Generative Engine Optimization (GEO) Tools Statistics: US 2025

Generative Engine Optimization (GEO) tools are quickly becoming a core part of marketing toolkits. Whether it’s automating time-consuming tasks or refining how teams produce, evaluate, and scale creative work, these tools are reshaping marketers’ and GEO agencies‘ processes. But as adoption grows, so too does the need to understand what really matters to the people using them

To find out what 2,031,192 marketing leaders in the US’ opinions were about generative engine optimization tools, we utilized AI-driven audience profiling to synthesize insights from online discussions over a year, ending July 27, 2025, to a high statistical confidence level. Their insights offer a clear picture of the priorities, frustrations, and expectations shaping how generative engine optimization tools are being put to work in real marketing environments.

Index

• GEO optimization tools
• AI search visibility tracking software
• Brand visibility tracking tools 
• GEO optimization for AI search 
• Choosing the right GEO Tool
• Curiosity about new solutions is a major driver for motivating 30% of marketing leaders’ teams to explore generative content platforms 
• Ease of use is important for 29% of marketing leaders when choosing a generative optimization tool
• Social media captions are the top priority for 25% of marketing leaders’ generative workflows 
• 81% of marketing leaders say that a GEO tool with workflow automation would be essential in adding the most value to processes 
• 73% of marketing leaders say GEO output quality is relevant to their goals 
• A high learning curve is a minor challenge for 51% of marketing leaders using generative engine optimization tools  
• 52% of marketing leaders say that GEO tools will provide a significant advantage for internal teams focusing on strategy 
• 27% of marketing leaders say that human editing is essential in the final steps of their workflow
• 66% of marketing leaders say that personalization at  scale is a strategic priority for gaining traction in their GEO strategy 
• 40% of marketing leaders are neutral about whether generative technology can improve conversions  
• 53% of marketing leaders say that free trial testing is essential for evaluating GEO tools
• 19% of marketing leaders measure generative output success by moderately positive campaign lifts
• Stronger analytics would influence 34% of marketing leaders to use a GEO tool in the future 
• 26% of marketing leaders agree that consistent updates are essential in generative engine optimization platform providers
• 69% of marketing leaders’ companies have a significant presence in New York   
• Inside the GEO revolution
• Methodology

GEO Optimization Tools

GEO optimization tools give marketers a way to shape how their brand appears in AI-driven search results. The right tools pinpoint visibility gaps, see exactly how competitors are showing up, and get a clearer picture of the themes AI already links to a brand. Many offer topic clustering, authority scoring, and deep competitor analysis, providing the kind of insight that’s hard to get from traditional SEO tools. Beyond just being found, the aim is to be the brand AI wants to use as the go-to answer.

GEO optimization tools also help marketing leaders keep pace with change. AI search behavior moves fast, and the queries that matter today may look different next quarter. By tracking how AI systems pull and present information over time, leaders can make precise adjustments instead of relying on broad guesses. That might mean refining headlines so they’re easier for AI to interpret, adding depth to pages that get cited often, or creating new content to cover emerging topics before competitors do.

With more buying journeys starting in AI-assisted search, GEO optimization tools are quickly moving from nice-to-have to essential. 60% of U.S. adults now use AI to find information, and 26% use it when shopping. Being visible at the right moment, with the right answer, can be the difference between getting a click and never being part of the conversation.

AI Search Visibility Tracking Software

Several platforms now specialize in showing exactly when, where, and how a brand appears in AI-generated search results. They go beyond traditional SEO metrics, helping marketers understand whether generative search systems are citing their content, recommending products, or mentioning a brand in answers for relevant queries.

These are some of the most popular:

SEMrush: The AI Toolkit adds AI result monitoring to its well-known SEO suite. It tracks how a brand surfaces in Google AI Overviews, ChatGPT Search, and other AI-enhanced search environments. Alongside visibility metrics, it delivers competitive analysis so marketers can see where they stand against key rivals and where there’s room to improve.

HubSpot: The AI search grader measures how content performs in AI-driven search and compares it directly to competitors. It shows how AI systems interpret pages and offers clear, actionable tips to boost semantic relevance, so content better matches the context and intent those systems favor. By pinpointing weak spots and quick wins, marketers can adjust copy, structure, or topics to improve visibility where it matters most.

Surfer SEO’s AI Tracker: This tracker keeps tabs on brand mentions and keyword triggers across multiple AI platforms, with the added benefit of prompt-specific tracking. It reveals which terms, formats, and even query styles are helping brands surface in AI-generated answers. By highlighting patterns in the prompts that work best it provides a clearer roadmap for refining keywords, adjusting content structure, and targeting the formats AI favors most.

