you do, how do you expect others to understand it and buy in? And more importantly, what’s driving your business strategy without it? How do you market to your customers without it? 

But don’t worry; after both writing and reading a lot of these, we’ve found that most successful value propositions have a few similar characteristics:

Who’s doing it well? 

A company whose value proposition we love is Slack.

If you don’t know what Slack is, it’s an easy-to-use collaboration tool that allows you to work on projects together openly, communicate with team members, and integrate with existing enterprise tools seamlessly. Every feature Slack rolls out is driven by their value proposition: 

Slack makes users’ working lives simpler, more pleasant, and more productive by tearing down communication and system silos. 

And if you’ve used Slack, you know their value proposition is reflected in their platform. They make corporate collaboration and communication...fun. How many of their competitors can claim that? 

What should you avoid?

Now that we know the good, it’s important to know the other side of the coin— why some value propositions fall short. What we’ve found is that:

Now what?

You know the good and the bad; now it’s time to get writing! As we mentioned, we recommend following the Steve Blank method to start. And once you’ve drafted it, it’s time to put it through its paces:

• Test with a few people in your target audience. 

  While friends and family will give you lots of praise no matter what your value prop states, you’re looking for honest feedback. We recommend practicing your value proposition in virtual networking platforms like Lunchclub. You get to pitch your business idea to a complete stranger with little to no downside, and you have the opportunity to collect honest feedback. Do that a few times and make tweaks as needed. 

• Check your length. 

  Value propositions are not the same as mission statements. When crafting your value proposition, evaluate whether it’s short enough to boil into a tweet. The longer it gets, the more muddled your message becomes. Would a kid understand it? 

• Does it reflect your company roadmap? Does it solve a customer problem? 

  Did you write a killer value proposition...that you’re not equipped to deliver on? Writing your statement is only part of the equation. If it doesn’t reflect your company’s activity or vision for the business, you’re setting yourself up for failure by violating customer expectations and losing them as customers once that happens

And as always, we’re here to help. In fact, if you want a second set of eyes on your value prop, just shoot us an email and we’ll give you some feedback, for free!

If you talk with me for more than 15 minutes it becomes pretty obvious I have a slightly unhealthy obsession with cars and racing them. Maybe it’s from growing up in metro Detroit, maybe it’s years of engineering school, or my first few jobs in the automotive industry that really nurtured the illness. Whatever the root cause, I’ve learned more from racing than simply shuffling a car around a few turns.

If I had to synthesize it into a tweet it’d be: 

Things change. Some things are out of your control so get comfortable with it. Learn to adapt and keep trying new things. 

But if you’ll indulge me and allow me to expand on that thought a little more, it’d be these 10 things I’ve learned from racing cars that have had the greatest impact on my life off the track.

1. It’s going to rain 

This could be a post all on its own. A book, even. Both literally and figuratively, at some point it’s going to rain. Life rarely never goes according to plan. And that’s okay. Just because something isn’t directly in your control doesn’t mean you can’t do anything about it. I would spend so much time hoping things wouldn’t go wrong, fingers crossed that it all goes perfect, only to feel that rush of disappointment when it doesn’t go to plan. 

On a long enough timeline it will rain, don’t dread it. Expect it and adapt. This perspective has helped me to see opportunities in the bumps. 

“Something horrible happened!” Yeah, of course it did. And it always will, eventually. What will you do about it and how will you greet adversity when it comes to your door? 

Bad things will happen and at the worst times. But the flip side is there are hidden opportunities, and you get to choose how you accept and approach them. This is where you jump into problem-solving mode. Expect that it will rain and be dynamic in how you adapt.

2. You’ll suck at first. But try anyway

There are few things scarier than climbing in the driver’s seat, putting on a helmet, and lining up on the grid for the first time with zero track experience and a strong desire not to crash. The only person who’s more scared than you are is the instructor climbing in the passenger seat next to you. It’s intimidating. There’s so much information to take in and so much to process that early on it’s impossible to be any good.

Developing skills takes time. In the meantime, grass is still considered track, right? 

After my very first session I felt worthless, and I couldn’t comprehend how people in the same car as mine could possibly be so fast and with so little effort. It was clear; I sucked and it was completely expected. Well, my instructor expected it. My delusions of grandeur had significantly different expectations. 

So, you will suck. But not starting won’t make you better, and this applies to anything you want to learn or try. From racing cars, starting a business, to tackling a data project, even interpersonal relationships, it all takes time on task to build the skills.

There are no warp whistles to help you skip the first level. You’re going to need to: 

• Get started

• Learn to rely on help from others

• Break things into smaller manageable pieces and eat the elephant one bite at a time. (nano...chomps even. Sorry, I couldn’t help myself). 

You’ll start getting better, I promise.

3. You’re going to make mistakes. Try to make them survivable

It’s hard to know where the limits are until you’ve crossed them. And if you’re trying hard enough, at some point you’ll cross them. Anyone can do the minimum of taking no risks and slowly navigating their way through a track (or life). That might be fine for some people. 

Not me, and if you’re reading this, probably not you either. To get better, to get rewarding outcomes, you need to push the perceived limits. That means trying new things, moving past your comfort zone, taking new approaches, challenging what you thought or KNEW to be “the way.”

When you try new things it might not work and you might not be good at it, but it’s still worth testing. In fact, most of the learning and growing happens here. Make a hypothesis and take small, survivable iterations to validate it. Don’t take those YOLO risks; that’s gambling not growing. (Unless you really know what you’re doing)

Keep trying new things, keep testing your assumptions, play in traffic and make some mistakes, but make them survivable so you can try again.

4. Everything changes at the limit

The world is built for the middle section of the bell curve. We design our products, processes and services here and dismiss the rest as “edge cases.”

“These are so rare!” 

“The customer doesn’t care!” 

It isn’t obvious, but almost everything you want to instinctually do at the limit in a race car will end poorly. 

In a race car (once you’re good) you don’t live in that middle zone where normal actions, physics or back-up plans work. In fact when you’re “at the limit,” a lot of the things you expect to work not only don’t, but often yield catastrophic results.

Pop quiz:

You’re taking a freeway on-ramp and you realize you are going just a little too fast. What do you do? 

You probably said, “Duh, lift off the throttle and push the brakes.”

But at the limit, it’s probably one of the most dangerous things you can do. At the limit of grip, lifting off of the throttle will take the weight off the back of the car and shift it forward. The result: you are now seeing the rear and front of the car trade places repeatedly while you wonder what happened. 

In business, things that feel safe start to rapidly fall apart at the limits. Bad quarter results? “Let’s trim the marketing budget!” If you have a data-driven marketing team delivering high return on ad spend (ROAS) campaigns, this “safe” cost-cutting tactic is the business equivalent to lifting off the throttle mid-turn. Best case, it massively slows you down. The more likely scenario is it sends you into a spinning “code brown” that will be hard (if not impossible) to recover from. 

Limit solutions work for the middle, but middle solutions don’t work at the limit. By accounting for edge cases you will cover the middle while delivering something special that challenges conventional ‘average’ solutions.

5. Just because it worked doesn’t mean it will keep working

It’s really easy to find something that works and do it over and over again. Running the same play or taking the same line works…until it doesn’t. 

You can’t be so dogmatically committed to what worked in the past. You must be willing to adjust, take a different line, try something new and maybe find a better way. 

The book “What Got You Here Won’t Get You There” sums this up perfectly.

The world is dynamic and we need to adapt to changing conditions. Be brave enough to take a different line even if it seems scary and unfamiliar (see lessons 2 and 3). Failing to do so will eventually put you into a wall.

We’ve seen too many examples of someone using emotion and what they know works from their past life only to deploy it, with millions of dollars invested, and find out the world turned and left their antiquated strategy behind. Constantly test and iterate with a data-driven approach to see what works now, not what worked before. 

“It’s worked before. I’ll keep doing it this way” - Blockbuster, Taxis, Kodak, BlackBerry, Nokia 

Pushing out of your comfort zone to test new things will put you miles ahead of everyone doing the “safe” thing. Need some aural inspiration? May I suggest “Off That” by Jay Z? We made a playlist to help you out. 

