Find the answers to those questions and more in The SERP in 2026: A Data-Driven Feature Analysis from STAT.

For those in the SEO, digital marketing, and content strategy fields, this report provides a data-rich look at how search engine results pages are evolving at a structural level. Its core finding is clear: AI-driven features—particularly generative summaries—are rapidly transforming the SERP into a more dynamic, crowded, and zero-click-oriented environment, fundamentally changing how visibility is earned.

Here are eight specific findings from the report’s authors.

1. AI Overviews Are Rapidly Expanding Across Query Types

One of the most consequential shifts documented in the report is the growing prevalence of AI-generated summaries, often referred to as AI Overviews. These features are no longer limited to experimental or niche queries; they are expanding across informational, commercial, and even some navigational searches.

This broadening footprint signals a structural change in how search engines deliver answers. Instead of simply pointing users to external content, the SERP itself is increasingly becoming the destination. For marketers, this means visibility is no longer just about ranking—it’s about being included, cited, or reflected within AI-generated outputs.

2. Organic Listings Are Being Pushed Further Down the Page

As new features, especially AI Overviews, occupy prime real estate at the top of the SERP, traditional organic listings are being displaced. The report highlights how multiple layers of features (AI summaries, “People Also Ask” boxes, videos, images, and more) now frequently appear before the first standard blue link.

This stacking effect reduces above-the-fold visibility for organic results, even for high-ranking pages. In practical terms, ranking #1 no longer guarantees meaningful exposure, particularly on mobile devices where screen space is limited.

3. SERPs Are More Feature-Dense Than Ever

The report shows a continued increase in the number and variety of SERP features appearing for a single query. From knowledge panels to image packs to AI-generated content blocks, the modern SERP is a highly modular environment.

This fragmentation creates both challenges and opportunities. While competition for attention is fiercer, there are also more entry points for brands to appear—provided they optimize content for different formats, not just traditional rankings.

4. Informational Queries Are Ground Zero for Generative Search

AI Overviews are most prevalent on informational queries, where users are seeking explanations, comparisons, or summaries. These are precisely the types of queries that have historically driven top-of-funnel traffic for content marketers.

The implication is significant: generative search is targeting the very queries that once fueled organic growth strategies. Brands that rely heavily on informational content must now rethink how they structure and differentiate that content to remain visible and valuable.

5. Zero-Click Behavior Is Becoming the Norm

As AI-generated answers provide increasingly complete responses directly within the SERP, the need for users to click through to external sites diminishes. The report reinforces a broader industry trend toward zero-click search behavior.

This doesn’t eliminate the value of SEO, but it does shift its purpose. Instead of purely driving traffic, SEO is increasingly about brand visibility, authority signaling, and influencing the information presented within search itself.

6. Featured Snippets and AI Overviews Are Converging

The report suggests a conceptual overlap between traditional featured snippets and newer AI-generated summaries. Both aim to answer user questions directly, but AI Overviews go further by synthesizing information from multiple sources into a cohesive narrative.

This evolution raises the bar for content quality and structure. It’s no longer enough to provide a concise answer; content must be comprehensive, credible, and contextually rich to be incorporated into generative outputs.

7. Mobile SERPs Amplify the Impact of AI Features

While SERP complexity is increasing across devices, the impact is particularly pronounced on mobile. Limited screen space means that feature-heavy layouts—especially those topped by AI Overviews—can dominate the user experience.

For marketers, this reinforces the importance of mobile-first optimization, not just in terms of site performance but also in how content is structured for extraction, summarization, and display within SERP features.

8. Visibility Is Increasingly About Inclusion, Not Just Ranking

Perhaps the most strategic takeaway from the report is a shift in how visibility should be defined. In a generative search environment, success is not solely about where a page ranks, but whether its content is included in AI-generated answers, featured elements, or other SERP components.

This reframes SEO as a broader discipline that intersects with content strategy, brand authority, and structured data. Winning in search now requires optimizing for machines that summarize, not just algorithms that rank.

Final thoughts on the evolving SERP in the age of AI

The findings in this report make one thing clear: the search results page is no longer just a list of links—it’s an increasingly intelligent interface that synthesizes, prioritizes, and presents information directly to users. For marketers and SEO professionals, this means adapting to a world where AI Overviews and feature-rich SERPs redefine how visibility and value are created.

For those looking to better understand and respond to these shifts, The SERP in 2026: A Data-Driven Feature Analysis offers a timely, data-backed perspective on where search is headed—and what it will take to compete within it.

ChatGPT assisted with research for this post.

The post AI Overviews, Zero-Click Search, and the New SERP: Key Takeaways from STAT’s 2026 Analysis appeared first on B2B Marketing Blog | Webbiquity.

Those are the questions I set out to answer in testing FlexClip. The results were both impressive and instructive.

A Platform Designed for Exploration

One of FlexClip’s biggest strengths becomes clear almost immediately: this isn’t just a video tool, it’s an AI experimentation platform wrapped in a user-friendly interface.

From the main dashboard, FlexClip offers a wide range of starting points—AI text-to-video, image-to-video, photo editing, headshot generation, and more. Just as important, it makes it easy to jump between these tools and the full video editor.

That may sound like a small UX detail, but it matters. Many AI video tools feel like isolated experiments. FlexClip feels more like a workspace, where you can test ideas, refine them, and assemble final outputs in one place.

The Core Idea: One Prompt, Many Models

To really evaluate FlexClip, I tested a single, detailed prompt across multiple video models within the platform.

Here’s the exact prompt I used:

Cinematography: Drone camera that follows the action from above and behind Nacho.
Subject: Nacho the corgi, see the photos I uploaded. He is wearing a pale blue Minnesota United FC Loons soccer jersey.
Action: Nacho is sitting on the sideline next to the coach. You can’t see the coach’s face as the drone camera is slightly above and behind them. A player comes off the pitch and Nacho is sent running on. He receives a pass, then deftly moves the soccer ball down the field using his nose and front paws. He scores a goal and is congratulated by his teammates. The drone camera follows all of this action.
Context: The inside of the Loon’s stadium, Alliant Field, at night under the stadium lights. The stands are full of fans.
Style & Ambiance: Almost photo-realistic, a cross between actual photography and very high-end animation.
Audio: The dull murmur of the crowd in the background, which rises to a loud cheer as Nacho scores. The entire clip is animated by a voice that sounds much like legendary actor John Houseman. The narrator script is: “Nacho finally got the chance he’d always dreamed of. Taking a pass from a Loons teammate, Nacho deftly pushed the ball down the field, until…goallll!”

