Control what you can, earn what matters: reflections from Trustpilot Horizon 2026
Alicia Skubick, Chief Customer Officer, Trustpilot
We’ve all seen AI dominate conversation at industry events over the last few years. But so much of the conversation stays stuck at a 30,000-foot view. Marketing and customer experience leaders are tired of the speculation. We want real-world playbooks, hard data, and actionable execution strategies.
That was the palpable energy in the room at Trustpilot Horizon, where more than 250 marketing and CX leaders joined us for a day of insights and practical frameworks. We learned from our CEO Adrian Blair why he sees the foundation of trust as transparency, credibility and humanity. We dived into the findings of our latest AI visibility study of 411,000 AI answers. And we heard about what’s next for Trustpilot as we continue to help businesses improve product and location visibility in AI answers.
It wasn't designed as a retrospective. Instead we made it an open forum on how modern brands adapt and win as consumer discovery shifts under our feet.
This was reflected by a theme in the questions submitted by our audience on the day. When AI tools are generating their answers independently, how can you influence their recommendation?
To show how brands can adapt to this new reality, I introduced ‘The AI playbook for marketers & CX leaders’. If you couldn’t join us at Trustpilot Horizon, or simply want a recap, here are my reflections on the main takeaways from the day.
The core theme of takeaway from our discussions during the day was clear: AI search has collapsed the divide between brand and performance. In this new world of AI search, visibility cannot be bought, but needs to be earned.
The new search narrative: Control what you own, earn what matters
For decades, marketers perfected owned channels, search rankings, and brand narratives. But today, discovery looks radically different. When someone asks an AI tool about your brand, it doesn't rely solely on marketing claims.
Instead, AI tools synthesize the public evidence from across multiple distinct areas:
Owned content: Your website, product descriptions, and official policies where you explain the offer.
Customer Experience: Independent reviews and real-world proof where customer feedback shows how well brand claims are met.
Expert validation: Media coverage, analyst reports, creator content, and publishers where third parties validate authority.
Community discussion: Forums and social channels where real people’s language and friction points surface.
Modern brand equity is built when the public evidence does two connected jobs. On one side, priming demand by building awareness and emotional connection. On the other, proving you make good on brand promises. You can directly control your ad spend, creative, written content, and product design. But in an AI-driven ecosystem, visibility is won through earning authentic trust.
To evaluate whether public evidence is more likely to carry weight with AI models, we use the Three Rs in a diagnostic framework:
Relevance: Does the evidence directly answer specific user questions? Does it use conversational human language?
Recency: Is the information continuously refreshed? Does it reflect what is true about your business today?
Ranking: Is the evidence published on highly authoritative surfaces? Can search and AI systems crawl and retrieve it?
Evidence layering: Matching specific proof to specific questions
But consumers don’t only ask AI about brands. They ask about specific products, stores and locations. This ties strongly back to the relevance point in the diagnostic framework above.
Trustpilot partnered with Seer Interactive to find out what this means for brands. A study was run analyzing over 411,000 AI responses across four of the major AI platforms.
The study was designed to test whether adding specific layers of customer proof, like dedicated product and location reviews, improves a brand's AI visibility when consumers ask targeted questions.
The findings revealed that 'evidence layering' significantly boosts AI citation coverage. What’s more, Trustpilot citation coverage rises from around 5% for awareness-stage queries to between 89% and 98% for trust- and review-focused questions.
This shift highlights why relying on brand-level service reviews alone is no longer sufficient.
To capture high-intent buyers, brands need to adopt an "evidence layering" strategy:
Product-level proof: Dedicated product review pages are cited in 51% of relevant product-level AI responses. Crucially, adding product reviews can boost your overall brand citation rate by over 11 percentage points.
Location-level proof: When AI tools respond to location-specific queries, 85% of citations point directly to specific location review pages over general brand profiles. Even having just 5 to 9 reviews on a location page increases citation coverage to roughly 53%.
Depth of proof: In head-to-head brand comparisons, brands with deeper review coverage get cited up to twice as often (1.7x), giving them greater representation in the final answer.
The strength of this strategy lies in layering product and location reviews on top of your core brand trust. You feed AI engines the specific, verified evidence they need to answer nuanced customer questions and recommend your business with confidence.
Measure and improve: Building a continuous AI visibility loop
Earning and maintaining AI visibility isn't a one-time setup. It requires an ongoing operational cycle to measure performance, assign ownership, and refine your approach over time. To track your brand's footprint effectively, teams must evaluate four key aspects of AI visibility:
Access: Monitor server logs to confirm whether known AI crawlers can reach and index content. Remove technical barriers and improve overall accessibility.
Presence: Conduct structured prompt testing across key intent-based questions. Measure how often your brand and content appear in AI answers.
Representation: Analyze response quality, tone, and accuracy. Do they accurately reflect your real product and service as they are now?
Action: Track downstream referral traffic (even if it’s small for now). Find out how AI visibility influences people’s behavior and choices.
Putting this model into practice requires clear cross-functional ownership. Rather than creating new silos, establish a small standing working group supported by technical and product specialists. Running a continuous improvement cycle of measuring results and retesting prompt performance. These steps ensure your brand builds sustainable, long-term AI visibility.
Winning in the age of AI: 5 practical priorities
If you're ready to move from speculation to execution, here are five practical steps your team can take today to put the AI visibility playbook shared at Horizon into action:
1. Test your AI search representation: Run key intent-based questions across major engines (ChatGPT, Gemini, Perplexity, and others). Document where your brand appears, which sources are cited, and where unaddressed negative sentiment or blank spaces exist.
2. Map evidence to key questions: Select 10–15 core questions that drive consumer decision-making in your category. Map whether your owned content explains the answer, and whether independent customer experience data proves it.
3. Unify marketing and CX targets: Align your Marketing and CX leaders under shared metrics. Embed customer operations data directly into growth and performance teams. Give paid media teams real-time visibility into feedback themes.
4. Fix operational gaps before AI finds them: Start treating customer feedback proactively. Address recurring customer complaints to resolve operational bottlenecks. Answer engines can see thin profiles or unaddressed negative trends as a warning sign.
5. Optimize technical accessibility: Ensure your product information, location feeds, and review data utilize structured schema markup. This allows answer engines to easily crawl, verify, and cite your brand proof.
Post-event resources
Whether you joined us for the day or couldn't make it to Horizon, the conversation doesn't stop here. Here are some resources to help you start building your brand’s own actionable AI visibility playbook.
Alicia Skubick
Chief Customer Officer