6. Look at the data and learn what it’s telling you

Did you really think I would make a list that didn’t involve looking at the data? With the right objective and strategy in place data is immensely valuable. It tells you what’s working and what isn’t. Data analytics lets you in on the secrets hidden below the surface tucked away from our human perceptions, experiences and emotions. And it lets you use cool jargon like “Artificial Neural Networks” “Machine Learning” and “AI.” 

Collecting the right data and figuring out what it’s telling you is the best thing you can do beyond getting started. That’s true for businesses and race cars.

At the track, putting an AIM Solo2 on board will tell you everything you need to know and even give real-time feedback on what’s working or what needs a tweak.

If only it was that easy for businesses. Plugging in a single device and having it give you suggestions on what to test next would be great. And while it’s not THAT easy, it is within reach. We built our business around that very thing. Helping marketing and product teams get better outcomes by deploying Agile data-driven strategies, and AI analytics services to solve data problems.

Learning what the data is telling you will guide you to much better decisions and inspire you to test more things to see/prove what will work.

This section also lets me inject one of my favorite quotes:

“Hold on to what is useful, abandon what is useless and add what is uniquely your own.” - Bruce Lee

7. Look ahead. But not that far ahead

Keeping your eyes up and being smooth are the foundation of driving fast. Having a solid objective, strategy and appropriately planning for the future is the life and business equivalent.

Looking ahead a turn or two helps you see traffic, obstacles, trends, and gives you an idea of what’s happening so you can adapt. Looking just far enough ahead smooths your line, improves your response time and helps you make the right decisions now to give you the best result in the future. 

Not looking and planning far enough ahead makes you reactionary. You’re no longer driving your race; you’re constantly reacting to what is happening to you, but what if you look TOO far ahead? 

Five-year plans are bullshit. 

I said what I said. 

I know some people like to sit in a room, build intricate 5 or even 10-year strategies and financial models, and play the game of “Corporation” rather than actually executing. The entire time everyone in that room knows they’re lying to themselves and the stakeholders they’re presenting to. You learn so much more by doing, testing and iterating (see lessons 1-5).

Have a long term vision of where you’re going, but really focus on the three turns in front of you (or the next 18 months). Looking right off your front bumper, living one fiscal quarter at a time is also a losing strategy. 

8. It’s all about balance 

Embarrassingly, while I picked this up quickly at the track, this life example took me far too long to learn.

Life is this funny balance between family, friends, goals, work, learning, being outside of your comfort zone, risk, trying, failing, supporting and challenging others. When all of these are in some level of balance the results are really beautiful, you and the people around you can grow and you attract a lot of positivity. One imbalance and everything goes sideways.

In a race car you’re transferring weight from wheel to wheel and balancing the variables while everything around you is constantly changing. Push on the brakes - weight shifts to the front, step on the gas - weight shifts to the back, turn left - weight shifts right, turn right - weight shifts left. 

As you adapt to changing environments and needs you start to learn how to keep the right balance for the best results. 

9. There’s someone who knows more than you 

Find them, and shut up long enough to hear them. While this seems obvious enough it’s something I didn’t appreciate for the longest time. Especially the shutting up and listening part.

At track events you meet a lot of great people with a ton of knowledge, experience and expertise who are dying to share it. It’s intimidating at first to risk looking like a moron and asking for help, asking for advice, asking what has worked for someone else or even asking them to give you feedback on why something might not be working for you. 

Invariably, someone smarter than you will be willing to help you and that knowledge transfer is golden. It’s the difference between learning how to swing and getting carried to third base. The ultimate hack and shortcut to rapidly growing in any area of life is finding just one person and asking them for help and feedback.

Over the years people who were my instructors have become pretty good friends who I ask for advice on a number of topics. 

From someone who used to be too intimidated to ask for help for not wanting to look like an idiot, being forced to has opened me up to asking other people for help in other areas. I even joined Lunchclub to connect with more subject matter experts to learn how they approached challenging situations. If you haven’t signed up for Lunchclub, I highly recommend it.

One of the biggest goals I have set for myself over the last three years has been to listen more, ask better questions, and get access to the people who know more than I do.

10. Keep going 

No matter what happens, the show goes on. Through the good, the bad and the challenging, the world keeps moving. Sitting on the sidelines won’t change that fact. You won’t get better by not trying. Every time I get hung up I remind myself that someone less capable is doing the thing I want to do. 

So, keep going. 

Keep learning, executing, and trying the things that scare you.

Keep being okay being bad at something.

Keep asking for help. 

Keep helping others when you have the tools to help. 

While along the way it may get difficult, just keep going

Want to see how we apply this philosophy to data-driven marketing strategies? We built the a framework we call BITES. Jump on my calendar <here> to chat about it and see how you can apply it to your business.

But how did we get here? 

In our experience we’ve found that marketing teams tend to lose their way by having one (or more) of the following issues:

1. There’s no marketing strategy tied to business goals and outcomes. 

2. If you do have a strategy, there’s no process to execute that strategy, and no way to effectively test it before sinking your budget on a potentially bad idea.

3. The executive team and the finance departments don’t fully understand how a good marketing team, and if you’re reading this, I’m assuming yours is, is integral to the health of the business. (We wrote a blog post about how you can change that; give it a read here.)

What do these factors facilitate?

1. Every day feels like a fire drill

2. No ability to think strategically

3. No time to test and understand customer needs

4. No process. No framework.

5. Shrinking budgets. Shrinking head count. Shrinking respect.

And so, we spend our days putting out fires, answering emails, and knocking out a few table stakes activities that’ll make you feel like you’ve accomplished something. But deep down you know it’s not what you should be working on, and you know that if you just had a little more structure, a little more time, you could be more productive, more strategic, and bring in more revenue for your business. 

How do you get out of that funk?

This scenario hits home for me because I lived it. When I took the job as a marketing director for a multi-million-dollar e-commerce brand three and a half years ago, I did what any new team member does; I spent the first few weeks simply observing what the team I walked into was doing. And maybe this is a familiar experience for some, but I was both amazed and horrified. 

I quickly realized that the team was amazing. They were an extremely productive, eager and knowledgeable group; they were accomplishing A LOT of work for the team’s size (five people), but what did it mean for the business? Was their activity tracking towards business goals and objectives? And speaking of those tasks, how were they prioritized? Were they visible to the rest of the organization? I also noticed that because the team was so busy performing all of these tasks,  there wasn’t any room for testing and iteration.

In short, I had a very capable team with no strategy and no purpose. But thanks to some previous run-ins with nerds, I had a solution. 

Call it a blessing or a curse, but in my former life in a corporate marketing role I was given the opportunity to work with nearly every department in the company. Along the way I befriended a few software developers, data scientists, and product managers. Back then, my idea of project management and organization was writing my team’s to-do list on my whiteboard at my desk, gleefully erasing items from that list and starting the process all over again the next day. 

My newfound friends mocked me. The badgering began.

• Why were you working on these projects to begin with? 

• Where was the framework to your day-to-day activities? Where’s your breadcrumb trail of activity so you could review how each project progressed, and what worked and what didn’t? 

• How do you know how much time and resources to allocate to similar projects in the future? 

• How do you maintain a reasonable workload for your team so you can set expectations for those above you? 

I asked them for a better method, and that’s when Agile entered my life. 

Agile itself has become a bit of a buzzword in the business community. It’s hard to listen to a startup podcast or read an article without hearing or seeing it (should this be a drinking game?) but what exactly does it mean? There are a ton of stuffy definitions and vague explanations about what Agile is (see what we mean?), but it’s really not that complicated. At its core Agile is:

It’s easy to write off Agile as just another way to get things done, but it’s more than that. It’s a framework. A philosophy that fundamentally shifts how an organization behaves -- from how ideas are introduced to the business to how they’re brought to market. And while you do get more things done, you don’t do Agile. You are Agile. Here’s a high-level graphic outlining the differences:

There are several ways to put the Agile framework into practice. For this post, we’re focusing on Scrum. At its core, Scrum is a way to implement Agile principles. Think of it this way. Agile is a philosophy. Scrum is a process. It’ll help you organize your work in a transparent way that promotes inspection and adaptation.