Yes, it’s a bit whimsical. But that’s the point: a detailed, multi-layered prompt is exactly where AI video tools should shine—or struggle.

The Results: A Tale of the Models

Here’s where things get interesting.

FlexClip gives you access to a wide range of models—Kling, Grok, Sora, Veo, and more—each with different strengths. Running the same prompt across them highlights just how uneven (and evolving) this space still is.

Kling 3.0 — A Miss

Kling struggled right out of the gate. It didn’t follow the opening scene correctly, failed to render the jersey, and completely broke the physics of the goal (Nacho somehow scored from behind the net). Audio didn’t work at all.

Google Veo 3.1 — Surprisingly Weak

Veo produced inconsistent visuals (the jersey appeared and disappeared), unrealistic physics, and even basic errors (a player using his hands in soccer). It also mislabeled the stadium as “Alliant Fied,” which is…not ideal.

Grok Imagine — Some Improvement

Grok Imagine was better, but still flawed. The visuals were strong, but details like the jersey and ball physics were inconsistent. The narration worked, but didn’t match the requested tone.

OpenAI Sora 2 Pro — The Standout

This was the clear winner in my test. The jersey was accurate, the action made sense, and the goal sequence looked believable. The main issue was audio—the narration cut off before the climactic “Goallll!”

What This Actually Tells Us

At first glance, you might think this reflects poorly on FlexClip. It doesn’t at all. In fact, it highlights one of its biggest strengths:

FlexClip makes it easy to compare models side-by-side without switching platforms.

The variability isn’t a FlexClip problem—it’s a state-of-the-models problem. And FlexClip turns that into an advantage by letting you:

• Test multiple models quickly
• Adjust prompts and rerun
• Choose the best output for your use case

In other words, it embraces the reality that AI video today is still experimental—and gives you the tools to work within that reality.

Beyond Video: A Broad Creative Toolkit

While video is the headline feature, FlexClip also includes a wide range of AI-powered image tools. These span multiple leading models and approaches, including:

• Google Imagen and Nano Banana
• OpenAI GPT Image models
• Bytedance Seedream
• Flux and Hunyuan
• Grok Imagine Image

As with video, the takeaway is similar: you’ll want to experiment. Different models produce different styles and levels of realism, and FlexClip makes it easy to test and compare.

Among the wide range of image tools FlexClip offers are a photo editor, text-to-image, background remover, old photo restoration, object remover, image upscaler, and face swap. Just for fun, I tried a few of the special effects tools with Nacho: anime-style (disappointing); 3D cartoon (goofy, but captures his personality :-)); and action figure (solid but not “wow”):

Pricing and Accessibility

The free version of FlexClip is rather limited, but the paid tiers are reasonably priced (as of March 2026):

• Plus plan: affordable entry point for individuals at $11.99 per month
• Business plan: adds higher resolution, more exports, and expanded capabilities at $19.99 per month

Pricing changes frequently, but overall, FlexClip sits in a very accessible range compared to specialized video tools.

Ease of Use: Mostly True, With a Caveat

FlexClip claims you can use it “without any learning curve.” That’s a bit optimistic. But it is:

• Reasonably intuitive
• Well-organized
• Supported by a large library of tutorials

For most marketers and creators, the bigger learning curve isn’t the interface—it’s prompting and model selection.

Final Thoughts: A Practical Platform for an Imperfect Technology

FlexClip succeeds not because it eliminates the challenges of AI video—but because it acknowledges them.

For marketers, creators, and teams looking to:

• Experiment with AI video
• Produce social and marketing content
• Explore multiple models without juggling tools

…it’s a highly practical, cost-effective platform.

For advanced video professionals looking to master a single model at a deep level, it may feel too broad and simplified.

But for everyone else—including those just getting started—FlexClip hits a compelling balance:

Powerful enough to produce real results, approachable enough to learn quickly, and flexible enough to evolve alongside the technology.

And if nothing else, it proves one thing: Even if the models don’t always get it right…Nacho the corgi is always worth another try.

The review experience was 100% human (actually, more like 95% human and 5% corgi). ChatGPT assisted with compiling the first draft of this post based on reviewer notes.

The post FlexClip Review: A Powerful AI Video Platform That Makes Experimentation a Feature, Not a Bug appeared first on B2B Marketing Blog | Webbiquity.

Find the answers to those questions and more in The 2026 social media management trends: Scaling authenticity from Sendible.

For those in the social media management, digital marketing, and agency communities—particularly teams managing multiple brands or locations—this report offers a data-backed look at how social media behavior is shifting.

Based on an analysis of more than 12 million posts scheduled through Sendible, the report suggests that the future of social strategy is less about maximizing reach across platforms and more about building authentic connections in the places where conversations actually happen.

Here are seven specific findings from the report’s authors.

Threads Is No Longer an Experiment

One of the report’s most striking findings is the explosive growth of Threads. Engagement and posting volume on the platform increased by over 300% between January and December of the past year, signaling that it is quickly evolving from curiosity to core channel.

The implication is clear: brands that have been “waiting to see what happens” may be running out of time. Threads appears particularly well suited for text-driven content such as commentary, quick insights, and conversational brand interactions. For marketers accustomed to the rapid-fire dialogue of legacy Twitter/X, Threads could become the new center of gravity for community-focused conversations.

The strategic takeaway is to treat Threads not as an experimental add-on but as a pillar for brand voice and discussion-based engagement.

LinkedIn Company Pages Are Quietly Resurgent

Industry chatter over the past few years has emphasized personal branding and employee advocacy on LinkedIn. Yet the report highlights a counterintuitive trend: LinkedIn Company Page activity is rising, not fading.

