Reading a market through its own reviews
The complaints merchants had already published about loyalty apps became the personas the team planned against.
Industry
SaaS / E-commerce
Scope of work
Research
Challenge
I could describe our merchants on paper, down to store size and plan tier. None of it explained why one loyalty app gets picked over another.
Or why a store that set the whole thing up in an afternoon never logged back in. Positioning written off that description would have been a guess, and competitor work that stops at feature checklists answers a sales objection and nothing else. I wanted the layer underneath.
Approach
A survey would have taken weeks and come back polite. The category had already been reviewed to death in public, so I went there instead.
I read across the Shopify App Store, Capterra, and Trustpilot, not just our own listing, then coded the reviews by theme. I checked what came out of that against how the category talks about itself in public, across listings and pricing pages and marketing sites. Those themes became personas, each built on a complaint frequent enough to plan around.
Outcome
The research didn’t stay a document. The personas became the shorthand the team used in launch planning.
Every new feature went out with a short positioning brief written off the same base. I stopped having the same argument about who a message was for, because the answer was already on paper. Competitor tracking stuck around too, more habit than process.