So how did this apply to my new marketing team? I took an...agile approach...to implementing Agile by boiling it down to its essence and incorporating the fundamentals as quickly as I could so that my team could have some structure and prioritization ASAP. 

Here’s what I did:

Does this process seem...basic? It kinda is. And that’s what I loved about it; if your process takes hours to explain and understand, it won’t stick. After my team implemented Agile/Scrum, we were able to prioritize our daily activities, make sure they were all in the pursuit of our business goals, track the process of each task for future reference, and rapidly test ideas for just as rapid customer feedback.

How do you get started? Here are three things you can do today to turbocharge your marketing organization: 

Audit your team. 

How are they working now? What’s going well? What could be improved? How can you be more transparent? 

Start small.

Don’t try to become a scrum master in a day. You can implement elements of the Agile framework quickly to start seeing results. How? We show you in this handy dandy free guide how to make that happen. 

Fill your executives in on the secret. 

My guess is that they don’t fully understand the volume of work your team does each day, how it’s making money for your business, and how much your team accomplishes each week. One of the three pillars of Agile is transparency; once your executive teams better understand how hard you’re working to drive meaningful results for the business, the easier it is to make your case for areas of your team where you may be deficient -- people, budgets or time. 

Interested in learning more? We wrote a free guide you can download here. 

You’re hard at work on your marketing plan for the next six months based on the budget Finance so graciously allocated to you. The team has their marching orders. The vendors are working to execute your grand vision. You’ve set realistic but aggressive goals, with lots of testing and iteration cycles baked in. You’re just about to kick up your feet and wait for the revenue dollars to roll in, when you see a dreaded meeting invitation from Finance pop up on your calendar.

You accept the invite, hopeful at first. Maybe Finance found a few more coins under the sofa cushions and they want to give that surplus to YOU. Maybe they were so impressed with the last campaign that they thought you deserved a bigger budget! 

These are the lies we tell ourselves. 

Turns out, Finance is asking you, nay, telling you to cut $200,000 from your budget. The same budget that’s been slashed by 25% year over year. You had a marketing plan...PLANNED. And now the Excel-loving number crunchers from the Finance department want to swoop in and take a machete to it? 

Why does this always happen to us? 

Why marketers get a bad rap

When I first moved from my agency job to an in-house, corporate gig, I didn’t understand why marketing organizations were viewed this way. Didn’t the executive team, the finance team, anyone outside of the marketing bubble, understand how important marketing is to an organization? 

Quick answer: No. But why? 

After spending more than 10 years in the corporate world, I’ve found the problem with marketing orgs is that, to many, the discipline is seen as an art, something that has an indirect impact on a business. And if I’m being honest, their perceptions aren’t completely off. Before marketing tactics became trackable and measurable, marketing was more of a dart toss. A guess about what may work, only to find out what did (and didn’t) pan out once your company sunk a lot of time and money into the campaign.  

But, over time, many marketing organizations have evolved. While some teams still have the luxury of racking up impressions and clicks and calling it a day, the rest of us have become more data-driven and ROI-obsessed. We’re tracking the performance of our social content, our PPC campaigns, our email marketing revenue, and how that ladders up to business metrics. We’re meeting with sales teams to ensure our campaigns capture meaningful leads. We’re working with supply chain to understand our inventory levels and to make sure we’re marketing the right mix of products so we don’t stock out. 

The best marketing teams? They’re embedded in the business. 

So, why doesn’t the rest of the organization understand that marketing isn't about chasing vanity metrics? Today, marketers are data-driven, revenue generating machines who are integral to a business’ success, not a cost center. 

After scratching my head at our dwindling marketing budget quarter after quarter, it hit me. 

Marketing departments need a rebrand.*
*It’s important to note that if you’re proclaiming you’re data-driven and everything you’re doing is inextricably linked to business metrics to the powers that be, you have to actually...do that. No amount of positioning and branding is going to help you if you’re not delivering meaningful results for the business, with the stats to back it up. I mean, I’m 5’2” with no coordination so while I could call myself a professional basketball player, the facts don’t add up.

How can we change the narrative? 

We’re so good at promoting the business and delivering results, that we weren’t focused on how our teams are being portrayed. We advocate for the company all day, but we don’t advocate for our discipline? Hogwash! Relying on other parts of the business to fully understand the importance of your role is a mistake. It’s the same advice we give colleagues and direct reports; you’re your own best advocate. Expecting someone to advocate on your behalf puts the power in someone else’s hands. 

So, what can we as marketers do to change the narrative within their organization? Here are three steps you can get started on today.

1. Be more visible among interdisciplinary teams. If your marketing team is truly data-driven and embedded in the business, then you’re already working with multiple departments to ensure what you’re doing is actually helping the business. For some organizations, the finance and the executive teams may not be privy to that cross-functional activity. And that’s on you. How can you proactively present to teams who hold the purse strings? How can you help them see what other parts of the organization already see? 

2. Educate the greater organization about what you’re doing. Do people outside of marketing know what “ROAS” means? Do they understand what your KPIs are? Does finance know what “PPC” stands for? How about Google Analytics? In our experience, they don’t. When the people who make decisions about your budget don’t understand what you’re doing, it’s much easier to slash it. You can’t expect people outside of the marketing team to know how the sausage is made and why it’s important if you don’t explain it. Proving that you have the finger on the pulse of how your marketing campaigns are tied to revenue can make a huge difference when it comes to your budget.

3. How often are you pressure testing your own assumptions? This isn’t a groundbreaking statement, but when you’re running a data-driven marketing organization, consistently testing and iterating based on what you’ve learned is not only imperative to running a successful and meaningful marketing campaign, but it could help justify your marketing efforts. For example, we were recently working with a marketing team who was performing consistent holdout tests of their direct mail campaigns. When finance threatened to pull spend for a quarter, the marketing team was able to explain the potential loss of revenue by leveraging the results of their holdout tests. Finance had to look elsewhere to trim budgets. Having a consistent testing strategy not only helps you be more effective with your budget, but it can save it, too. 

Alright, cool. Do you have anything that can help me? 

Implementing Agile methodology into marketing teams can not only help make teams more data-driven and transparent to a greater organization, it can help get twice as much work done in half the time. And what finance department doesn’t like the sound of those words? We wrote a free guide that explains what Agile is and how you can quickly implement it into your own teams to see some pretty great results. Download it here. 

OK, enough of the doom, gloom and cautionary warnings; today we’re discussing how to make your data-driven projects more successful. 

Why should you care? Because when things go well, you and your team can:

• save time

• make informed decisions instead of emotional ones

• save money you didn’t know you were wasting

• find hidden correlations by connecting dots faster

• connect dots that mere mortals (humans) can’t see and didn’t even know were there

• gain a huge competitive advantage 

We think we just heard you say, “I’m sold, give me the blueprint.” Great, we’re happy to have you on the squad.

Here’s the process, nice and easy:

Objective -> Strategy-> Collect -> Analyze-> Outcome -> Iterate*

*While I admittedly tried to force that into a clever, easy-to-remember acronym (for an embarrassing amount of time) I abandoned that dream and stuck with this less acronymable (is that a word?) workflow. 

You’ll see this structure pop up over and over again in the content we develop. We are firm believers in hypothesis-based problem solving as the starting point for just about everything, from working with marketing teams on strategies to developing and deploying AI solutions for clients.

We use this workflow because it’s effective, it stops you from chasing cars, it makes your actions intentional and it forces you to map your effort to success criteria as well as overarching business goals.

1. Objective 

What do you want to accomplish?

“If you don’t know where you’re going, any road will take you there” - Cheshire Cat.

The Cheshire Cat isn’t usually thought of as a sage of business wisdom and strategy, but he absolutely nails this one. Have a clear objective so you know what road to take to get there. Start with a hypothesis and clearly state what you’re trying to achieve or accomplish. If we’re spending time and money on something, we need to know why we’re doing it. Your objective also drives what data you need to collect, where you need to collect it from and what metrics are proving (or disproving) your hypothesis.

How does this map to the higher level business goals? 

The wrong objective can have disastrous results on your overall business performance. We’ve seen customer service teams set metrics that inadvertently decrease revenue. We’ve seen marketing teams succeed at targeting customers that are more likely to take a call, but less likely to convert to an actual sale. Having the right goals with the right skin in the game is very important. 