Why the reversal? According to the report’s analysis, audiences may be gravitating back toward official company pages as reliable sources of information in an era increasingly filled with AI-generated content and influencer noise. While employee advocacy still matters, the company page has become something of a “source of truth” for brand messaging.

The recommended strategy is a “hub and spoke” model. Individual employees generate reach and conversation, while the company page functions as the authoritative anchor that converts interest into trust.

The Best Day to Post Is Changing

Social media timing advice often centers on a single “best day” to post, but the data suggests the situation is evolving.

Wednesday remains the most active day for social media publishing, accounting for about 18% of scheduled posts, but Thursday is rapidly catching up.

This subtle shift has strategic implications. When everyone posts on Wednesday, competition for attention peaks. Marketers willing to experiment with Tuesday or Thursday may find themselves competing in slightly quieter feeds.

For brands launching major announcements or thought leadership content, shifting to a less crowded publishing window may improve visibility without increasing budget or production effort.

Authentic Engagement Still Comes from Handcrafted Content

Automation and AI have transformed many aspects of social media publishing, but the report’s data suggests that human-crafted content remains the dominant force.

According to Sendible’s analysis, 94.9% of posts are created individually in the compose box, while only 5.1% are published through bulk imports or automated scheduling tools.

That doesn’t mean automation is losing relevance. Instead, the emerging model is hybrid: bulk scheduling for evergreen content and routine updates, combined with real-time publishing for conversations, announcements, and reactive posts.

In other words, automation sets the foundation—but authenticity still drives engagement.

Facebook Is Still the Most Used Platform

Despite years of predictions about its decline, Facebook remains the most widely used platform among social media managers in the dataset.

The report found that 44.6% of scheduled posts were sent to Facebook Pages, making it the single largest channel by a significant margin.

For local businesses and multi-location brands in particular, Facebook continues to play a central role in community engagement. While newer platforms often dominate marketing headlines, the data suggests Facebook still provides reliable reach and interaction at scale.

The lesson: don’t abandon the platform simply because it no longer feels new.

Carousel Posts Are the Surprise Breakout Format

One of the most interesting content-format findings involves the rapid rise of carousel posts.

Carousel usage grew by more than 24% year over year, jumping from a tiny fraction of posts to nearly a quarter of all scheduled content.

Carousels are particularly effective for educational storytelling and B2B thought leadership. They encourage users to swipe through multiple frames, increasing dwell time and engagement. In fact, the report notes that carousel posts can generate around 12% higher engagement than video on average.

For marketers producing tutorials, explainers, or step-by-step insights, carousels may now represent one of the most efficient content formats available.

Video Is Becoming More Strategic

Just a few years ago, the prevailing advice was simple: produce as much video as possible. But the data suggests that mindset is shifting.

Video posting volume fell sharply—by more than 34% year over year—as brands moved away from producing “filler” video content.

Instead of treating video as a default content format, marketers are now reserving it for high-impact storytelling moments. This suggests the industry may be moving toward a more balanced mix of formats rather than chasing video production quotas.

In practice, that means brands should focus on quality and message clarity rather than volume when planning video content.

Social Media Has Clear Seasonal Peaks

The report also highlights how social media publishing fluctuates throughout the year.

The busiest month for social activity in the dataset was October, accounting for roughly 8.9% of all scheduled posts, as brands ramp up campaigns ahead of the holiday season.

By contrast, February tends to be one of the quietest months. This drop-off presents an opportunity for brands willing to launch new campaigns early in the year, when competition for attention is lower.

Timing, in other words, can be as important as channel or format.

Final Thoughts on the Future of Social Media Authenticity

The central theme of The 2026 social media management trends: Scaling authenticity is that the next phase of social media strategy will be defined less by platform proliferation and more by meaningful connection.

For social media managers, agencies, and digital marketers, the report suggests that success will come from combining efficient publishing workflows with genuinely human content. Brands that balance automation with authenticity—using data to guide platform choice, content format, and timing—will be best positioned to stand out in increasingly crowded feeds.

And perhaps the most important takeaway is this: even as tools and platforms evolve, the brands that succeed will be the ones that remember social media is still, fundamentally, about conversation.

ChatGPT assisted with research for this post.

The post Social Media Management Trends: Threads, Carousels, and the “Authenticity Gap” (Research) appeared first on B2B Marketing Blog | Webbiquity.

Retailers that analyze customer behavior and adjust store strategies can transform overlooked sections into productive parts of the shopping environment. Data-driven decisions, thoughtful merchandising, and strategic visual cues all play a role in improving movement across the retail floor.

Identifying Where Traffic Declines

The first step in improving low-traffic areas involves determining exactly where the problem occurs. Many retailers rely on foot traffic analytics, point of sale data, and in-store sensors to monitor customer movement. Heat mapping tools often provide a visual representation of which areas customers visit frequently and which sections they avoid.

Patterns revealed through these analytics may show that certain aisles receive little attention due to their location, product placement, or lack of visual cues. For example, spaces located far from entrances or popular product categories often experience lower engagement.

Data may also reveal time-based patterns, such as sections that remain quiet during peak hours but attract visitors during slower shopping periods.

Improving Store Layout and Product Flow

Layout adjustments can significantly influence how customers move through a store. Retail studies frequently show that shoppers follow natural walking paths once they enter the space. Placing attractive displays along these pathways encourages exploration of additional sections.

Repositioning complementary products can also improve engagement in underused areas. Items that relate to high-demand categories may guide customers into nearby zones that previously received limited attention. For example, placing accessories near popular clothing displays can extend browsing time while exposing shoppers to additional merchandise.

Clear sight lines across the store help customers recognize that other sections exist beyond the primary aisles. Removing visual barriers or adjusting shelving height can make distant displays more noticeable.

Using Visual Signals to Draw Attention

Visual communication plays an important role in guiding customer attention. Lighting, color contrast, and digital displays can all influence where shoppers choose to walk.

Retailers often use digital signage to highlight promotions or seasonal offers in quieter parts of the store. Screens positioned at strategic points create visual interest that encourages customers to explore further. Collaboration with a reliable LED sign manufacturer can help retailers install displays that remain visible under different lighting conditions and store layouts.