The magic happens when the data is put to work. If SEMrush shows that competitors are dominating certain queries, HubSpot can help refine messaging, and Surfer can highlight the prompts where a brand is underrepresented. Together, they provide a clear, actionable picture of how to boost share of voice in AI-generated results.

Brand Visibility Tracking Tools 

These platforms are built to monitor how a brand appears in AI-generated answers, summaries, and citations, and to provide the data needed to shape that presence. Each takes a different approach, making it easier to find one that matches your scale and goals.

Profound: Profound is an enterprise-grade platform built for global teams managing visibility across multiple languages and markets. Alongside advanced multilingual tracking, it offers in-depth sentiment analysis to show exactly how a brand is being perceived, plus proactive crawler optimization to ensure AI systems are accessing the most current content. Its detailed, high-volume reporting makes it especially valuable for organizations that rely on precise, actionable insights to shape their presence in AI-driven search.

Peec: A lighter, more affordable option aimed at small-to-medium businesses and agencies that want AI visibility tracking without the heavy lift of enterprise software. Its clear dashboards and easy-to-read metrics make it simple to spot patterns, track changes over time, and identify opportunities for improvement. The platform’s straightforward setup means teams can start making data-driven adjustments almost immediately.

Demandsphere: This tool combines competitive benchmarking with detailed content performance tracking, giving brands a dual view of how they’re being cited and how that stacks up against rivals. Its insights help pinpoint wins and where marketers may need to refresh or expand content to close competitive gaps. This makes it a strong fit for brands that want to stay sharp in fast-moving AI search landscapes.

Athena HQ: Athena HQ brings semantic relevance scoring into play, measuring how closely content matches the context AI models use when crafting answers. Alongside tracking, it offers practical suggestions for refining language, structure, and coverage to improve content’s resonance with AI systems. It’s particularly effective for brands in niche or competitive markets where precision matters.

Otterly: Built with startups and smaller teams in mind, Otterly offers quick setup and an interface that focuses on what matters most, such as monitoring citations, tracking sentiment, and spotting shifts in visibility. By stripping away unnecessary complexity, it keeps budgets lean while still providing the insights needed to maintain a strong AI search presence.

Whether marketers are looking for granular data, competitor insights, or a lightweight monitoring tool, these platforms make it possible to see and influence how AI represents a brand across the web.

GEO Optimization for AI Search 

Some platforms focus purely on tracking visibility, but others go further by supplying the tools to actively improve it. GEO optimization platforms analyze how AI search engines are interpreting content, then provide actionable steps to increase online presence in those answers.

SparkToro: This tool helps uncover what your audience is talking about, where those conversations are happening, and which influencers are shaping them. While SparkToro is not built solely for AI search, its audience insights can guide the topics, tone, and formats that AI models are more likely to surface, making content feel naturally relevant in those results.

Scrunch AI: Built for large-scale organizations that need to track visibility across complex AI search landscapes, Scrunch AI monitors presence in real time, maps how users move through AI-driven search journeys, and flags inaccurate or misleading brand references. Its recommendations give a clear path to securing a stronger place in the answers customers actually see.

Goodie AI: Goodie AI focuses on generative engine optimization, blending visibility tracking with content gap analysis and practical ways to boost GEO presence. It keeps tabs on mentions across platforms like ChatGPT, Gemini, and Perplexity, and its AI Optimization Hub offers source-by-source recommendations for improving visibility. With built-in content creation tools, it helps marketers close gaps fast and stay in step with shifting AI search trends.

By using platforms like these, brands can pinpoint where they’re being overlooked, understand the themes that already connect to their expertise, and create content designed to become part of the answers that matter most in AI search.

Choosing The Right GEO Tool

Finding the right GEO tool starts with knowing what you want it to do. Some platforms are built for pure monitoring, giving a clear view of when and where your brand shows up in AI search results. Others layer in optimization features, helping you actively shape that presence rather than just watch it unfold.

Think about the scale you need to work at. Enterprise-grade solutions tend to offer deeper analytics, multilingual tracking, and more complex integrations, while lighter tools focus on speed, simplicity, and affordability. If you have a team that thrives on data, advanced sentiment analysis, and competitor benchmarking might be worth the extra spend. If you’re working lean, a clear dashboard and straightforward metrics may be all that’s needed.

It also pays to look at platform coverage. A good GEO tool should track visibility across the AI search engines your audience actually uses, whether that’s ChatGPT Search, Gemini, Perplexity, or newer players. It’s even better if it can spot emerging formats that AI models are favoring, like video snippets or interactive answers.