Today, businesses are becoming more Agile, and that means your competitors too. The teams that communicate effectively and transparently set goals that all map to the larger business objectives will always outperform the siloed teams high-fiving themselves for successfully executing a project that perfectly fails to move the ball toward the high-level business goals.

What does success look like?

Now, you’ll need to define what a win looks like. Setting minimum success criteria will give you some much-needed guard rails that will tell you if your effort is tracking to your expectation of success. Drawing that line in the sand gives you a baseline to determine what is working and what needs to change, even if the only thing to change is your early expectations. 

We often like to take our initial minimum success criteria and say, “What would we need to do to 10x this result? 100x that result?” or “How would we accomplish this in half the time, or with half the resources?” Sometimes you get really creative ideas that help you accomplish more than you initially expected.

2. Strategy

At this point, you’re well positioned to build out your strategy and path to validation to prove/disprove your hypothesis.

To frame your data-driven strategy we need to turn to the data, but first we consider the following:

What data do you need to collect?

To accomplish our objective and prove if our effort is exceeding our minimum success criteria and working (or not), we need to determine what data we will actually need. A poorly thought-out set of metrics can derail an otherwise excellent plan. It’s thinking through what helpful data you need to collect for analysis.

How it will be collected

What’s your plan for collecting your data? For marketing campaigns you’ll likely have multiple data sources across several platforms, and you’ll need to know how to get your hands on them. There are metrics that may require some cross-department collaboration to be granted that access. 

Where it will be stored

Collecting and getting access to the data is one thing, but making sure you know where it will live, how it will be processed and cleaned is another. This task ends up being the real grunt work of data projects and a famous failure point for even seasoned teams. You might start off oldschool with spreadsheets, and that’s perfectly fine, but over time your data initiatives will be more sophisticated and your tools will need to grow as well. 

For example, with any data-driven marketing initiative you’ll likely be leaning on Google Analytics, Facebook Business Manager and other tools. Over time you’ll want to consolidate those separate data sources using APIs to get the most out of your effort by analyzing cross-platform data collectively. When that time comes you might be relying less on spreadsheets and more on databases in AWS or Azure. 

The important thing is to make sure you are storing the appropriate data in a place you have ready access to so you can rapidly analyze and iterate.

How it will be structured so it maps to your stated objectives

With the data sorted, you can really dig into your strategic planning and how the data will be an integral part of validating your efforts.

3. Collect

Objective: Check.
Strategy: Check. 

At this point we are well into executing our initiative and collecting all that data we planned for in the previous step. This task can be as simple as looking at dashboards or as in-depth as pooling all of the data sources into a data lake that we can perform advanced analytics on. The important thing (especially for your early projects) is to start. Many teams stay on the bench because the process feels intimidating, but don’t be that person. As you progress through your data-driven journey you can keep optimizing and get better with each cycle.

4. Analyze

Alright, this is the fun part. And if you’re doing this right it will be a continuous part of the process. 

Depending on the objective or problem you’re trying to solve you'll likely take different approaches here with different algorithm families to get your outcome. For example:

• Working on an automation problem? Sounds like reinforcement learning. 

• Doing keyword detection in audio or object detection in video? This smells like a job for a neural network. 

• Processing huge amounts of customer data and linking it back to their persona types? K-means clustering to the rescue.

Few things are more worthless than unanalyzed data. A car without a motor, a staircase to nowhere, diet water, the G in lasagna. You did all the hard work; this is where you get your reward. Plus, you get to use buzzword-rich jargon at this part of the process. Does any discipline have better buzzwords right now than the AI/ML space? Artificial Neural Networks, Support Vector Machines, Random Forests, Recurrent Neural Networks. These are the words LinkedIn flexes are made of. 

5. Outcome

Phew. You’re nearing the finish line. 

All of that hard work is paying off and your cup is now spilling over with those sweet, sweet insights. 

So, how did it turn out? Did you validate your hypothesis? Were there any surprises? Did you get a few ideas on what to test next? Did the results reinforce some of your assumptions? Are you enjoying those data visualizations from Seaborn and Plotly? 

What adjustments do you need to make to get the most from your insights and run another test?

6. Iterate

Sorry, friends. This isn’t where you get to pat yourself on the back, relax and admire how smart you are. 

This is just the start. 

Use the data to help direct you to what tweaks to make, what hypothesis to test next and go back to the top of this list. Each time through you’ll get better, your data will give you better insights, and your process will get a little cleaner. The first few passes through you will likely be doing a lot of manual testing and analysis. 

Over time you will be able to automate more and more. If something is measurable and continuous you can eventually let the robots do the lifting.

And if you feel intimidated or overwhelmed, just know that according to NewVantage Partners, 72% of companies have yet to forge a data culture and 52% of companies are not treating data as a business asset. So you’re already ahead of the pack.

And if you need help or advice making your next project data-driven, let us know. If you couldn’t tell, we love this stuff.

To build on what you’ve learned, we’ll be tackling this in small bites (nanochomps, even. Get it?) to keep you coding. In this installment we’re introducing some core concepts and a little terminology that will make you just dangerous enough to say something stupid in your next scrum stand up meeting with the dev team.

Eventually, we’ll walk you through setting up your local computer with Anaconda, Homebrew (it’s not as delicious as it sounds), PIP, IDEs, virtual Envs, CLI tools, LMNOPs (OK, maybe I made up that last one), but for now we will keep using Colaboratory because it’s easy, free, and it works. 

Alright, let’s get started!

Basic Data Types, Variables and Basic Math

Programming languages use interpreters and compilers to take what you type and magically convert that code into 1s and 0s. Those become instructions for a computer to crunch and give you a result. 

Since computers are not exactly fantastic at reading our minds (yet...Wait, is this an ad on Instagram for something I was just thinking about?) and they’re not great at guessing, we need to tell them exactly what our intention is. To help organize our code/programs/apps we learn that languages have “data types.” Data types are building blocks that tell the computer what type of thing it is working with.

We don’t want to overload you (that’s a programming joke you’ll get at some point) so today we’ll introduce just a few data types to get the ball rolling: The integer, float, and string. 

Stay with us; we’ll get you through the boring stuff and onto the fun stuff like making a bot that automatically waters your plants, but one step at a time. 
It’s time to open up a Colaboratory notebook here as well as our little cheat sheet to follow along and see how this is all coming together. Feel free to make a copy of our notebook and work right off of that if you want.

Numbers are an important part of computer science and there are few different ways to handle them. In Python we can use:

Integers (int)

You will see these identified as “int.” Integers are whole numbers such as 1, 10, 100, 6. Just plain ol’ whole numbers with no decimal points at the end. In the Colab notebook you will see that “int” is the default data type for any number you input. Don’t believe us? We’re hurt. But fine, we’ll prove it.

In your Colab notebook: 

1. Type (or copy paste we won’t judge): 

   x = 10 

   type(x)

2. Click run

3. The output should say ‘int’

Ok, we pulled a variable assignment here by setting x equal to 10, which we’ll  touch on shortly. This code creates a variable we are calling “x” and sets it equal to an int 10. The next line tells us what “data type” x is. Since x is holding the value of integer 10 we should see type return “int.” 

Now, give it a try.

Floats (float)

Floats are “floating point” numbers that are 64-bit double-precision values. “What does that mean?” you ask? It just means that a float is a number that can hold data beyond the decimal point. 

Wanna test this out? In your Colab notebook:

1. Type:

   x = 10.1

   type(x)

2. Click run

3. The output should say ‘float’

String (str)

A string is a sequence of characters, any sequence of characters as long as they are between single or double quotes. This includes words, single letters, phrases and even numbers can be stored in strings (but not for math manipulation. If you’re curious what we mean, just ask) Here are a few examples of strings:

• “Hello”

• “nanochomp”

• “Abracadabra”

• “Star Wars is overrated”

• “10 is a number”

Variables

Assigning variables you can save numbers, strings, equations, and other data types into variables. Before we jump in there are a few rules to note:

1. Keep it short but meaningful. A good variable name should be easy to understand, but not super long.

2. A variable name MUST start with a letter or and underscore. If you really wanted to start your variable names with numbers you are out of luck. _thisworks, this_works, This_Works2.