Promotional messaging should remain concise and relevant to the surrounding merchandise. Messages that align with nearby products often generate stronger engagement than generic advertising content.

Creating Experiences That Encourage Exploration

Interactive elements can also help activate overlooked retail zones. Demonstration areas, product sampling stations, and small event spaces give customers a reason to move beyond the main shopping aisles.

Retailers sometimes rotate promotional displays throughout the store to maintain curiosity. A rotating schedule prevents certain areas from becoming permanently overlooked. Data gathered from these experiments can reveal which types of displays generate the highest levels of customer engagement.

Customer feedback provides another useful source of insight. Surveys and digital reviews often reveal which aspects of the shopping experience feel confusing or difficult to locate.

Low traffic areas in retail spaces often reflect gaps in layout design, product placement, or visual communication rather than a lack of customer interest. Careful analysis of movement data combined with targeted merchandising strategies can transform quiet sections into productive parts of the store.

Retailers that continuously evaluate these patterns create environments where customers explore more of the store and discover products they might otherwise miss. Look over the infographic below to learn more.

The post Turning Quiet Corners Into Sales Drivers: Reviving Low Traffic Retail Zones appeared first on B2B Marketing Blog | Webbiquity.

Find the answers to those questions and more in 20+ AI Prompts from Top Marketing Pros from Brand24.

For those in the B2B marketing, content marketing, and digital strategy communities, this report provides a practical look at how experienced marketers are actually using generative AI in their daily workflows. Rather than focusing on abstract AI theory, the report offers specific prompts and use cases that help marketers brainstorm ideas, analyze audiences, develop content, and extract insights from data.

Here are six ways to use AI in marketing plus two additional key findings from the report’s authors, based on input from marketing experts like Andy Crestodina, Gini Dietrich, Neal Schaffer, and Jim Harris.

1. Using AI prompts to accelerate research

One of the most practical uses of AI highlighted in the report is research. Marketers often spend hours gathering information about competitors, audiences, or industry trends before launching campaigns. The report shows how using structured prompts with conversational AI chatbots can dramatically speed up that process.

For example, one prompt asks AI to act as a market analyst and summarize the most important trends in a specific industry segment. Another encourages the AI to identify emerging topics that competitors may not yet be covering. By clearly defining the role the AI should play and the type of output required, marketers can generate research summaries that would otherwise take hours to compile manually.

2. Turning AI into a brainstorming partner

Creative ideation is another area where AI prompts can provide significant value. The report includes several prompts designed to help marketers generate fresh campaign concepts, blog topics, and social media angles.

One example prompt asks the AI to produce ten unconventional marketing ideas for a specific product, emphasizing originality rather than conventional tactics. Another prompt instructs the AI to analyze a target audience and propose messaging angles that would resonate with different customer segments. These types of prompts transform AI from a simple writing assistant into a brainstorming collaborator that can help break through creative blocks.

3. Using prompts to refine messaging

Many of the prompts in the report focus on improving marketing copy. Instead of asking AI to simply “write a headline,” the examples encourage more detailed instructions.

For instance, one prompt asks the AI to rewrite a piece of marketing copy in three different tones: authoritative, conversational, and provocative. Another prompt requests several variations of a value proposition tailored to different buyer personas. This approach helps marketers quickly test alternative messaging strategies before deciding which version best aligns with their brand voice and campaign objectives.

4. Improving content outlines and structure

Content creation is one of the most common marketing applications for generative AI, and the report includes several prompts designed to improve content planning.

One example asks AI to generate a detailed outline for a blog post that answers common customer questions about a particular product category. Another prompt encourages the AI to structure an article so that it addresses both beginner and advanced readers. These prompts help marketers move quickly from a blank page to a structured framework that can then be refined by human writers.

5. Extracting insights from customer conversations

The report also demonstrates how AI prompts can help marketers analyze qualitative feedback from customers.

One prompt instructs AI to review customer reviews or social media comments and identify recurring themes, frustrations, and feature requests. Another asks the AI to summarize sentiment patterns from online discussions about a brand. These prompts illustrate how generative AI can function as a lightweight analysis tool, helping marketers surface insights from large volumes of text.

6. Using AI to simulate audience perspectives

Another interesting set of prompts involves asking AI to role-play different customer personas. By instructing the AI to respond as a specific type of buyer, marketers can explore how different audiences might react to a product message or marketing campaign.

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For example, one prompt asks the AI to evaluate a marketing message from the perspective of a skeptical buyer. Another asks it to identify potential objections a prospect might raise during the decision-making process. While these simulations are not a substitute for real customer research, they can provide useful starting points for refining messaging and anticipating concerns.

Prompt structure matters more than prompt length

A key takeaway from the report is that effective prompts are rarely one-sentence instructions. The most useful prompts provide context, define a role for the AI, and specify the format of the response.

For example, instead of simply asking “What are some marketing ideas?” a more effective prompt might say: “Act as a senior B2B marketing strategist and propose five campaign ideas for a cybersecurity SaaS company targeting mid-market IT leaders. For each idea, explain the audience insight behind it and the expected marketing impact.”

This structured approach tends to produce much more relevant and actionable output.

AI prompts still require human judgment

While the report highlights many useful applications for AI prompts, it also implicitly reinforces an important point: prompts are tools, not substitutes for expertise.

The best prompts still depend on the marketer’s ability to define goals, interpret outputs, and refine the results. AI can accelerate idea generation and analysis, but the responsibility for evaluating those ideas still belongs to the human marketer. In practice, the most effective workflows combine AI speed with human judgment.

Final thoughts on AI prompts for marketing

As generative AI becomes more widely integrated into marketing workflows, the challenge for many professionals is figuring out how to use these tools effectively. The examples in 20+ AI Prompts from Top Marketing Pros from Brand24 show that the key is not simply asking AI to produce content. Instead, the most valuable prompts guide the AI toward specific tasks such as research, ideation, analysis, and messaging refinement.

For marketers who want to move beyond experimentation and start using AI more strategically, this report offers a helpful set of starting points. By studying and adapting the prompts shared by experienced practitioners, marketing teams can begin to integrate AI into their everyday work in ways that save time, spark creativity, and improve decision-making.

