How Brands Should Think About the ROI of Generative Engine Optimization

Marketers are always pressed to prove the return on investment of their efforts, especially when proposing a strategy that relies on disruptive technology. AI search and generative engine optimization (GEO) is the latest case.

For executives wondering how to respond to questions from the rest of the C-suite about the ROI of GEO, it’s unfortunately not a simple answer (and anyone who claims to have cracked it is lying to themselves and you).

The typical “revenue-cost/cost x 100%” framework doesn’t fly when determining the impact that GEO has on revenue. It’s also potentially the wrong way of looking at outcomes.

Today, we’ll take a closer look at why calculating the ROI of GEO is such a complicated task. We’ll also look at why it’s still a critical part of marketing strategies that companies should look at as a combined effort between SEO, Content, Brand, Social, and PR teams.

The Fundamental Flaw in the ROI of GEO Conversations

Before we dive into what success looks like and how to measure it, we need to address the elephant in the room: traditional ROI frameworks don’t work for GEO. 

Like calculating the ROI for any marketing effort, determining the value of your generative engine optimization efforts should follow this formula:

The cost calculation is straightforward to determine. Simply add up all your marketing costs related to GEO: internal team resourcing, agency/freelancer costs, tool subscriptions, etc.

But tying the value of these efforts directly to specific revenue-increasing events is incredibly difficult since generative engines are influenced by activities that fall across multiple teams. There’s a significant overlap between GEO and SEO, sure, but there are PR, Brand, and Social elements at play that further complicate the calculation. 

Just think about how you would go about assigning a monetary value to the following events:

• When asked about your category, ChatGPT mentions your product among the top brands
• Gemini responds to questions about your brand with positive sentiment instead of negative
• A Reddit thread with the title “Is [YourBrand] legit?” ranks #1, and the top answer is “yes”
• Your site is possibly ranking a bit better in the AI Overview, on average, because you’ve added comprehensive GEO-oriented schema markup

These factors have a major impact on buying decisions and brand visibility, but it’s incredibly difficult to assign them a dollar value. 

Calculating the return you get on an investment in generative engine optimization requires the ability to completely attribute the impact that every AI search has on buyer behaviour. And that’s simply not possible.

Why? For a few reasons. Not the least of which is that many of these events happen in zero-click environments. 

1) The Attribution Problem in Zero-Click Environments

The fundamental challenge goes even deeper than traditional multi-touch attribution issues. 

“The ROI of GEO depends entirely on how the company has set up their marketing funnel. GEO operates in zero-click environments like ChatGPT, AI Overviews, and Reddit threads and you can’t track user behavior on platforms you don’t own. Multi-touch attribution breaks down when the ‘touch’ happens outside your ecosystem.” — James Scherer, VP of Strategy at Foundation

The attribution breakdown is a problem many executives miss (or simply ignore). Search engine optimization, while also challenging to measure, at least drives traffic to your owned properties, where you can implement tracking and determine an ROI. 

GEO is an investment in influencing channels that are separate from your domain—AI answers, Reddit threads, social posts, review sites, industry publications, and more. LLMs pull information on your brand from all of these places, but you aren’t seeing trackable traffic that converts neatly into measurable MQLs.

To understand why this makes attribution more difficult, think about who gets credit when a prospect checks the “ChatGPT” box in your signup form: 

• The dev team that optimized your blog article for LLM crawling?
• The SEO team that developed the product comparison page? 
• The PR team that secured the industry publication mention? 
• The community manager who commented on a frequently-cited Reddit thread? 
• The social media team whose YouTube video appeared in the response?

The real answer is that all of these efforts contributed to generating that lead. This is why the ROI of GEO is currently impossible to isolate using traditional attribution models.

2) GEO Is (Often) Brand Awareness & PR, Not Performance Marketing

With the attribution challenges established, we need to reframe how we think about GEO investments. Yes, you can capture AI referral traffic in Google Analytics or set up forms to capture referrals from ChatGPT, but you need to remember the following:

GEO is primarily a brand awareness and sentiment play, influencing decisions early in the journey and with knock-on effects on lead generation.

The impact is real, but it’s often not directly measurable in the same way as paid search or email marketing campaigns. Think of it less like performance marketing and more like:

• PR and media relations
• Brand awareness campaigns
• Thought leadership initiatives
• Industry event sponsorships

All of these activities influence buyer behaviour, strengthen market position, and protect brand equity. But none of them offer clean, direct attribution to revenue. The classic ROI calculation doesn’t do these efforts justice. 

Why GEO Matters Despite Challenges in Proving ROI

Given all these difficulties, why should companies invest in GEO at all? The answer lies in understanding the fundamental shift happening in how buyers research and evaluate solutions.

