Industry

Regulation Technology (RegTech)

Client

Questtor

QHSE Compliance Tool

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Strong Early Adoption, but Poor Retention Beyond Beta

Questtor - an early-stage startup using LLM technology to automate Quality, Health, Safety, Environment (QHSE) compliance - had successfully beta-tested its MVP with over 40 users but struggled to convert them into paying customers. Through LinkedIn outreach, the team was able to consistently find early adopters, using prior experience with AI tools like ChatGPT for documentation analysis and generation as a strong qualification signal. This approach delivered an average of four demos per week over three months, requiring only around two hours of outreach per demo booked. Conversion from demo to active beta tester was healthy at roughly 50%. However, despite strong initial interest, users disengaged after a small number of sessions and reverted to existing workflows - most commonly using ChatGPT.

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Repositioning the Product Around Certainty, Not Speed

The core issue was differentiation. While users were drawn to Questtor because ChatGPT lacked reliability and accuracy for QHSE work, Questtor was only marginally better on these dimensions while being noticeably slower. Attempting to optimise for speed, accuracy, and reliability simultaneously was slowing development and diluting the product’s value proposition. The solution was a clear strategic shift: Questtor would not compete with ChatGPT on speed. Instead, the product was redesigned around certainty and trust. Users could upload a document, leave the analysis running for as long as needed, and be notified when results were ready. The mental model was explicit - if you want fast, approximate answers, use ChatGPT; if you need confidence and defensibility, use Questtor. This reframing aligned the product with its strongest user motivation and created a clear reason to switch and stay.