ChatGPT assisted with research for this post.

The post How Top Marketers Are Using AI Prompts to Work Faster and Smarter (Research) appeared first on B2B Marketing Blog | Webbiquity.

Find the answers to those questions and more in Navigating Growth in 2026: Business & Digital Marketing Insights from 1,000 Companies from OuterBox.

For B2B executives and marketing leaders, the report offers something more useful than optimism. It provides a snapshot of how companies are actually responding to sustained economic pressure and evolving buyer behavior. The numbers suggest that growth in 2026 is possible, but won’t happen by accident. It will come from disciplined execution, operational alignment, and a more deliberate approach to digital strategy.

Here are seven key findings from the report and what they reveal about the year ahead.

1. The Performance Gap Is Widening

In 2025, 69 percent of respondents reported meeting or exceeding expectations. Thirteen percent said they far exceeded them. At first glance, that sounds like steady progress.

But last year’s survey told a different story. In 2024, only 54 percent met or exceeded expectations, while 46 percent fell short. The shift is not just upward, it’s uneven.

The market has become more polarized. Some organizations are navigating volatility effectively, while others are not keeping pace. That divergence suggests that external conditions alone do not determine outcomes. Strategic posture and internal discipline increasingly matter more than macro trends.

2. Economic Pressure Is Still Present, Just Less Dramatic

Among companies that underperformed in 2025, 39 percent cited economic conditions as the primary contributor. Inflation, tariffs, and pricing pressure continue to weigh on performance.

A year ago, that number was 86 percent. The drop does not necessarily mean the environment improved dramatically. Instead, it suggests that economic pressure has shifted from shock to structure. Businesses are no longer reacting to sudden disruption, but rather managing sustained uncertainty.

When volatility becomes routine, leaders have fewer excuses to defer strategic adjustments. Execution quality becomes more visible.

3. Growth Leaders Are Strengthening Their Foundations

Among companies that met or exceeded expectations, increased customer demand was cited most often at 45 percent. But internal improvements were nearly as prominent. Operational improvements and sales and marketing strategy were each selected by 39 percent of respondents. Strategic partnerships followed at 30 percent.

That balance reveals that although sales and marketing remain essential, they are no longer described as the single dominant growth driver. Instead, they operate alongside operational efficiency and structural improvements.

In practical terms, that means marketing is being evaluated in the context of what the organization can realistically support. Generating demand without scalable systems introduces friction; in longer B2B buying cycles, that friction compounds.

4. Buyer Behavior Is Reshaping Marketing Priorities

Respondents report longer decision timelines, greater price sensitivity, and more extensive research before sales engagement. Buyers are not retreating from purchases, but they are scrutinizing them more carefully.

That shift changes the role of digital marketing.

When buyers conduct deeper research before engaging sales, digital channels become validation mechanisms. Messaging clarity, proof points, and user experience carry more weight. It’s not surprising that 31 percent of respondents rank expanding presence across key digital channels as a top priority, while 28 percent prioritize improving customer experience.

The emphasis is moving away from exposure for its own sake. Visibility must align with buyer intent and credibility must be established earlier in the journey.

5. Operational Efficiency Now Leads the Agenda

When asked about operational priorities for 2026, 38 percent selected improving operational efficiency. Scaling marketing and sales efforts followed at 30 percent.

Last year, scaling ranked first. The reversal suggests that leaders are filtering growth initiatives through a sustainability lens. The question is no longer simply how to expand, but rather how to expand without eroding margins or straining internal capacity.

Marketing budgets are being judged less by reach and more by predictability. Efficiency is no longer a back-office concern; it’s become central to growth planning.

6. AI Preparedness Remains Limited

AI has clearly entered the strategic conversation, but most organizations are still early in the process.

Thirty-five percent describe themselves as minimally prepared. Forty-three percent say they are moderately prepared. Sixteen percent have no AI plans in place. Only 6 percent consider their organization well or highly prepared.

The data reflects awareness and experimentation, but not widespread integration. Many companies are exploring use cases and testing applications, yet relatively few have embedded AI into a cohesive, cross-functional strategy.

From now until March 31, 2026, enter code VEEDSPRING20 to get 20% off your first year on the Pro plan! (new customer / annual plans only)

At the same time, buyers are increasingly influenced by AI-driven search and LLM-based discovery tools. If discovery mechanisms are evolving faster than marketing infrastructure, visibility gaps can emerge quietly.

The implication is not that companies should rush into aggressive AI adoption. Rather, they should move deliberately, define measurable use cases, and ensure alignment between experimentation and business objectives.

7. From Traffic Growth to Demand Capture

One of the clearest shifts in the survey involves digital priorities. In the previous year, 50 percent of respondents identified increasing traffic as their primary focus. In 2026, expanding presence across key digital channels leads at 31 percent, followed closely by improving UX at 28 percent.

Increasing digital media ROI and enhancing analytics each register at 11 percent.

The shift reflects how AI-influenced discovery and longer buying cycles are changing what “growth” means in digital marketing. Raw traffic is less valuable if it does not align with intent. Demand generation remains important, but demand capture and conversion quality are increasingly decisive.

SEO, analytics, user experience, and attribution now function as a connected system. Marketing performance is being measured not just by visits, but by clarity, credibility, and conversion efficiency.

Final Thoughts on Growth in 2026

What Navigating Growth in 2026: Business & Digital Marketing Insights from 1,000 Companies ultimately illustrates is not blind optimism. Seventy-eight percent of respondents describe their outlook as cautiously optimistic or planning for growth, but that optimism is measured.

Leaders are prioritizing efficiency at 38 percent, recalibrating digital strategy toward intent-driven visibility, and acknowledging that only 6 percent feel fully prepared for AI.

Growth in 2026 appears achievable. But it will favor organizations that align marketing with operations, strategy with readiness, and experimentation with measurable outcomes. In an environment where volatility is normalized, alignment rather than enthusiasm will determine who pulls ahead.

ChatGPT assisted with research for this post.

The post Growth in 2026 Will Depend Less on Optimism and More on Alignment appeared first on B2B Marketing Blog | Webbiquity.