Ultimately, the best tools make it easy to see your AI visibility at a glance, understand what’s driving it, and take action to improve it, without slowing your team down. 

With so much to offer and such enormous potential, this is what our audience of over two million marketing leaders says about the topic:

What Motivates Your Team To Explore Generative Content Platforms?

Curiosity about new solutions is a major driver for motivating 30% of marketing leaders’ teams to explore generative content platforms 

Teams are approaching generative content platforms with a mix of exploration and intent:

Curiosity about new solutions is the biggest motivator for teams exploring generative content platforms. It’s a major driver for 30% of marketing leaders in our audience, a significant factor for 12%, a minor consideration for 4%, and not a motivator for 7%. This makes sense, given that 60% of marketers believe generative AI will transform their role, fueling interest in new tools and approaches. Strategic experimentation is also in play, with 12% calling it a major driver, 7% a significant factor, 2% a minor consideration, and 1% saying it’s not a motivator.

Rounding out the list, increased content demand is a major driver for 5%, a significant factor for 8%, a minor consideration for 2%, and not a motivator for another 2%. The desire for faster campaigns is a major driver for 2% and a significant factor for 7%, while lack of internal resources is a significant factor for 1%.

Combined, these insights suggest that while curiosity and future-readiness are leading the charge, practical needs like speed, scale, and resource constraints are reinforcing the shift toward generative content solutions.

What Is The Most Important Factor When Selecting A Generative Engine Optimization Tool?

Ease of use is important for 29% of marketing leaders when choosing a generative optimization tool

Practical considerations take the lead in selecting the right tool:

Ease of use tops the list of factors in selecting a generative tool, with 29% of marketing leaders calling it important and another 19% saying it’s less significant. Many platforms now build their interfaces to feel familiar, borrowing design cues from tools like Gmail or Microsoft Office so users can find their way around without needing formal training. This focus on intuitive design likely plays a role in why ease of use stands out.

Customer support is considered important by 28% and less significant by 7%. Integration options are viewed as important by 11%, and 5% say they’re less significant, showing where priorities lie.

What Type Of Content Do You Prioritize For Generative Workflows?

Social media captions are the top priority for 25% of marketing leaders’ generative workflows 

There’s one content format that’s clearly front and center, even if not everyone agrees on how much it matters:

The types of content prioritized for generative workflows show that social media captions are a standout and a sticking point. For 25% of marketing leaders, they’re the top priority, and another 30% call them important. Conversely,  43% rate them as a low priority, showing just how divided teams are on where social content fits into generative workflows.

This contrast reflects how teams are still experimenting. Generative AI is already helping social media marketers draft captions, replies, and hashtags at speed, but not everyone is leaning on it just yet.

Landing pages are marked important by only 1%, while video scripts are a top priority for just 1%, suggesting longer-form assets still rely more on human input. Interestingly, no opinions were expressed on the importance of blog articles or product descriptions, pointing to a narrower focus in current generative strategies.

Which Feature Of A Generative Engine Optimization Tool Would Bring The Most Value To Your Process?

81% of marketing leaders say that a GEO tool with workflow automation would be essential in adding the most value to processes

One feature dominates the GEO tools wish list:

Workflow automation is by far the feature marketing leaders value most in their generative processes. A full 81% of our audience call it essential, and another 9% say it would be highly valuable. That strong focus is a choice backed by results. According to PwC’s 2024 AI Jobs Barometer, industries with the highest AI integration are seeing 4.8 times greater labor efficiency growth.

Performance insights come next, but at a distant second, with 3% calling them essential and 2% saying they would be highly valuable. Real-time editing is essential for 2% and somewhat useful for 1%, while multi-language support is only somewhat useful for 1%. Brand voice options are a highly valuable feature for just 1%. Clearly, teams are still eager for strategic tools, but getting the day-to-day flow right comes first.

How Do You Currently Evaluate Generative Engine Optimization Output Quality?

73% of marketing leaders say GEO output quality is relevant to their goals 

Most marketing leaders are thinking strategically:

Relevance to goals is the top priority for 73% of marketing leaders in evaluating GEO output quality. Readability still carries weight, cited by 27%, but it clearly plays a supporting role in whether the content is actually moving the needle.

This focus on strategic alignment echoes a recent point made in The Economist, which noted that reviewing AI-generated work still calls for human expertise and good judgment. Even with powerful tools at our fingertips, it takes experience to decide if the content is truly hitting the mark or just filling space. It’s not just about how well something reads, but whether it gets results.

What Challenge Do You Face When Using Generative Engine Optimization Tools?