3. You can use letters, numbers and underscores. Special ch@racte$ are out of bounds.

4. No whitespace in a variable name

5. Variable names are case sensitive. pyVar1 is seen as different from PyVar1

6. Oh and one last thing. Reserved words are not usable for variable names. “for” “if” “while” and other reserved words in the language will not be usable as variable names. We will run into these as we go so don’t overthink it just yet.

For this example we will set ‘first_number’ to 10, ‘second_number’ to 5 and we will set a variable answer to be the result of ‘first_number’ + ‘second_number’. For good measure we will use the print function to print what gets saved into ‘answer’.

first_number = 10
second_number = 5
answer = x + y
print(answer)

“Fun” with Math

Now that you have the basics, let’s put it all together. 

We learned that we can assign numbers to variables, add them together, store the result in another variable and print the result.

We can also subtract, multiply, divide, work with exponents, square roots, and even a weird little operator called the modulo (spoiler alert, it’s a fancy name for taking a remainder after division).

To have fun with some of these exercises, flip over to your Colab notebook and play around with someone of the basic math operations we added for you. Change the numbers and see what happens when you add two strings together.

Next time, we’ll play with data types and introduce you to Lists, Dictionaries, Tuples and Booleans. These will add some structure with ordered and unordered lists and will be really important later. 

Then, we’ll explain what looping and control flow are. 

The goal is to build you up to the point where you can create a game. It may not be Fortnite just yet, but tic tac toe or rock, paper, scissors are well within reach here. 

Yes, yes we are. 

Let us explain. 

Our story begins on a Zoom call (don’t they all these days?) with the marketing and customer service teams of an e-commerce company we’d been working with. We were asked to help find ways to make more revenue, so one tactic we proposed was to have the customer service reps upsell customers by recommending a more expensive product than the one they were interested in. And, after asking customers a few questions about their needs, we suggested reps try to capture a greater share of their wallet by recommending complimentary products to their order. Low hanging fruit, right? A no-brainer. We’ll just be seeing ourselves out...

We were not prepared for the feedback. 

Customer Service Team: “We like these ideas, but we have to keep our call times low.” 

Us: “Why’s that?”

Customer Service Team: “Because we’re incentivized to keep our individual call times to a minimum. Our performance reviews factor in this metric, so we can’t spend more time on the phone.” 

After duct taping our heads back together, it hit us. Because the team’s customer service reps were rewarded for keeping call times low, they were missing opportunities to:

• Create a better experience for their customers by not rushing them off the phone

• Deliver more revenue for the business by cross-selling and up-selling

• Foster a loyal customer base by adding value beyond simply placing an order

By focusing on a single metric, reps were ignoring other, potentially more meaningful ones that could add value to customers and the business. 

This got us thinking…

What other metrics, when viewed in isolation, were having potentially similar, negative unintended consequences? 

Visions of marketing teams high fiving each other for getting thousands of impressions and clicks danced through our heads. But then we woke up from that dream and it turned out the company’s revenue was declining and the sales team couldn't hit their numbers. 

Flashbacks of penning braggadocios emails to the executive team recounting how successful the last paid social and pay-per-click campaigns performed came to mind. According to Google Ads and Facebook, each campaign generated $1M in revenue last month….only the company’s revenue didn’t match those monster numbers.

The spiral began. 

But, but...you did everything right! You implemented an omnichannel marketing strategy! You met your customers where they were! You emailed them. Ran paid social campaigns. Invested in targeted, programmatic display ads. Learned about Google Shopping ads. The works! Why is your ROI inflated?

That’s the beauty and the curse of omnichannel marketing. When your brand is everywhere it’s hard to draw a clear line of attribution to see what’s working (and what’s not). Social platforms want to optimize attribution so you keep boosting those Facebook posts. Google Ads wants you to keep bidding on those keywords. And even as Google Analytics has made improvements with their attribution models and you can set conversion windows narrowly, it’s still not perfect. 

It made us wonder: as marketers, are we just lying to ourselves? 

Maybe. But is there anything we can do? How do we not fall into the marketing confirmation bias that what we’re doing is working, while our business metrics don’t reflect the meteoric numbers we’re seeing in our marketing dashboards? 

Should we just ignore our marketing ROI?

No. But we don’t think you should blindly accept the data, either. The amount of data we can collect these days is amazing, but it has to be paired with context, insight and well-planned objectives or it’s useless. 

Well, where do you start?

• Your marketing metrics are awesome, but are they reflected in your business metrics? Now more than ever, marketers are asked to be more data driven and are being held accountable for the success of the business. That means you can’t bury your head in the sand and simply brag about the impressions and clicks your campaign scored. As much as you have your finger on the pulse of your marketing metrics, you need to have an even bigger obsession with the business metrics. How’s the health of the business? How do your marketing tactics ladder up to that? How can you get plugged into the health of the business consistently so you can develop marketing strategies to actually boost revenue?

• Which attribution model are you using, anyway? While attribution models deserve a blog post of their own, it’s important to note here. How are you calculating attribution? Last click (hope not)? First click (hope not)? Linear attribution? Position-based? Time-based? What makes the most sense for your business? How close can you get to an attribution model that’s a decent representation of your company’s business performance? 

• Are you A/B testing your marketing tactics? Performing holdback tests? The best way to determine what’s working when you’re in the thick of your omnichannel marketing program is to do the hard thing -- strategically “turn off” marketing initiatives to measure the impact of not running that campaign. The key here is to pull enough levers to derive meaningful insights, but to test in a way that doesn’t hurt the business long term. Plus, when you’re able to isolate and validate the efficacy of one marketing tactic, you can justify the budget for it to the folks on the executive team and make it harder for them to cut spend. 

The bottom line? Don’t look at marketing metrics in a vacuum. Data that you can pull from tools like Google Analytics can help marketers make adjustments to their omnichannel marketing strategy when a vehicle isn’t performing as expected, but don’t be like that customer service team we mentioned. Pair your marketing metrics with an obsession with your company’s business metrics and a consistent testing strategy to make sure your marketing metrics don’t let you lie to yourself. 

For the non-nerds reading this thinking, “What is a Jupyter notebook? Why do I care? Where are you going with this?” I’ll get to all of those burning questions soon, but first, a challenge. 

This challenge is for anyone who hasn’t tried to code, who has wanted to learn but was intimidated, anyone who hasn’t written a line of code in a long time: we challenge you to write seven lines of code today. Right now, even. 

We can hear the excuses already.

“Meh. That sounds complicated.” 

“I really don’t have time. Maybe later, though.” 

“You really expect me to install all that stuff on my computer? I don’t even have admin rights to this computer. How would I possibly install Python let alone try to learn to code. I have spreadsheets to get to. Bye!”

“Barstool just went live on Instagram; I’ll do it later.”

We get it, but stay with us, because with Python and Jupyter notebooks zero of those excuses are valid. With tools like Google Colabratory, you don’t have to install anything on your computer since it’s cloud-based and accessed through your browser, including the one on your phone. Writing your first lines of Python code isn’t even going to be difficult; it will be slightly easier than replying to that last email you opened and about as time consuming and complicated as sending a tweet.

Now that we’ve eviscerated those excuses of yours, let’s get started.

Clicking here will take you to your first notebook, complete with a “getting started” guide. You can read all of that beautiful prose later because the goal is to get you to write your first lines of Python right now. So, with that in mind:

1. Find the button labeled “+ code” near the top of the page. Click it! 

2. A code cell will pop up with your cursor in it, blinking at you, almost daring you to start writing your first line of code (if Goosebumps were written today one would start like this)

3. Write your first line of code. This might be intimidating and we’re giving you very little direction, but we have faith in you...and we even made a cheat sheet for you to look at (heck, copy and paste into your notebook to prove it works). Spaces and tabs matter in Python so mind those tabs in the example with the “if/else” statements

4. With that good-looking code in the cell, press the triangle play button to the left of the cell

5. The notebook will think for a second and BOOM. Like magic, it will “print” a reply on the next line

6. Want some extra credit? Of course you do. Change the numbers for ‘a’ and ‘b’ and press the run button again to see the output change.

That’s it. Congratulations, you did it. You wrote your first Python program. 