Find the answers to those questions and more in the Be Category-Famous and Accelerate Social Trust report from LinkedIn.

For senior B2B marketers and marketing decision-makers, this report makes a clear and compelling case: trust is not a soft metric or a branding afterthought. It is the strategic foundation of sustainable growth, and it is built less through broad fame and more through category-specific validation, peer credibility, and social proof across the funnel.

Here are eight specific findings from the LinkedIn report’s authors, Mimi Turner and Jann Schwarz.

1. Trust Is the Most Important Factor in B2B Brand Success

When asked directly whether building trust is the most important factor for achieving success as a B2B brand, 93.7% of marketers agreed or strongly agreed (page 6). Only 1% disagreed outright. That level of consensus is rare in marketing research. It signals that trust is no longer viewed as a halo effect or secondary outcome; it is seen as the core strategic lever behind influence, growth, and competitive advantage.

The implication is clear: if trust is foundational, then the tactics used to build it must be treated as primary investments, not optional branding task items.

2. Customer and Peer Recommendations Outweigh Price and Features

In a progressive rating exercise (page 8), marketers consistently ranked customer recommendations and peer endorsements as more influential than price competitiveness, advanced features, or being a household name. In fact, customer recommendations were 1.25x more influential than price competitiveness, and peer recommendations were 1.27x more important than being a household name.

This challenges a common internal narrative. Many organizations still default to feature launches, pricing strategies, and innovation messaging as primary growth drivers. The data suggests marketers themselves believe relational proof matters more.

3. When Forced to Rank, Proof Beats Popularity

When marketers were required to strictly rank factors influencing trust (page 9), the findings sharpened. Being recommended by customers was ranked first by 35.8% of marketers, and peer recommendations by 15.9%. Combined, those signals of category relevance far outweighed fame or price competitiveness.

Image credit: LinkedIn

Notably, “category famous” scored just 10.1% when ranked explicitly. Yet marketers implicitly chose category relevance through their prioritization of peer and customer validation. This gap between what marketers say explicitly and what they prioritize implicitly is one of the more interesting tensions in the report.

It suggests an opportunity: reframing “category fame” not as vanity awareness, but as earned relevance within a specific buying ecosystem.

4. Recognition Is More Defensible Than Price

In forced-choice comparisons (page 11), marketers overwhelmingly favored brand recognition over cost leadership. 80.7% selected “a brand that is widely recognized across the industry” over “the most cost-effective brand.”

The report notes that brand reputation was seen as more than four times as defensible as price competitiveness. This is a critical insight for B2B firms tempted to compete on margin-eroding discount strategies. Recognition, especially within the category, creates insulation against commoditization.

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5. Peer Credibility Beats High Awareness

When asked to choose between high brand awareness and peer recommendation (page 11), 62.3% of marketers chose peer credibility. In other words, general fame is less powerful than endorsement from respected insiders.

This reinforces the report’s core thesis: trust is socially constructed. It spreads through validation networks, not just impressions and reach. For B2B marketers, this elevates advocacy programs, community building, and co-marketing with customers from tactical add-ons to strategic imperatives.

6. Endorsements Outperform Innovation Alone

In another forced-choice comparison (page 11), 68.7% of marketers preferred a brand with strong customer endorsements over one known for cutting-edge innovation but lacking proof.

This doesn’t mean innovation is unimportant, of course. But innovation without validation is flimsy. In high-stakes B2B buying environments, especially with large buying groups and risk-averse stakeholders, emotional safety and demonstrable results outweigh theoretical superiority.

7. Trust Requires Visibility and Social Proof

The report also examines barriers to building trust (page 14). Interestingly, there is no single dominant obstacle. Instead, several related factors cluster together: lack of product differentiation (30%), lack of awareness (28%), insufficient case studies or proof (27%), and absence of customer advocacy (24%).

The takeaway is striking. Marketers believe that invisibility and lack of endorsement are liabilities. Trust cannot exist “in secret.” Without category awareness and visible validation, even strong offerings struggle to build confidence.

This finding adds nuance to the awareness-versus-trust debate. Awareness alone is insufficient, but the absence of awareness undermines trust.

8. Trust Is a Full-Funnel Activity

One of the report’s strongest sections examines how trust manifests across the funnel (page 16).

At the top of the funnel, being known as a trusted and reliable brand within the category was more than twice as important as being a household name. Being known and trusted was 1.25x more important than being memorable or recognized as innovative.

In the middle of the funnel, third-party validation dominates. Being named the top solution by analysts received the largest share (37.9%), and video testimonials were 20% more effective than written versions. Expert and customer endorsements significantly outperformed company-produced content.

At the bottom of the funnel, the most surprising insight emerges. While functional levers like free trials and personalized solutions matter, what marketers most want is a more intelligent lead-scoring system. They prefer better qualification over higher volume. In fact, marketers believe a smarter scoring system that surfaces higher-value leads would close more deals, even if overall lead counts decline.

This finding shifts the focus from “more leads” to “better signals.” Trust at BOFU is not just relational, it’s operational.

Light Critical Analysis: What’s Missing?

The report makes a persuasive, data-backed case for prioritizing social validation and category fame. However, two questions remain.

First, while marketers overwhelmingly prioritize trust, the study is based on self-reported perceptions. What marketers believe drives growth may not always align perfectly with what financial performance data would show. It would be valuable to see trust metrics correlated directly with revenue or pipeline performance.

Second, the report champions peer and customer endorsements, but it does not deeply explore how organizations can systematically scale advocacy. Advocacy is easier to endorse conceptually than to operationalize at scale. More practical frameworks for turning customers into active advocates would strengthen the prescriptive power of the findings.

That said, the directional clarity of the research is hard to ignore.

Final Thoughts on Category Fame and Social Trust

For senior B2B marketers, the message is both validating and challenging. Validating because it confirms what many intuitively know: trust is the foundation of sustainable brand success. Challenging because it demands a shift away from feature-first messaging, price competition, and broad awareness toward a disciplined strategy of category relevance, social proof, and intelligent lead qualification.