A high learning curve is a minor challenge for 51% of marketing leaders using generative engine optimization tools  

For many marketing leaders, using generative platforms isn’t hard, but it’s not always smooth sailing either:

The high learning curve is the most common challenge in using these platforms, but just 10% of marketing leaders see it as a significant challenge, and 51% call it a minor issue. This suggests that while these tools are accessible, they’re not always intuitive from the start, and part of that adjustment may come from figuring out how to fit these platforms into existing workflows. 

Luckily, generative engine optimization builds on familiar concepts from traditional SEO. But while this may help speed up adoption, it doesn’t eliminate every roadblock.

Other hurdles remain, and for our audience, originality concerns are a significant challenge for 8% and a minor issue for 4%. Accuracy of information is a significant challenge for 6% and a minor issue for another 6%. Limited training material is seen as a significant challenge by 7%, while 1% are neutral. 

Workflow disruption is noted as only a minor issue by 7%, indicating that while there are several concerns around using generative engine optimization tools, this is not a major pain point for most marketing leaders.

What Internal Team Benefits Do You Hope To Achieve With Generative Engine Optimization Tools?

52% of marketing leaders say that GEO tools will provide a significant advantage for internal teams focusing on strategy

Speed helps, but it’s giving teams the headspace to plan that matters most to marketing leaders: 

When it comes to internal benefits, US marketing leaders are hoping these tools will give teams room to think bigger. Better focus on strategy leads the list, with 52% calling it a significant advantage and another 15% seeing it as a potential gain. 

That focus tracks with how AI is transforming strategy development by helping companies automate the more mechanical parts of strategic planning, like running scenarios or analyzing competitor moves, so teams can spend more time on higher-impact decisions.

Other benefits don’t rank quite as high. More content output is seen as a significant advantage by 16% and a potential gain by 6%, while easier collaboration is listed as a significant advantage for just 9%. Time savings comes in at the bottom, with only 2% saying it’s a significant advantage. This is interesting as time equals money, and marketers are currently prioritizing quality and strategy over sheer speed. 

How Important Is Human Editing In Your Generative Engine Optimization Workflow?

27% of marketing leaders say that human editing is essential in the final steps of their workflow 

Some marketing leaders treat editing as essential, while others barely touch it:

Human editing plays a key role in generative engine optimization workflows, but the way it’s used varies across teams. For 27% of marketing leaders, editing is always part of the final steps and considered essential, with another 10% saying it’s important. 

Some prefer a lighter touch, with 16% calling editing rarely required but essential, while 22% say it’s important but infrequent. For others, the focus is structural. Editing that targets layout and flow is essential for 10%, but 16% don’t see it as important at all.

This emphasis on human involvement lines up with broader shifts in how companies think about digital credibility. IDC projected that over 70% of G2000 companies would have formal programs in place to monitor their digital trustworthiness by 2022, and human editing remains a key part of that trust equation.

Which Use Case Is Gaining Traction In Your Generative Engine Optimization Strategy?

66% of marketing leaders say that personalization at scale is a strategic priority for gaining traction in their GEO strategy 

While several strategies are in play, one emerges as the dominant focus:

Given that 81% of customers prefer brands that offer personalized experiences, it’s no surprise that the use case gaining the most traction in generative engine optimization strategies is personalization at scale, with 66% of marketing leaders in our audience seeing this as a strategic priority.

Real-time optimization shows emerging interest, with 9% listing it as a strategic priority, though 6% say it’s not a focus. Market trend analysis follows closely at 7%. Audience targeting and A/B content testing are each a strategic priority for 5%, while 2% say audience targeting is not a focus. 

While teams are exploring different tactics, the strongest momentum is clearly behind scalable personalization that keeps up with rising customer expectations. 

Which Content Goals Align With Generative Technology?

40% of marketing leaders are neutral about whether generative technology can improve conversions  

What’s most striking here is how few marketing leaders are taking a clear position: 

The content goals aligning with generative technology are still up for debate, with most responses sitting squarely in the neutral zone. This widespread caution may be driven by broader strategic concerns. The fact that 65% of CEOs are prioritizing AI use cases based on ROI could explain the hesitation around aligning generative tools with specific content outcomes.

Improving conversions received a neutral response from 40% of marketing leaders in our audience, while 34% said the same about scaling creative testing. Growing website traffic was viewed neutrally by 25%, with no opinions expressed regarding launching campaigns quickly or supporting sales materials. This pattern suggests that many teams are still weighing their options. 

How Do You Approach Generative Engine Optimization Tool Evaluation?

