Solutions / SaaS and software
Buyers and internal champions increasingly shortlist vendors after conversations with large language model assistants. Those answers favor a small set of vendors and often summarize positioning you did not author. Kelsey operationalizes how often your product and named alternatives appear for the same controlled evaluation prompts.
Product marketing, demand generation, competitive intelligence, and sales enablement share one dated source of truth instead of ad hoc threads and static exports.
Rankings and paid traffic do not explain which vendors assistants treat as default answers.
Category ownership
Track definitional and "best of" prompts where analysts and operators form their initial vendor set.
Competitive displacement
Surface when legacy incumbents or well funded challengers begin to dominate the same language your win stories depend on.
Regional and segment nuance
Run parallel libraries for North America, EMEA, and regulated industries without duplicating manual research in each theater.
Typical owners inside mid market and enterprise B2B SaaS organizations.
Validate whether new messaging, analyst relations outcomes, and launch moments change how assistants describe your differentiation versus adjacent categories.
Prioritize campaigns and events in metros and verticals where assistant answers still omit your brand despite strong organic performance elsewhere.
Maintain a living library of assistant narratives tied to named competitors, including which proof points and certifications models repeat.
Arm enterprise AEs and SCs with dated examples of assistant positioning before high stakes proof of value cycles and RFP stages.
Define the prompt library
Align on evaluation, migration, security, and industry vertical prompts with product and sales leadership, then version the library the same way you version sales plays.
Run on a fixed cadence
Weekly or monthly runs across ChatGPT, Perplexity, and Gemini produce comparable time series for leadership reviews.
Route insights into existing rituals
Feed outputs into QBRs, pipeline council, and launch retros without creating a parallel reporting stack.
Illustrative language only. Replace vendor and category names with your own product, competitors, integrations, and compliance frameworks.
Kelsey executes your library against ChatGPT, Perplexity, and Gemini so product and GTM leaders compare behavior on the assistants buyers already use side by side with web search.
Treat assistant recommendations as a measurable channel, not anecdote.
Start with the twenty prompts your executive staff already debates. Expand into vertical and regional matrices as the program matures.
AI answer tracking, competitor intelligence, Reddit and opportunity surfaces, and Google presence monitoring are described in the consolidated feature catalog.