In the Be Category-Famous and Accelerate Social Trust report, LinkedIn’s head and senior director of marketplace innovation, Mimi Turner and Jann Schwarz, argue that B2B growth comes not from being famous everywhere but from being trusted where it matters most. For organizations willing to treat advocacy, validation, and smarter signals as strategic assets, the report provides a compelling roadmap for earning that trust across the funnel.

ChatGPT assisted with research for this post.

The post Why “Category Fame” Beats Household Fame in B2B Marketing appeared first on B2B Marketing Blog | Webbiquity.

Artificial intelligence (AI) has moved from experimental pilots to core budget priorities across multiple industries. Executive teams are allocating significant capital to systems that improve speed, accuracy, and decision-making. For B2B marketers, tracking where these investments are flowing offers valuable insight into future demand and messaging strategy.

Manufacturing and Industrial Operations

Manufacturers are directing major funding into predictive maintenance, quality inspection, and production optimization. Machine learning models analyze equipment data to identify early signs of wear or performance drift. Reducing unplanned downtime has a direct impact on margins, which makes this category attractive to operations leaders.

Computer vision systems are also gaining traction on factory floors. Automated inspection tools can flag defects faster than manual checks, reducing waste and improving throughput. As industrial firms digitize supply chains, AI platforms that connect procurement, logistics, and production data are receiving sustained investment.

Financial Services and Risk Management

Banks, insurers, and asset managers continue to expand AI capabilities in fraud detection, credit modeling, and compliance monitoring. Real-time transaction analysis helps institutions identify anomalies and respond quickly to potential threats. These systems reduce losses while strengthening regulatory adherence.

Customer analytics is another priority area. Financial institutions are using generative AI to synthesize large volumes of customer data, summarize insights, and support advisory teams. Risk modeling, portfolio optimization, and claims processing are increasingly driven by advanced algorithms rather than manual review.

Healthcare and Life Sciences

Healthcare providers and pharmaceutical companies are channeling resources into AI-assisted diagnostics, clinical workflow optimization, and drug discovery. Imaging analysis tools can detect patterns in scans that might be missed during manual review. Predictive models also support patient flow management, reducing wait times and improving resource allocation.

Biotechnology firms are applying machine learning to accelerate compound screening and identify promising treatment candidates. Research timelines that once spanned years can now be shortened through advanced data modeling. Investment in AI infrastructure is becoming part of a long-term research strategy.

Retail and Consumer Intelligence

Retailers are investing in AI to forecast demand, manage inventory, and personalize customer experiences. Predictive analytics helps companies adjust purchasing and pricing strategies based on shifting patterns. Supply chain resilience has become a board-level issue, and AI marketing platforms that provide end-to-end visibility are receiving increased funding.

Marketing automation tools powered by advanced analytics allow retailers to segment audiences more precisely. Campaign performance data feeds back into algorithms, improving targeting efficiency over time.

Cybersecurity and Data Governance

As digital transformation expands, cybersecurity has become a top AI investment category. Threat detection systems use machine learning to identify unusual behavior across networks. Automated response tools reduce reaction times and limit exposure during incidents.

Data governance platforms are also evolving. AI-driven classification tools help organizations manage sensitive information and maintain compliance with privacy regulations.

AI investment trends reveal a clear pattern. Industries are funding solutions that reduce operational risk, increase efficiency, and generate measurable returns. Clear articulation of business outcomes remains essential as AI shifts from an innovation initiative to an infrastructure necessity. For more information, look over the accompanying resource below.

The post Where AI Investment Is Reshaping Industry Strategy appeared first on B2B Marketing Blog | Webbiquity.

Find the answers to those questions and more in the 2026 MarTech Outlook report from Stensul.

For those in the B2B marketing leadership and marketing operations community, this report offers a clear-eyed snapshot of where martech priorities, budgets, and operating models are heading in 2026.

Its core finding is that AI is no longer treated as a side experiment; instead, organizations are increasing martech budgets, investing directly in AI-powered tools, and reshaping teams and workflows to bring more execution in-house—often faster than their processes are ready for.

Here are seven specific findings from the report’s authors.

1. AI Has Become the “North Star” of MarTech Strategy

Across company sizes and business models, AI emerges as the dominant strategic priority for 2026. The report makes it clear that AI is no longer framed as a future capability or a pilot initiative; it is now central to martech roadmaps.

What’s notable, however, is why organizations are pursuing AI. For B2B teams, AI is tied closely to attribution, workflow efficiency, and cross-team alignment, while B2C organizations emphasize speed, scale, and personalization. This distinction matters: it suggests that AI success will be measured differently depending on operating reality, not by a single universal KPI.

The implicit risk here is that AI becomes a broad mandate without a clear operational definition. “Implementing AI” sounds decisive—but without alignment on outcomes, teams may still struggle to move from intent to impact.

2. MarTech Budgets Are Growing—and AI Is Claiming a Bigger Share

One of the clearest signals in the report is that 2026 is a growth year for martech budgets. Nearly 80% of surveyed organizations expect budget increases, with more than half anticipating growth of at least 10%. Roughly a quarter expect increases of 20% or more.

These increases are not evenly distributed. Highly regulated industries and complex environments—such as technology and software—are the most likely to anticipate major budget expansion. This aligns with the reality that complexity drives tooling needs, governance requirements, and process automation.

Crucially, the report shows that AI-powered tools sit at the top of planned martech investments. This confirms that AI spend is not simply incremental; it is often displacing or redefining existing categories of marketing technology.

3. AI Investment Is Shifting from Capabilities to Embedded Execution

The report highlights a subtle but important evolution in AI adoption: organizations are prioritizing AI-powered tools, not standalone AI features or experimental add-ons.

More than half of surveyed companies cite AI-powered tools as their top martech investment area, ahead of traditional marketing automation and analytics. This suggests a preference for AI that is embedded directly into execution—campaign creation, optimization, and workflow management—rather than AI as a separate layer that teams must consciously invoke.

From an operations standpoint, this is encouraging. Embedded AI reduces friction and increases adoption. At the same time, it raises governance questions: when AI is everywhere, controlling quality, compliance, and consistency becomes harder unless guardrails are designed into workflows from the start.

