A leading conversational AI platform provider had spent years selling chatbots and virtual assistants to large enterprises and had extended its platform into generative AI. By 2024 enterprise buyers were choosing generative AI platforms in a crowded field of hyperscalers, model providers and specialist vendors, and the company was losing evaluations it believed it should win. Sales feedback explained individual losses but not the pattern. The company wanted a fatal-flaw assessment from the market itself: a direct, quantified reading of how enterprise decision makers select generative AI platforms, where its own offering fell short in their eyes, what non-customers actually knew about it, and what would make those buyers reconsider.
PP&A designed the study as a voice-of-customer survey aimed deliberately at non-customers and at buyers who had evaluated the client and chosen another platform. PP&A wrote the questionnaire, which covered the models and tools respondents used, their top selection criteria, their generative AI use cases and priorities, the importance of enterprise search, their experience of the client, the steps they took to evaluate competing offerings, their reasons for not selecting the client, their view of its security and compliance posture, their trial and support experience, and open-ended questions on what would make them reconsider and which features they wanted to see.
The survey ran online over one week in late September 2024 and returned 64 completed responses from directors, vice presidents and C-level executives at large US companies actively using generative AI, most of them sole or joint decision makers on the purchase. PP&A analyzed the results by respondent segment, comparing buyers who had evaluated and rejected the client with those who had never evaluated it, coded the open-ended answers into primary and secondary themes, and delivered the findings as a report on the state of enterprise generative AI, market perceptions of the client and a set of final takeaways.
The report gave the client a reading of its market position from the buyers it had not won. The first part set out how enterprise decision makers choose generative AI platforms: the providers they already use, the criteria that decide a selection, the use cases they prioritize and the weight they place on enterprise search. The second turned to the client: how familiar non-customers were with its generative AI offering, how buyers researched competing platforms, how those who evaluated the client judged it, why they chose another provider, and what would bring them back.
Comparing buyers who had rejected the client with those who had never evaluated it helped separate gaps in awareness from gaps in the product. PP&A's final takeaways ranked the flaws by priority and gave the client an ordered agenda for closing them.
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