To recap, you made a simple adder and comparison tool. You learned:

1. Variable assignment

2. Math operations

3. if/else control flow

4. Printing a result

While it’s not the cutting edge machine learning and AI tool that you are going to blow the Valley’s mind with, you still overcame a barrier.  You learned that writing code was actually no big deal. 

So, don’t stop now. 

Keep learning, because the more basic computer science you know the better you’ll be at not only identifying problems and places to optimize your business, but also identifying solutions, even if you’re not the one who’s writing the code. Just wait until you start connecting the dots and realizing what you can do with Python and all of your data.
Wanna take a deeper dive into Jupyter and install it on your computer? Check here.

We recommend using Anaconda for your Python installation because it’s easy, effective, and comes with Jupyter built in. 

Don’t love Google Colabratory and want to try Jupyter’s online environment? Here you go. 

Already hooked and want to take a Python bootcamp? This online course from Jose Portilla is one of our favorites.

Did you complete the challenge? Did you do it from your phone? Feel like diving deeper? Let us know. 

Have a great holiday season, let’s gear up for a great 2021.

Earlier in this guide we briefly explained what a Wizard of Oz MVP is but we’re digging deeper because it’s important to show how your concept works without spending a lot of time and money to build the back-end functionality or physical device. Think of this as taking a job interview over Skype wearing a suit and tie up top and your pajama bottoms below.

To make this happen you’ll use a few existing services and glue them together (we told you you’d need those glue sticks) so the end result looks like a fully functioning product/service, but with a bit of manual trickery keeping it all running. 

Let’s get to the meat of our jerky concept, Primal Post. Before we hire sourcing, operations, sales, software development and marketing teams, we’ve learned there’s a more effective way to keep validating the idea, receive orders and get feedback that doesn’t involve a degree in computer science.

• Start by making a list of the functions you need so you know which tools to layer onto your existing landing page. Do you need to have a shopping cart and accept payments? Customer service and support? How about a blog and content management feature? Need to send an invoice? What is the minimum functionality you need to keep getting validation? 

• How many functions from your list can be done directly from your CMS? You’d be amazed by how much you can get done with Squarespace, Typeform/Wufoo and If This, Then That (IFTTT) stacked together. For any gaps your CMS can’t handle, Google things like “Squarespace shopping cart,” for example. Actually need a shopping cart? Check out (pun intended) Stripe, PayPal or Shopify. Zendesk can help with customer support. ZoHo can help you with your invoicing needs. Want to get replies from a survey and email them a personalized follow up? Typeform/Wufoo and MailChimp stacked together will make it easy. The best contenders for each service change constantly so do your research.

• Integrate most of these tools by embedding code snippets provided by the tool into your platform. This facilitates a seamless form inside your CMS without a developer. You may not always be able to pull off this ninja trick, but that’s OK for now. Linking to your form or content may not look as slick, but it’ll be good enough to test your concept.

• Glue it together using tools like If This, Then That (IFTTT) or Zapier. IFTTT and Zapier can help you stick two dissimilar platforms together. They use an “If <THIS> happens, do <THIS>” framework that can help you do everything from sending a notification if someone signs up for your service to triggering an invoice getting sent automatically. For example, if <someone submits an order>, do <email customer thanking them and letting them know their order was received>.

Here’s what we did for Primal Post

We made a list of the functions we needed, determined what we could accomplish with our platform, what we needed to supplement, and determined how to glue it together

• List of functionality and selecting a CMS

  We knew we needed an attractive landing page, but we were not inclined to dust off our primitive HTML skills to build it from scratch. We opted for an easy-to-use CMS (Squarespace, in this case) with a pile of templates.

  We needed a form to collect information about potential customers -- general contact information to get our fellow meatheads lined up to start placing orders. Squarespace had this function built in so we leveraged that.

• Integrations and gluing it together

  We automated the data collection process by connecting a Squarespace form to MailChimp and a Google Sheet. When a new user signs up, they receive an email thanking them for their interest and highlighting what delicious meat snack they can expect this month. We can even send polls to subscribers to crowdsource what they want us to ship before we spend any money on inventory.

  Once our meatheads opt in to receive their first box, they’ll make their purchase with a Stripe integration. You guessed it; that triggers a confirmation email, an order number and alerts us that an order has been placed. That order gets pushed to a Google Sheet so we can track who is getting this month’s meat box.

  We can be clever and enable subscriptions, single purchases and even the ability to select your favorite meats, but those functions add more complexity than we’re willing to manage manually at MVP stage. When Primal Post demand explodes, we’ll go whole hog and add features, clean up the code and operations. 

Depending on your concept this will look different, but the process is the same. The Wizard of Oz MVP allows you to quickly validate your idea. Zappos took photos of shoes at the store across the street for images on their website. When they received an order, employees would run across the street, buy the shoes and ship them to the buyer. We wouldn’t call this a seamless automated warehouse, but it proved there was demand for shoes purchased online (a crazy idea at the time) and it saved them from spending countless months building something no one wanted.

Hey! What about Hardware MVPs?

What if your opportunity has a hardware component? As recently as five years ago you’d need circuit board layout skills and know how to program PIC microcontrollers. Today there is an abundance of cheap and powerful single-board computers to choose from. These palm-sized, fully functioning computers have plenty of power, WiFi, USB ports and GPIO (general purpose input/output) that let you control just about anything. Pair one of these with a 3D printer for the external design and you can make a product prototype that looks and performs like a fully functioning product for a whopping $50! Some thoughts on building your next prototype: 

• Integration

  Select a versatile single-board computer solution with good community support to build your hardware project. If you or someone you know knows what they’re doing, integrating things together is manageable. These devices have Linux operating systems, USB ports, GPIO ports and devices like the Raspberry Pi have a Python distribution baked in. Using these to connect to external devices and trigger events isn’t exactly as easy as Pi, but it’s doable. If this is way outside your comfort level and the YouTube videos and community support isn’t helping, enlist the help of your favorite engineering friend that owes you a favor, or who would make a great co-founder. Building a business is more fun with great co-founders with complementary skill sets, anyway.

• Gluing it together

  Using tools like If This, Then That (IFTTT) or Zapier makes everything “go.” Let’s say your side hustle is Airbnb-ing your place while you’re on the road for work. You can have a Raspberry Pi send a trigger to IFTTT that someone has checked out of your Airbnb. That can trigger a notification to your cleaning resource to tidy up the property for the next guest. This can be accomplished using simple tools that already exist without having to write any code. 

Phew! You’re a Wizard of Oz MVP. Congrats! Now you’re ready to gather a few rounds of feedback and tweak your offering. But the fun’s not over; once you’re ready…it’s explainer video time, the subject of our next post

You built a simple, three-component landing page, drove at least 100 pairs of eyes to it, got email sign-ups, received generally positive feedback on your concept and tweaked your offering based on the feedback you received. Sheesh! Wipe that sweat off your brow; that’s a productive three hours. 

OK, break’s over. It’s time to take what you learned and step up your game. One hundred people is a solid number to gut check your idea and get valuable feedback, but that just won’t cut it when you’re trying to determine if your idea is worth building. If your idea has made it this far, you need to put your back into it and get your idea in front of 1,000 people for further iteration. Buckle up; this is going to take persistence, a few more elements to your landing page and a little cash (remember that thing you used before Bitcoin?)

Feedback-based optimizations

Does your landing page have a dope headline? A prominent call to action? Clear features and benefits? While that may have gotten you some initial traction and a few interested people subscribed to your email list to learn more, most people need more information before they buy in. They’ll likely have questions about your product/service, will want reassurance that someone else has had a positive experience and will want to know you’re someone who’s credible and won’t rip them off. Just like you conducted your own sniff test early on in the process, they’re conducting theirs. To lubricate the path between landing page visitor and conversion:

Develop FAQs. By now you’ve had a few questions thrown your way and patched a few flaws that these questions exposed. Rather than letting them becoming sticking points that deter people from clicking “buy/pre-order/email me,” address a few of them head on. Don’t make the list exhaustive; include your top five questions to eliminate roadblocks to someone taking action.

Establish credibility. Prove this is coming from a credible source. Tell your story. If you have a few early customers, testimonials go a long way.

