Different AI search engines are showing users vastly different robo-advisor brands, even when answering identical questions. A measurement study across Perplexity, ChatGPT, Gemini, and Claude found that brand visibility swings wildly depending on which engine a user consults, revealing how fragmented the answer-engine landscape has become for financial services.

Why Do Answer Engines Show Such Different Results for the Same Question?

Each AI search engine pairs a different underlying language model with its own retrieval system, meaning a brand's appearance rate reflects that specific engine's search behavior as much as the brand's actual market position. Researchers at 5WPR tested 24 prompts three times each across the four engines, attempting 288 answers and receiving 186 usable responses about robo-advisors.

The disparities are striking. ChatGPT named Vanguard in 97.8% of its 46 returned answers, while Claude mentioned Vanguard in only 30.4% of its own 46 answers. Perplexity named Fidelity in 95.8% of its 48 answers, compared with just 39.1% for Gemini. Charles Schwab appeared in 91.3% of ChatGPT answers but only 21.7% of Gemini answers. A brand team measuring only one engine could reasonably conclude it dominates the category or is nearly invisible, and be wrong either way.

Does Appearing in an Answer Engine Actually Help a Brand?

Appearing in an AI-generated response is not the same as being cited as evidence. Betterment led the overall visibility index at 69.4% appearance rate across all 186 answers, with Vanguard at 66.7% and Fidelity at 66.1%. However, when researchers looked at which brands supplied their own website as the source for those answers, the rankings shifted dramatically.

Fidelity had the highest owned-domain citation rate at 26.3% of answers with retrieval evidence, more than double Betterment's 12.4% rate. Wealthfront followed at 17.7%, Vanguard at 14.0%, and Charles Schwab at 13.4%. Most striking, Robinhood, SigFig, Webull, and Public each had a 0% owned-domain citation rate despite appearing in returned answers, meaning the engines named these brands from training data or competitor pages without ever quoting their own websites as supporting evidence.

This distinction matters because it reveals two separate contests. Betterment is winning the visibility game, but Fidelity is winning the credibility game by supplying its own authoritative content to back up the claims answer engines make about its products.

How to Build Your Brand's Presence Across Answer Engines

• Publish Direct, Sourceable Content: Brands like Robinhood, SigFig, Webull, and Public should create pages that directly explain how their automated investing products work, formatted as citable answers rather than marketing copy. Answer engines can only cite what they can retrieve, so product pages must be written for machine readability.
• Monitor Each Engine Separately: A brand team cannot assume its visibility is stable across all platforms. Charles Schwab's 91.3% appearance rate on ChatGPT versus 21.7% on Gemini signals a significant gap that requires investigation into how each engine's retrieval system ranks financial content.
• Rebuild Tax and Account Pages for Retrieval: SoFi and M1 Finance, at 5.9% and 4.8% owned-domain citation rates respectively, should restructure their tax-loss-harvesting and account-minimum pages as direct, citable answers rather than marketing-focused content that answer engines are less likely to quote.

What Role Do Publishers Play in Answer Engine Visibility?

Financial-advice answer engines lean heavily on established publishers with editorial review processes for regulated-product comparisons. Forbes appeared as a cited source in 72.6% of the 186 answers with retrieval evidence, ahead of NerdWallet at 48.9% and CNBC at 35.5%. This means a brand's own product pages compete directly against these major publishers for the same citation slot rather than filling an empty one.

The research also connects to a broader shift in how answer engines shape brand perception. Forrester research published on the same day argues that answer engines have become a brand-building channel for marketers, shaping consumer preferences before website visits occur. Rather than simply capturing existing demand through ranked links, these systems influence awareness, consideration, and purchase intent through conversational responses that shape how brands are understood.

"Answer engines are the primary audience that marketers must influence because they determine when and how buyers form preferences," said Nikhil Lai, Principal Analyst at Forrester.

Nikhil Lai, Principal Analyst at Forrester

Forrester argues that marketers should not treat answer engine optimization as simply an extension of search engine optimization. Organizations focused only on rankings, snippets, and clicks may overlook how large language models present a brand's relevance, differentiation, and trustworthiness to prospective buyers.

Answer engines also compress the consideration journey by allowing consumers to ask multiple follow-up questions in a single exchange. Users can compare products and assess options more quickly, while brands face greater pressure to appear credibly in AI-generated responses earlier in the decision-making process.

The fragmented results across Perplexity, ChatGPT, Gemini, and Claude suggest that financial brands cannot rely on a single visibility measurement or assume their market position is consistent across the answer-engine ecosystem. Instead, they must build a presence that works across multiple retrieval systems, supply their own authoritative content for citation, and recognize that appearing in an answer is only half the battle; being quoted as evidence is what actually shapes buyer preference.