People also ask
In practice
An AI product enters a market where the usual infrastructure — the established review sites, the mature comparison roundups, the decades of category coverage — may not exist yet, and where the buyers are precisely the people who ask ChatGPT or Perplexity for recommendations. That shifts the campaign’s centre of gravity. Coverage formation matters more than coverage harvesting: the early mention footprint — the newsletters, practitioner blogs and new comparison pages forming around the category — defines what engines and buyers will believe the product is, so placements there carry weight out of proportion to the publishers’ metrics.
Consistency carries unusual load: if the market cannot yet describe the product, every placement is also a definition, and five conflicting descriptions become the permanent record engines reconcile. The placement set looks familiar — insertions into the emerging roundups, guest posts establishing the product’s point of view, mentions where the category’s conversations happen — but target selection weighs “where will this category’s canon form” over “where is the biggest DR today”. Founder-led material and first-party data (usage benchmarks, pricing surveys, methodology write-ups) give publishers something to cover and give engines something citable.
The honesty constraints hold: new categories mean no guaranteed inclusion in AI answers, tracking instead of promises, and patience with a citation layer that updates on the engines’ schedule rather than the campaign’s.
See also: Link building for SaaS, Category creation and new-market mentions, AI answer engines.