The uncomfortable truth is that if your leadership demands traditional ROI from GEO, they’re misunderstanding the channel. Instead of asking about the ROI, we encourage them to think about it like this: 

“What’s the opportunity cost of ceding territory to competitors across multiple AI search tools?” 

Recent data from a Magna Media Trials x Reddit survey of over 1,200 people in the US shows that over 53% start their searches with AI assistants at least once a day. Traditional search and social media still lead the way, but the search landscape is continuing to fragment across channels.

A single AI search has the potential to shape how someone approaches the next steps in their online journey.

The Buyer Behaviour Shift Is Already Here

Prospects are no longer starting and ending their research with Google searches that lead to your website and funnel them to high-conversion pages. Brands are losing control of the BoFu journey as potential buyers turn to LLMs, Reddit, and other platforms to inform decision-making. 

The same survey from Manga and Reddit shows that, while traditional search is still the most frequently used tool, the start of online discovery is now spread across a range of different tools.

Now think about how this new search behaviour plays out in an already convoluted B2B buyer journey. Your potential customers are hopping from platform to platform throughout the process:

• Discovery: “What are the best [category] tools for [use case]?” asked to ChatGPT
• Comparison: Searches “[Brand A] vs [Brand B]” on YouTube
• Validation: Asks “Is [Brand] legit?” in a relevant subreddit 
• Deep dive: Only after forming opinions do they visit company websites

If you’re not present in those initial steps, you’ve lost the deal before the prospect ever reaches your website.

There’s also some debate around the influence that AI search results have on conversions. Early data from Semrush suggests that someone who reaches a site via an LLM referral is worth 4.4x more than a visitor through the SERPs because of the personal, word-of-mouth nature of the experience. On the other hand, findings from the team over at Amsive show that there’s no statistically significant difference in the conversion rates of LLM vs organic search visitors (4.87% vs. 4.60%). 

Regardless of how the referral quality debate plays out, the fact that more and more people are incorporating AI tools as part of the search experience makes brand visibility critical. 

The Competitive Disadvantage of Absence

Perhaps the strongest argument for GEO investment is the competitive risk of inaction. Considering the data showing increasing usage during online search—and the findings that buyers may give more weight to AI recommendations—absence from AI responses is a major risk.

Competitors who establish a presence now become the default recommendations. They’ll own the narrative in the discussions that matter. By the time absence shows up in your win/loss analysis, competitors will have spent months or years building positioning advantages that are difficult to overcome.

The best way to think about GEO is as an infrastructure investment, not tactical marketing spend. Just as companies invest in CRM systems before proving direct revenue impact, or in brand guidelines without calculating exact ROI, GEO represents the infrastructure investment required to compete in an AI-mediated research environment.

Ross Simmonds describes this as building “GEO-aware infrastructure” — accepting that influence can’t always be measured in dollars, but absence will definitely be felt in decline.

Understanding What GEO Success Actually Looks Like

Since we can’t rely on traditional ROI metrics, what does success actually look like? 

The answer lies in understanding visibility and positioning metrics, in addition to the conversion metrics that C-Suites typically focus on. Real GEO success isn’t about adding X leads to your pipeline in month one — although that’s still a possibility — it’s about systematically improving your brand’s presence in the AI-powered research process. 

Here are a few examples of what measurable GEO success looks like from our work with B2B companies:

Reddit Thread Influence and Replacement

One of our clients in the financial services space implemented a targeted Reddit strategy over three months. The results:

• Baseline: Of 100 priority Reddit threads being cited by LLMs, 22 were locked/archived (meaning competitors owned the narrative with no ability to participate).
• Outcome: Replaced 14 of those locked threads with new, brand-owned discussion threads.
• Impact: Now authors 6 of the most-cited relevant threads on the platform and generates measurable impressions from both SERP visibility and LLM citations.

Mention Rate Transformation

The same client saw dramatic improvements in mention frequency:

• Baseline: Mentioned in 12 of the 100 priority threads being cited by LLMs.
• Outcome: Now mentioned in 73 of those threads.
• Competitive positioning: Appears above competitors in 53 of those mentions.

These aren’t vanity metrics. When your brand moves from 12% to 73% mention rate in the most-cited discussions in your category, you’ve fundamentally shifted your position in the AI-powered research process.

In a separate engagement with a debt relief company, the team focused on identifying threads that were “open” (able to participate in) but not yet mentioning the brand:

• Baseline: Minimal presence in the top 50 most-cited threads relevant to debt relief services.
• Strategy: Identified threads open to participation; systematically engaged with or created replacement content for high-value discussions.
• Results: Over three months, engaged with or replaced 70% of the top 50 most-cited threads; shifted from minimal presence to becoming one of the most-frequently mentioned providers.

