THE SIGNAL - SEPTEMBER 2026 AI

AI AMA with Alisa Scharf and Nick Haigler

Thursday, September 17th @ 12pm ET

 

This month, Alisa and Nick covered research we ran with TrustPilot on how reviews shape brand presence in AI search. 

Have a question you want covered next month? Submit it here

 

Listen to the September episode of The Signal
33:42

 

September 2026 Insights and Action Items

1. Review and trust sites are the number two citation source in AI answers, and they take over right when people decide.

What's happening: Seer's analyzed more than 800,000 responses across ChatGPT, Gemini, AI Mode, and Perplexity and found review sites make up just 3% of citations at the awareness stage, where Reddit and editorial sites dominate discovery, then climb to 23.5% as users move down the funnel toward a decision.

2. Having no reviews is its own signal, and it costs you in head-to-head comparisons.

What's happening: Models will state outright that a brand has "a distinct lack of extensive verified third-party reviews," and in comparison prompts the brand with more reviews had its evidence pulled into responses nearly twice as often as the brand with fewer, even when both had substantial review inventories.

3. One prompt run shows you less than half the field, so three runs is the floor.

What's happening: Seer's prompt frequency test across just under 100 prompts found a single run surfaces five or six brands where ten runs surface twelve or thirteen, with three runs getting you a little more than 70% of the brands ChatGPT will ever name — and legal, beauty, health and fitness, and energy categories need more than that.

4. If you're the first brand named, that position is stickier than everything below it.

What's happening: The usual complaint about AI search is that the same prompt reshuffles the same brands every time, but 75% of runs repeated the same lead recommendation — a spot that's typically inherited from existing market leadership rather than earned through a GEO program, so treat it as a benchmark to defend.

Action Items

1. Pull the review platforms getting cited for your brand's evaluation prompts, then claim those profiles and monitor themes and sentiment. How old is the review driving your brand's perception?

2. Run your 20 to 30 most important prompts ten times each and classify results as locked in, mixed, or volatile. Which of your current reports are built on a single run?

AMA with Alisa and Nick

As always, we ended with open Q+A. Have a question you want us to cover next month? Submit it here.
A: No single tool owns this yet, so our number one buying criteria for any MarTech platform right now is whether it has an MCP connector. Whatever a vendor ships, there will always be something you want to customize. The way we're building it at Seer: pull responses on a schedule into a database or doc, then use AI to compare each response against your brand canon statement. Models are very good at spotting what's right and what's wrong when you hand them the answer sheet.

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Alisa-Scharf-Headshot

Alisa Scharf

Chief AI & Innovation Officer

Alisa Scharf has with over a decade helping Seer clients and teams navigate the biggest shifts in digital marketing. She's a regular conference speaker on AI-driven search and the value of operationalizing AI within organizations.  

nick-haigler

Nick Haigler

R&D Lead, AI and Innovation

Nick Haigler is a R&D Lead at Seer Interactive and a member of the AI Council, where he leads GEO-related projects and research shaping Seer’s approach to AI-driven search. With enterprise experience spanning SaaS, finance, healthcare, and eCommerce, Nick develops analysis-driven strategies that drive ROI and brand growth. 

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