53% of marketing leaders say that free trial testing is essential for evaluating GEO tools

Marketing leaders rely on different cues when deciding which tools are worth exploring:

Free trial testing stands out as the go-to approach for evaluating generative optimization tools, with 53% of marketing leaders saying it’s essential to the process. That preference speaks to the psychological appeal of free offers, where the zero-cost element removes the usual cost-benefit analysis and makes the offer feel risk-free.

Analyst reports are also a key part of the mix, considered essential by 36%. Case study reviews are seen as essential by 6%, while vendor demos trail slightly at 5%. The data points to a strong preference for hands-on experience and trusted third-party perspectives over more traditional sales materials.

How Do You Measure Success From Generative Outputs?

19% of marketing leaders measure generative output success by moderately positive campaign lifts

Marketing leaders are now chasing results that drive real impact:

Measuring success from generative outputs is becoming less about any single metric and more about what drives business results. Generative AI requires a new set of  KPIs to measure success, and many companies are now focusing on outcomes like time savings, scalable content production, and reduced manual effort. That expanded view helps explain why traditional indicators only go so far.

Campaign lift fits squarely into that shift. It leads the pack, with 19% of marketing leaders in our audience calling it a strongly positive signal, another 11% seeing it as moderately positive, and 20% viewing it neutrally or negatively. SEO rankings still carry weight, delivering a strongly positive result for 10% and a moderately positive outcome for 15%, but 20% report neutral or negative impact.

Engagement metrics show a smaller return, with 5% calling them strongly positive and 2% moderately positive. Internal feedback registers only a 2% moderately positive score, and conversion rates are seen as a strongly positive measure by just 2%, putting them firmly at the bottom.

What Future Generative Engine Optimization Tool Capability Would Influence Your Decision Most?

Stronger analytics would influence 34% of marketing leaders to use a GEO tool in the future 

Priorities show where marketing leaders are placing their bets as generative tools evolve:

Stronger analytics is the most influential future capability in generative engine optimization, according to 34% of marketing leaders in our audience. This reflects a growing need for tracking performance across generative engines, with teams focusing on metrics like engagement, time on page, click-through rate, and conversions to guide smarter decisions.

Better automation is close behind at 33%, pointing to a clear push toward streamlining workflows and working more efficiently. Flexible integration follows at 24%, showing how important it is to connect platforms and keep data flowing smoothly. Smarter suggestions come in at 9%, indicating that while smart features matter, teams are putting more weight on clarity and control.

What Do You Value Most From Generative Engine Optimization Platform Providers?

26% of marketing leaders agree that consistent updates are essential in generative engine optimization platform providers

One feature stands out as the most prized among GEO platform provider offerings:

Consistent updates are the most valued feature from platform providers, with 26% of marketing leaders in our audience calling them essential and another 36% saying they’re valuable. As the World Economic Forum points out, continuous training and evolving LLM algorithms are key to advancing generative AI. Regular updates are what make these improvements possible, which may be why updates rank well ahead of other platform features.

User education is next, with 15% saying it’s essential. Customization options are considered essential by 11%, and easy onboarding by 4%. A transparent roadmap ranks far lower, with just 1% calling it essential and 7% saying it’s valuable, indicating where the biggest value overall lies.

What City Is Your Company Primarily Located In?

69% of marketing leaders’ companies have a significant presence in New York  

While the West has influence in our audience, the center of gravity for generative strategy appears firmly rooted on the East Coast:

New York stands well ahead of other cities as the primary base for marketing leaders using generative engine optimization, with 69% reporting a significant presence there. That momentum may reflect what’s happening on the ground. In North Brooklyn, for example, new businesses are opening faster than existing ones close.

Los Angeles follows at 26%, with a significant presence that shows solid traction on the West Coast. San Francisco accounts for a significant presence, too, though at just 5%. Even so, with nearly a third of the footprint split between these two cities, the West Coast is still very much in the game.

Inside the GEO Revolution

GEO tools are fast becoming a core part of how marketing teams work. These insights from over 2 million marketing leaders point to a clear shift toward practical tools that help teams stay consistent and focused on the bigger picture. 

While the exact priorities may vary, one thing is clear: these tools are changing how teams shape their campaigns and how they keep things running smoothly.

Methodology

Sourced using Artios from an independent sample of 2031192 United States Marketing Leaders’ opinions across X, Reddit, TikTok, LinkedIn, Threads, and BlueSky. Responses are collected within a  95% confidence interval and 4% margin of error. Results are derived from opinions expressed online, not actual questions answered by people in the sample.

About the representative sample:

• 54.8% of marketing leaders in the US are aged 45 and above.
• 55.1% identify as male, while 44.9% identify as female.
• 58.1% earn between $80,000 and $200,000 annually.
• 54.7% reside in the Pacific region.