Retirement Planning Searches In One Metro Market Now Lead Back To One Firm
Few categories make AI engines more cautious than personal finance. Generic advice, however accurate, almost never earns a citation - and for years, that was the only kind this firm published.
The Challenge
Few categories make AI engines more cautious than personal finance, and that caution works against generic advice almost by design. When someone asks an AI assistant how much they need to retire in this firm's metro market, or whether they should convert a 401(k) to a Roth before leaving work, the model is unusually picky about who it cites. It wants a named, credentialed source attached to the answer, not an anonymous "Wealth Team" byline sitting on top of advice that could have come from anywhere.
This firm's content technically wasn't wrong. It just wasn't useful to anyone in particular. Articles cited the standard 4% withdrawal rule and generic Social Security claiming strategies pulled from national data, while the firm's actual clients were dealing with state-specific income tax treatment of retirement distributions and a cost of living particular to their own metro area. A retirement calculator built for the whole country answers a different question than the one a local retiree is actually asking.
Compliance made it worse before it made it better. Every published page had gone through a review process built to minimize regulatory risk, which over time had also minimized anything specific enough to be useful. The result was content vague enough to clear legal review and vague enough that no AI model had a reason to treat it as the definitive word on anything.
The Approach
We built individual advisor profile pages listing each planner's CFP designation, years in practice, and specific areas of focus, then added Person and Organization schema connecting named advisors to every article under their name. Working with the compliance team, we also established a faster review track specifically for factual, non-promotional educational content, separate from the slower process used for promotional material.
We rewrote the firm's core retirement planning guides around its actual service area: how the state treats retirement account withdrawals for tax purposes, a cost-of-living-adjusted retirement number specific to the metro market, and the quirks of the regional Social Security office that generic national content never mentions. National-average advice gave way to advice that matched the questions local retirees were actually asking.
We worked with the firm to anonymize and aggregate its own client data - average retirement age, typical withdrawal rates clients actually use, common timing patterns for Roth conversions - into an annual Local Retirement Benchmark report. That gave local press and AI engines proprietary regional data to cite instead of recycling the same national statistics every other firm references.
From week eight on, we tracked a fixed set of 26 regional retirement-planning queries weekly across ChatGPT, Perplexity, and Google AI Overviews, watching which source won each one and why. Financial queries shift less dramatically week to week than crisis-driven categories, but credential and authorship signals mattered more here than almost anywhere else we track.
The Results
Eight months in, the firm's content is now cited on 17 of the 26 regional retirement queries we track - a 65% citation share, up from under 10% before the engagement started. On several of the most specific queries, the ones referencing this metro area by name, the firm's guides are the only locally specific source AI Overviews have to pull from.
Qualified consultation requests grew 2.9x over the engagement period, and this category of organic, AI-influenced traffic now accounts for 44% of new assets-under-management leads, up from a small fraction of pipeline before the content rebuild. The firm's advisors also report that prospects increasingly arrive at a first meeting already familiar with the firm's specific planning philosophy, having read it first inside an AI-generated answer.
We'd spent years building real expertise for people retiring in this specific market. Once that showed up in writing with our names attached to it, AI engines finally had a reason to point here instead of a generic finance blog.
Citation Strategy
Driving Digital Growth with Innovation & Strategy
Search Visibility Engineering for the AI era. We help businesses become discoverable across every platform where modern buyers search.