4. B2B and B2C MarTech Priorities Are Diverging in Practice

While AI is the common thread across all organizations, the report makes clear that B2B and B2C teams are optimizing for very different outcomes.

B2B organizations prioritize attribution, analytics, and collaboration workflows—reflecting long, complex buyer journeys and cross-functional handoffs. B2C organizations, by contrast, emphasize campaign creation efficiency and personalization at scale, where speed and relevance directly affect revenue.

For hybrid organizations, AI is often framed as a way to manage complexity across multiple motions. The implication for martech leaders is that “best practices” are becoming less universal. Tool selection and success metrics must be tailored to operating models, not borrowed wholesale from other segments.

5. Collaboration Workflows Are Becoming a Hidden Bottleneck at Scale

Among large enterprises, improving collaboration workflows is the single most cited martech priority for 2026.

As organizations scale, approvals, handoffs, and coordination—not campaign ideation—become the primary constraint.

This finding reinforces a reality many marketing ops leaders already experience: efficiency gains from automation are often lost if collaboration remains fragmented. AI can accelerate content creation, but without structured workflows and shared systems, it may simply increase the volume of work entering already-constrained processes.

The report stops short of prescribing how teams should redesign workflows, but the implication is clear: AI value depends as much on organizational design as on technology selection.

6. In-House Enablement Is Replacing Routine Agency Dependence

One of the most consequential findings in the report is the shift away from agencies for routine execution and toward internal enablement.

Nearly one-third of organizations plan to reduce spending on external agencies, while more than half plan to invest in reskilling in-house teams to support AI adoption.

This does not signal the end of agencies, but it does redefine their role. Agencies are increasingly positioned for specialized, strategic, or high-impact initiatives, while day-to-day execution moves inside the organization.

For B2B marketing leaders, this shift raises important questions about talent, training, and accountability. Owning execution internally can improve speed and control—but only if teams are properly enabled with the right tools and governance models.

7. Training and Enablement Are Emerging as Critical AI Investments

The report underscores that AI investment is not limited to software. Training and upskilling rank among the top planned martech investments, signaling recognition that tools alone do not drive transformation.

This emphasis on workforce enablement suggests a more mature phase of AI adoption. Rather than treating AI as a cost-cutting mechanism, organizations are investing in people to ensure AI is used effectively and responsibly.

What the report underplays, however, is the time and change management required to make this work. Training programs must be continuous, role-specific, and tied to real workflows—not one-off initiatives designed to “check the box” on AI readiness.

Final Thoughts on the 2026 MarTech Outlook

For B2B marketing leaders and operations teams, the 2026 MarTech Outlook from Stensul paints a picture of an industry at an inflection point. Budgets are rising, AI is becoming foundational, and organizations are restructuring how marketing work gets done by shifting execution in-house and investing in internal enablement.

At the same time, the report makes clear that technology alone is not the solution—workflow design, governance, and training will determine whether AI investments deliver meaningful returns.

Check out the full 2026 MarTech Outlook report from Stensul.

ChatGPT assisted with research for this post.

The post From AI Pilots to Operational Reality: Key Takeaways from Stensul’s 2026 MarTech Outlook appeared first on B2B Marketing Blog | Webbiquity.

Find the answers to those questions and more in the 2026 AEO / GEO Benchmarks Report from Conductor.

For those in the digital marketing, SEO, and brand visibility space, this report offers a robust look at how AI answer engines and Google’s AI Overview results are creating new visibility metrics and redefining discovery. Rather than displacing SEO, AI search introduces a parallel visibility surface where brand credibility is measured by citations and mentions within AI responses.

Here are six specific findings from the report’s authors.

1. AI Referral Traffic Is Still Small But Meaningful

AI referral traffic currently accounts for only a little more than 1 % of total website visits across the 10 industries analyzed — underscoring that AI-driven discovery is nascent in volume but significant in impact. Despite its small share, the fact that LLMs and answer engines are directing users before they click into sites indicates a shift in where discovery begins.

2. ChatGPT Dominates AI Referral Sources

Across all industries, about 87 % of AI referral traffic originates from ChatGPT, with other AI platforms like Gemini and Perplexity accounting for smaller but notable shares. This dominance suggests that brands optimizing for visibility on ChatGPT could capture most early AI referrals.

3. Google’s AI Overviews Appear in Over a Quarter of Searches

The report showed that 25% of analyzed Google searches generated an AI Overview result — revealing how often users encounter AI-generated summaries embedded within traditional search results. This signals that brands need to optimize not just for rankings but to earn inclusion in those synthesized answer experiences.

4. Visibility Varies Widely by Industry

Industry benchmarks reveal stark differences: healthcare queries trigger nearly 49% AI Overview results; much higher than real estate, where only about 4.5% of queries return overviews. These discrepancies highlight that query intent and content complexity drive how often AI systems synthesize responses for users.

5. AI Search Doesn’t Replace SEO, It Expands It

Rather than making traditional SEO obsolete, AI search introduces a parallel surface of visibility. Organic search remains the backbone of most traffic, but brands that fail to win citations and mentions within AI answers risk missing out on early discovery moments before a user ever clicks.

6. Brand Credibility Is Measured Differently in AI

Success in AI search isn’t just about traffic; it’s about credibility inside AI responses. The report emphasizes that brands need structured, high-quality content that AI systems can understand and confidently cite. This shifts performance measurement from clicks and rankings to shares of voice within AI answers.

Final Thoughts on AI Search, AEO, and GEO Benchmarks

For marketers and SEO leaders, the 2026 AEO / GEO Benchmarks Report from Conductor underscores a fundamental shift in how people discover brands online. Rather than seeing AI search as a threat to traditional organic discovery, the report shows that it expands the arena of visibility, introducing new metrics and surfaces where brands can capture attention through citations, mentions, and inclusion in AI-generated answers.

For more specific “how-to” content on this topic, check out Optimizing for AI Overviews and AI Searches Make WPO Matter More Than Ever.

ChatGPT assisted with research for this post.

The post AI Search Isn’t Replacing SEO — It’s Rewriting Visibility: Key Insights from Conductor’s 2026 AEO / GEO Benchmarks Report appeared first on B2B Marketing Blog | Webbiquity.