Provide risk reversal and assurance. Reduce the risk of trying your product or service. No one wants to feel like they got “got,” so eliminate that risk with a “30-day money back guarantee” or a “If you’re not in love with our product, we’ll give you [insert reward]” promise. 

When engaging with your target audience:

• Don’t be lazy! Make your messages unique to each user persona. They have different care-abouts, interests and ways of thinking. Trying to create a one-size-fits-all message will fall flat with all of them.

• Use calls to action. Start a dialogue with the content you posted in your social media groups, ask people to sign up to your mailing list, even get people to sign up for pre-sales. Click that buy button! 

• Review your minimum success criteria you developed earlier. Remember, we have two goals in the MVP phase-- to drive traffic to your landing page for feedback (% positive feedback) and get a specific number of email sign ups over a set period of time and spend (CPA). When trying to drive traffic, make sure your calls to action and content align with these goals. 

Organic growth hacking:

While the term growth hacking is often thrown around by engineers, sales VPs (who in your sales org isn’t a VP?) and product managers, when we talk about growth hacking we’re referring to rapid customer acquisition. Our goal is to quickly experiment to determine the most effective and cheapest way to get your idea in front of your target audience for quick feedback. At this phase you’re combating lack of cash flow by leveraging known channels, groups and places where your target market lives, works and plays.

This list isn’t exhaustive, but we’ve provided a smattering of ideas to get your brain churning:

• Share your landing page on forums like Reddit (like you weren’t already deep in a subreddit), Hacker News,  Product Hunt and indie Hackers.

• Find local communities/meetup groups to pitch your idea. 

• Troll Facebook and Linkedin groups and add value by posting thoughtful comments/suggestions. The goal is to be seen as a reputable source. Of course, add a link to your landing page. 

• Follow hashtags and thought leaders on Instagram. Leave comments and ask for feedback on your concept.

• Search Medium and Quora for relevant posts and leave comments or ask questions to engage. Or, write a post yourself and promote that in the comments. Answer questions on Quora. Again, include a link to your landing page. 

• Join Slack groups. These could be local, (or not) but focused on your target markets. Ask for feedback on your concept.

• Send an email announcing your landing page to the contacts you collected in the market feedback section.

• Stalk key influencers on your social platforms and ask them to coffee/lunch/convos. The key is not to “sell” them. Build a relationship and add value before asking for a favor. 

• Seek out mentors. They have more experience and insight than you do. Utilize the wisdom of others when you can. 

Paid traffic

If you’ve hit a wall trying to stand out organically, you’re not alone. Take social platforms for instance. Simply posting really great content and expecting people to see it is becoming more and more difficult; organic social reach is at an all time low of 2-6%. And as you’ve probably noticed as you scroll through your personal news feed, the posts you’re served aren’t in chronological order; each platform uses an algorithm to score and rank content based with the hope of the most “engaging” content rising to the surface. 

To quickly get feedback, we recommend spending a little cash on paid social during the MVP phase, no more than 100 clams. You can increase the spend and develop more robust content once you’ve proven there’s interest in your idea. Until then, this is duct tape marketing at its finest. Some tips and best practices for getting the most bang for your buck: 

• Post content that’s social and shareable. Consider imagery that educates, entertains or creates intrigue so people will want to share it. Include a question so people will be compelled to respond. 

• Understand the ad options for the platform and optimize your content to those specifications. Since we’re still in MVP phase, choose an ad option that you can quickly and effectively execute. Are you able to create a compelling video? Do it! Is a photo more in line with your skill set? Start there.

• Experiment with your target audience. Start with a narrow target audience and see how it performs. Then, slowly add in interest categories to see what moves the needle to broaden your target audience.

• Use quality photos and videos. You wouldn’t click on a crappy photo or video as you’re scrolling through your social feed, would you? Your content should grab a user’s attention, so make the first 5 seconds of your video epic or your photo compelling. 

• Include a call to action. What do you want them to do? Including a call to action ensures your target audience knows what you’re asking of them. And do it quickly; don’t wait until the end to tell them what you want them to do. 

• Design your ads for mobile. It’s how the majority of social media users use the platform. When you make content, be sure to design with mobile viewing in mind. 

• How will you differentiate? Stand out from the competition with your content. There are free tools that have compiled thousands of social ad examples across almost every industry. Search for ads that may exist in your orbit and design your content to look and sound unique.

• Test everything. From post length, to image types, to hashtags used -- which variations are getting the most engagement?

Facebook ads step-by-step

We know, we know -- we recommended you choose the social media platform where the largest concentration of your audience is. And that’s true. The thing is, two billion people are on Facebook, so the odds are good that your audience is active on this platform. Plus, Facebook’s ad revenue in Q3 2017 was more than $10 billion, so it’s one of the biggest players in all digital advertising. With its robust targeting capabilities and huge user base, we chose the most pervasive platform with the best ROI  to walk you through the process of advertising on social media. Each platform varies in its ad offering, targeting, cost and process of buying an ad, but this should serve as a good primer. Disclaimer: social media platforms and their ad options are ever-changing. We’ll update this section frequently, but it’s hard to keep up with Zucks. 

• Determine your campaign objectives. At the time of writing this guide, Facebook offers 10 campaign objectives broken into three categories: Awareness, (brand awareness, reach), Consideration (app installs, engagement, lead gen, traffic, video views) and Conversion (conversions, product catalog sales, store visits). What do you need your ad to do? Aligning your campaign objectives with your business objectives will help determine the best ad type to reach them. At the MVP stage, we’re looking to drive traffic to your landing page. We recommend establishing your campaign to get people to head to your page to gather quick feedback. Establishing brand awareness and reach is too broad of a goal right now; consider which goal will get the largest number of people to your landing page. 

• Select your ad type. You have multiple ad types to choose from: photo, video, carousel, slideshow and canvas. Which piece of content can you create quickly without leveraging a ton of external resources? Which one has the greatest potential of achieving your campaign objectives? We recommend starting with a single photo of video at this stage of the campaign.  Now that you’ve determined what your ad needs to accomplish and the best format to reach your target audience, pop over to Facebook Ads Manager to create your campaign. Remember, you need to set up a Facebook business page first.

• Set your campaign objective. Set your objectives based on what you’ve determined above. Again, in the MVP phase we recommend a campaign for quick feedback from 100 people.

• Refine your target audience. Make sure you eliminate waste by targeting your ad to the people you want to see it. In addition to targeting by age, location, gender and language, you can further refine your target audience by demographic data, interests and behaviors. Facebook’s Audience Insights tool can tell you a lot about how your target audience interacts on Facebook. What pages do they like? How often are they on Facebook? What devices do they use? Post-MVP, you can import data from people who have already connected with you on or off Facebook with custom audience tools, or target people who are most similar to your most valuable audiences with a lookalike audience.

• Set your budget and schedule. How much money do you want to spend on your Facebook ad? Set your budget (daily or lifetime) and schedule (a stop date or continuously). Facebook lets you get very granular in how you can apply spend to your ad (optimization for ad delivery, bid amount, ad scheduling, delivery type, etc.) Make sure you’re getting the most for your $100 by keeping an eye on the meter on the right side of the page, which indicates the breadth of your audience selection. At this stage we recommend setting your campaign to one day at a $10 spend, and letting Facebook do the bidding for you. See what worked and what didn’t, and allocate the rest of your $100 to target using this feedback.

• Create ad and publish. Remember, Facebook (and all social media platforms) have specific rules for all ads. View their advertising guidelines by medium, and their advertising policies before you create your ads.

We know you’re muttering to yourself, “Now I have to make content for and manage 15 social media platforms? Will I ever eat Carne Asada tacos again?” Fear not, you overachieving entrepreneur; that’s not what we mean. First, don’t forget that we’re still in the MVP phase. It’s a waste of time to establish a presence on every social platform for a product or service that you may have to pivot or abandon. Second, you have limited time and resources. Rather than doing a mediocre job of managing six platforms, focus on the two that will net the highest return right now. Once you’ve proven product/market fit, you can increase your footprint.

Where is your target audience active? Cross reference the target audience profile you developed against the audience profile of each social platform and select the ones with the largest concentration of your audience.

