FinTech brand: +35% mentions in AI answers

The problem

On financial queries the brand was never quoted. Assistants answered with competitors and with aggregators, and nothing on the site was shaped in a way a model could lift.

What we did

AEO content rewritten so each answer sits whole in one paragraph, FAQ schema on the pages that carry conditions, monthly monitoring runs, and work on third-party mentions so the brand reads as one entity across sources.

Result

Share of answer sets containing a brand mention rose 35% over six measured runs. Under NDA: the industry and the trend, not the brand or the absolute numbers.

Presence is measured by running a fixed question set and recording mode, region and date every time. Without those three, this month cannot be compared with the last one.

Method: finance is judged more strictly

Both search and assistants are harsher on money topics, because a wrong answer costs the reader. They cite sources that carry dates, caveats and checkable conditions — not promises.

Every number with a source and a date. Rates, limits and fees change; an undated figure ages into something unreliable, and unreliable does not get quoted.

Conditions in full. Price, requirements, timing and what happens if you break them — those are precisely the fragments a model can extract.

Named accountability. An author with verifiable credentials and the company's legal details; without them a finance site reads as risky.

Consistency off-site. Name, licences and specialism have to match across directories, profiles and publications, or the brand never resolves into a single entity.

Services used on this project: Generative Engine Optimization.

Relative metrics only: these projects are under NDA, so the industry, the timeframe and the direction of change are published and the brand and absolute volumes are not. On a call we walk through the same structure applied to your market: baseline, work, expected metric.