Fixing Recommendation Gaps and Awareness Issues in Yuka

✳The problem they went after

Yuka users scan food and beauty products and get an ingredient safety rating back, which works. The breakdown comes one step later. When something scores badly, the in-app alternatives turn out not to exist in the stores those users actually shop at. So they buy the poorly rated product anyway or give up on the decision entirely.

✳What they actually did

Interviews with five long-term free-tier users turned up things the researcher was not hunting for: none of them knew the paid subscription existed, all of them struggled to find recommended products locally, and most did not realise supplements go unrated. Survey data backed the core finding that people trust the recommendations but cannot act on them. A meaningful share fill the gap with ChatGPT, Google, and YouTube. The SWOT credits clear ingredient visualisation and ease of use while flagging personalised filtering and paid feature discoverability as weak spots.

✳What you can take from it

The transferable bitLetting interviews reframe the question instead of confirming it is how paywall blindness and unrated supplements showed up in a study about recommendations. The other habit worth stealing: asking where users go when the product fails them, because the workaround tools name the gap more precisely than any complaint does.

✳The problem they went after

Yuka has 77 million users and under 10 percent of them pay, which produced 7 million dollars of revenue in 2024 despite obvious product-market fit. Five interviews and a pass through app store reviews split the shortfall into two causes: most users do not know premium exists, and the ones who do are not convinced it is worth the money.

✳What they actually did

The awareness half traces back to signposting. All five interviewees were unaware of premium, and several asked for features that already ship in the paid tier. Search and filter sit behind the paywall on a path the standard scanning workflow never crosses. Users with dietary restrictions and allergies come out as the best conversion target because their free experience is genuinely broken. The fixes lean on visibility over pressure: a premium section in the options menu, a limited free search bar on the history screen that prompts an upgrade on new-product searches, and contextual modals at feature launch.

✳What you can take from it

The transferable bitA monetisation number gets treated as a discovery problem, which changes the solution set from pricing and promotion to placement. The segment choice is worth noting too: the target is picked because their current experience is actively broken, not because the group is large, and RICE then favours the cheapest high-confidence starting points.

✳Everything else they shared