Facebook

68% of US adults are active on Facebook. 81% of 18- 29 year olds and 78% of 39-49 year olds are active on the platform. Plus, they’re engaged. 44% of users check Facebook several times per day. Even if this demographic seems to skew too old for your target audience, its robust ad platform and huge user base allow you to target content to your audience.

Instagram

59% of the 800 million users on the platform are 18-29, and 60% of all users check the platform at least once a day. If your product or service is highly visual and your audience skews slightly younger, Instagram may be your platform. Plus, its use of hashtags makes interacting with influencers and people who may be interested in your product or service very easy. Like Facebook, even if you don’t deem Instagram a key social platform to start, keep Instagram in mind when building your paid strategy. If you have a Facebook business page, you can serve ads on Instagram without having a profile.

Linkedin

29% of online adults use LinkedIn, and it has one of the largest percentages of users aged 30-49. If your target audience is highly educated with high household incomes, tapping into LinkedIn users via LinkedIn groups and direct messages might make strategic sense for you.

Twitter

The majority of Twitter users are younger, urban dwelling and highly educated. While Twitter is a great platform for timely, breaking news and for engaging directly with influencers, the nature of the platform makes it challenging to ensure users see your message without some paid spend.

Pinterest

41% of all adult women online use Pinterest, with 36% of users aged 18-29 and 34% of users are 30-49. If you’re in fashion, food, home goods, art or anything that lends itself to highly visual content for women, consider Pinterest. Plus, The Pinterest Buy Button makes it easy to convert a lead to a sale.

Snapchat

78% of Snapchat users are under 24, and 49% of Snapchat users check the platform multiple times a day. If millennials comprise your target audience, get your selfie game up and make a profile.

Build your profile

Take advantage of the tools you used to develop your landing page to quickly and easily build your cover/profile photos. Tools like Canva do the heavy design lifting for you and size your imagery to the exact dimensions for each platform. Don’t forget to include your bio and link to the landing page you developed.

Source followers

Now that you’ve selected and built your platforms, you need people to like your page or follow you. This is roll-up-your-sleeves work, not “Field of Dreams,” “if you build it they will come” work.

Follow influencers in your industry. Comment on their posts, send direct messages and tag them in your posts. The key is to engage!

Search for relevant hashtags. People are self identifying what they’re interested in with hashtags. Search for hashtags relevant to your idea and follow them, send them direct messages so they engage and follow you and comment on their content.

Find popular groups and contribute to active conversations. Groups of like-minded people with similar interests are low hanging fruit for new followers.

Leverage trending topics. Is there a natural way to insert yourself into a popular conversation, movement or event? Don’t force it (it’ll look desperate), but if the topic is right, try it.

Still need followers? If you’re still having trouble building your following, sites like Fiverr can source followers for you to give you a head start. While no one wants to follow an account with no posts and no followers, use this option as a last resort.

Did your idea crush it in your initial market feedback exercise? Great, you’re ready to launch your product, rent office space and hire a few employees! Oh, wait; what that really means is you’re ready to expand the number of people exposed to your idea to 100 without spending a fortune. Enter the landing page MVP. We identified popular types of MVPs earlier in this guide but we highly recommend developing a landing page in addition to the MVP most appropriate for your concept. As we’ve mentioned no less than 30 times (sorry, not sorry), the goal of the MVP is to quickly get customer feedback and iterate based on feedback. The landing page is the easiest way to avoid wasting valuable time and money on an idea that isn’t worth it.

Why you’re doing it

The goal of the landing page is to get your idea in front of 100 people quickly and affordably. You want to get to the “Why.” What do we mean by that? Glad you asked:

• Getting quantitative metrics. Remember your minimum criteria for success metrics? They are cost per acquisition and % positive feedback. How are these numbers stacking up after 100 eyeballs? Do you have 100 views and no sign ups? Now is the time to find the flaw in your assumptions and make adjustments.

• Getting feedback beyond the numbers. Try to move beyond the numbers to a 1:1 conversation. You want real market feedback and input on your concept from as many people as possible.

What’s involved

A successful landing page has three (and only three) components:

• Headline. Keep it benefit-focused, relevant and succinct.

• Call to action (CTA). What do you want people to do? Get updates? Stay informed? Pre-order now? At this stage, you want to collect contact information so you can follow up; a prominent email entry is recommended.

• Features and benefits. A feature is what your product does; a benefit tells your customer what it means to them. This landing page should contain a simple explanation of services to entice action, and why they should care.

How to build it

There are a number of tools that make the development of a landing page a lot less daunting. Below are some resources to go from 0-100 quickly:

Instapage, Squarespace and Wix are intuitive, and easy-to-use content management systems (CMS). Instapage is perfect for setting up a page quickly to acid test, whereas Squarespace and Wix are more robust CMS tools. Pick your poison.

Canva makes it easy to develop a color palette, format photos and create font combinations for whatever piece of content you need, from a website header graphic to a social post. Their built-in templates take the guesswork out of it.

Most stock photos suck. But unless you’re a professional photographer, great imagery may not be easily accessible. It’s OK to cheat with something like Pexels. They provide higher quality stock photos that don’t look like stock photos. Other great websites include deathtothestockphoto and unsplash.

What comprises a good landing page? Slack is one of our favorites, and here’s why:

It clearly states Slack’s benefits The call to action is clear, prominent and in several locations

• The copy is succinct and doesn’t beat around the bush

• Its visuals are consistent with Slack’s advertising, social and video content, so visitors know what to expect when they arrive

• Trying Slack is free; there are few barriers to signing up

• The landing page asks for an email address. That’s it. No unnecessary questions or data collection here

• The content isn’t peppered with confusing jargon. If you’re a developer or an art director, you’re pickin’ up what Slack is puttin’ down

We applied these best practices to Primal Post’s landing page. How did we do?

Primal Post’s value proposition is above the fold The call to action is clear (and cute)

• The body copy clearly states what Primal Post does and why they should care

• The visuals on the landing page are consistent with the “thanks for signing up” email they receive after entering their information

• Primal Post offers a “meat lover’s promise” to their customers. If they aren’t happy with their jerky, they will be refunded The landing page asks for their name and email address

• The copy speaks to our jerky-loving target audience

You’ve determined who you’re up against in the marketplace and what your competitive advantage is, but what do you call yourself?

What will your logo look like? Having the words “TBD Company” (even in a really clean, modern font) in the header of your landing page isn’t a recipe for success. Now that you have a firm grasp of who your target audience is, you have the tools to determine what names, tone of voice, personality and aesthetic will resonate with them. Here’s where to start:

Make it memorable. You want your name to stand out, especially compared to your competitors. What name or phrase will linger in the minds of your potential customers?

Don’t make it too long or complicated. Don’t make your name hard to remember or pronounce. Simple and straightforward names are more likely to be remembered. Don’t get too kreative with the spelling. You want customers to easily Google your company name. Getting weird with the spelling makes that more difficult.

Make it a reflection of your brand. With your target audience identified you should have an idea of what will resonate with your customers, including your name and logo. What’s going to grab their attention?

Make sure it’s available. Before you fall in love with your name, make sure the web domain is available. We also recommend inquiring with your state’s Secretary of State (who approves business entry filings) and the U.S. Patent Office for trademarks.

Don’t be too narrow. If you make your name hyper specific to the product or service you’re offering right now, you may make it difficult for your company to evolve over time with new products or services. Don’t box yourself in!

Gather market feedback. Test your name with a few folks in your target audience to see if you get the reaction you want. Before your anxiety kicks in and you feel like you need to knock it out of the park right way, let us be clear; don’t get too hung up on your name and logo during this process. Many successful companies had other names before they took off; Nike was once Blue Ribbon Sports, Google was called BackRub and Best Buy started as Sound of Music. Like everything else in this guide, iteration (even your name and logo) is OK at this phase.

Don’t break the bank on the design right now. Unless you’re a graphic designer or someone owes you a favor, don’t spend a lot of time or money in logo development right now. With tools like Fiverr a designer can develop your logo for as little as $5. Once you’ve determined there’s product/market fit, you can invest more in logo design. Keep in mind, however, that a complicated or intricate logo is not a requirement for success. Google and Apple have simple logo designs, and they’re doing OK.