The key insight here is that visibility increases are immediate once optimized content goes live and gets indexed by LLMs. 

The challenging part is doing the analysis to identify which Reddit threads actually matter, but it’s worth the investment. As Foundation’s VP of Strategy, Jamers Scherer notes: “Once you add your brand to the 10 eligible, most-cited threads, you’ll see an immediate and measurable knock-on effect on LLM visibility.”

When LLM Discoverability Does Align with GEO Efforts

Earlier this year, we covered how the form-building company Tally tapped into GEO to drive 25% of new users. Co-founder Marie Martens revealed that ChatGPT had become the company’s leading source of referral traffic and that AI tools contributed over 2,000 new sign-ups to their freemium platform (confirmed through their onboarding survey). 

Just this week, we saw another example of generative engine optimization having a more direct impact on the bottom line: according to Deocebo’s VP of Revenue Marketing, Silvia Valencia, 13% of their high-intent leads come through AI discovery.

Their early insights into what worked align with the SaaS SEO strategy we see driving results across different generative AI tools: 

• BoFu comparison pages that AI overviews can’t summarize (yet)
• Focusing on on-page elements like tables and FAQs
• Implementing self-reporting for attribution capture to replace lost clicks

It’s nowhere near advertising-level attribution, but these results tie in more closely to “needle moving” results that companies want from marketing departments. 

So, What Should You Measure to Prove GEO Success

Because generative engine optimization involves activities across a mix of owned and non-owned channels, proving success depends completely on your context. 

Growth-hungry startups like Tally and Docebo are able to demonstrate the more concrete ROI metrics that C-Suites love. But that may not be the case for an established enterprise that’s dealing with negative sentiment or a complete lack of mentions. It also may not be the case for these companies as LLMs continue to change. 

That’s why measuring and proving the success of GEO efforts means tracking relevant SEO, content, and brand marketing metrics alongside PR-style indicators: 

• Visibility Share: Your percentage of appearances across AI platforms for priority queries (not just mentions in isolation, but actual visibility when prospects search).
• Mention Rate: Percentage of high-value discussions/threads where your brand appears.
• Position Quality: Average ranking when mentioned in lists (appearing #1 vs. #7 matters significantly).
• Thread Ownership: Number of priority discussions your brand authors or meaningfully participates in.
• Competitive Positioning: Frequency of appearing above competitors in shared mentions.
• Cross-Platform Presence: Number of different domains and platforms citing you (Reddit + industry publications + YouTube creates compounding authority).
• Sentiment Score: Positive vs. negative context in AI responses.
• Query Coverage: Percentage of relevant prompts where you appear.

By measuring these indicators with GEO tools like Profound or the Semrush’s AI Toolkit, you can see how success comes from orchestrated cross-channel effort, not from any single source. It’s the marketing equivalent of asking “what’s the ROI of having all your instruments play in harmony?” — the value is in the symphony, not the individual notes.

Now for the next question, how often should you report on these metrics? Whether you’re preparing a GEO RFP to outsource your efforts or building a timeline internally, make sure you have a cadence in place. 

Just because ROI is difficult to measure doesn’t mean measurement altogether is off the table. Intentional GEO measurement requires establishing baselines before execution:

• Monthly: Track mention rate changes, new threads authored, competitive positioning shifts, and visibility share trends.
• Quarterly: Analyze sentiment of mentions, cross-platform presence expansion, and query coverage improvements.
• Biannually: Monitor directional business metrics like branded search volume trends, sales conversation themes mentioning AI tools, and competitive win/loss patterns.

This cadence acknowledges that visibility changes are worth tracking frequently, while business impact requires patience and longer observation windows.

The Value of GEO in an AI-First World

The ROI of GEO is like the ROI of having a good reputation. You can’t calculate it precisely, but you’ll certainly feel its absence when competitors dominate the AI conversation about your category. And by then, it’s already too late.

The brands winning in the battle for AI influence are building for visibility, positioning, and reputation advantages that will compound over time as more buyers rely on AI tools for research.

They understand that success looks different depending on the context: for some, that means increasing the mention rate from 12% to 73% in priority Reddit discussions. For others, it means investing in high-intent comparison pages to drive leads through AI search. 

GEO is about ensuring your brand has a voice in the conversations that shape buying decisions, even when those conversations happen in places you don’t own and can’t fully track.

Ready to expand your presence across leading LLMs? Get in touch with the leading Generative Engine Optimization agency now.