How A B2B SaaS Platform Increased AI-Cited Brand Mentions By 340% In 90 Days
The platform showed up in AI answers occasionally and unpredictably - never enough to count on, never absent enough to ignore. Ninety days of entity work changed that math entirely.
The Challenge
This mid-market SaaS company had a strange problem to bring to us. Ask ChatGPT about its product category on one day, and the brand might come up third in a list of recommendations. Ask the same question a week later, and it vanished entirely, replaced by two competitors and a directory site. There was no pattern the marketing team could point to - no campaign that reliably moved the needle, no content update that consistently helped. The brand existed in AI answers the way a weak radio signal exists: present, but never something you could plan around.
The underlying issue became clear once we mapped out how the company described itself across the web. Its own site, its G2 profile, its Crunchbase entry, and a handful of press mentions each described the product slightly differently - different category language, inconsistent feature claims, even a stale integration list on one third-party directory that hadn't been updated in over a year. AI models build a working understanding of a brand from exactly this kind of scattered evidence, and when the evidence disagrees with itself, the model has no stable foundation to cite confidently. Inconsistency, more than absence, was the real problem.
The Approach
We catalogued every place online where the company's category, features, and integrations were described - its own site, G2, Crunchbase, its app marketplace listing, and a dozen smaller directories - and flagged every point of disagreement. Several listings hadn't been touched since the product's last major version, which meant AI models researching the brand were pulling in outdated claims alongside current ones.
We implemented SoftwareApplication and Organization schema consistently across the marketing site, synced the canonical feature and integration list across every third-party profile the company controlled, and corrected the outdated directory listings that had been quietly working against the brand's credibility for over a year.
With a consistent entity foundation in place, we ran a focused outreach campaign to place the company in three category-defining comparison roundups on sites AI engines already treat as trustworthy sources, and secured a technical contribution to an integration partner's documentation that linked back with full attribution.
From week four on, we ran a fixed set of category and feature-comparison prompts against ChatGPT and Perplexity twice weekly, tracking not just whether the brand appeared but whether the description attached to it matched the corrected, consistent entity profile we'd put in place.
The Results
By day 90, AI-cited mentions of the brand had grown 340% against the pre-engagement baseline, and just as importantly, the mentions had become consistent - the random disappearance the marketing team used to shrug off stopped happening almost entirely once the underlying entity data agreed with itself everywhere it was checked. Our internal authority-score index, which weights citation frequency, source quality, and description accuracy, rose 58 points over the same period.
The consistency mattered more to the sales team than the raw growth number. Reps reported fewer conversations where a prospect repeated an outdated feature claim or confused the product with an older version, since the AI-sourced information prospects encountered before a call now matched what the company actually offered.
We thought we had a visibility problem. It turned out we had a consistency problem, and once every source agreed with every other source, the visibility took care of itself.
Citation Strategy
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