Vectorly
Vectorly now appears in 38% of recommendation-stage prompts in their category — up from 4%.
Illustrative example based on a composite of client engagements. Figures are representative, not a named client result.
The challenge in detail
Vectorly ranked in the top three organically for every head term in its category and converted well from search. In AI answers it barely existed. A 200-prompt panel run across six assistants returned a 4% mention rate on recommendation-stage questions, and in the few answers where the brand did appear it was characterised generically — listed as an option with no stated reason to choose it. Competitors with a fraction of the organic traffic were being named first, consistently.
Diagnosis
Three root causes. First, entity ambiguity: the company name collided with an unrelated open-source project, and public records described the product with three different category labels. Second, no independent corroboration of differentiators — every specific claim traced back to Vectorly's own marketing pages, which models discount. Third, no comparison surface: buyers asked constrained comparison questions and the only sources available to answer them were competitor-authored roundups.
What we did
We rebuilt the entity graph, reconciled public structured records so that every source agreed on what the product is and who it serves, and resolved the naming collision through disambiguation. We then built an honest comparison surface — including explicit statements of where Vectorly is not the right fit — and refactored the top twenty existing pages to a direct-answer, extractable structure. In parallel, an authority program targeted the specific third-party domains that appeared in citations for the prompt panel.
Results and timeline
Entity and readability work moved the mention rate from 4% to 19% within the first quarter as models stopped hedging. The comparison surface and authority work carried it to 38% by the end of the third quarter, with the brand named in the first three positions in a majority of shortlist answers. Citation share of Vectorly's own domain rose from near zero to roughly one in five answers.
“We went from invisible on Perplexity and Gemini to consistently being one of the three names recommended.”
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