How does Truveris validate new features and drive user engagement for its award-winning app OneRX?

by Mayowa Fadina in Best practices
May 27, 2016

Increasing drug prices are again at the forefront of national attention. Anxiety runs high for those that need to fill prescriptions that once seemed affordable yet continue to take up higher shares of disposable income.

A New York-based health technology company is focused on alleviating much of the pain for consumers. Truveris is the maker of OneRX, an award-winning app that enables patients to look up prescription drug costs and redeem hidden coupons and discounts before they select a pharmacy. Truveris takes an impressively data-driven approach to developing their innovative solution.

truveris team

The VP of Product, Sunil Parekh, has been on the product side of healthcare apps for more than 10 years. To help make OneRX as relevant and easy to use as possible, Sunil and his team regularly reviews industry reports to assess the competitive landscape and user behavior and perceptions of existing solutions. Based on this analysis, the team develops a number of assumptions and ideas for the app.

Substantiating and validating assumptions

Although secondary research was readily available, Parekh’s team struggled to substantiate assumptions with primary research. Their vendor only offered a small number of qualitative interviews in limited geographic regions, and, to make matters worse, the research was slow and expensive.

Parekh’s team turned to Alpha’s platform, which provides them with on-demand access to their niche target of 45-65 year olds who have filled a prescription in the last year. They can also tap into Alpha’s exchange of designers to generate interactive, testable prototypes. The team can now generate user feedback within two days instead of two weeks, and rely on custom primary research in addition to secondary research.

Going from product or feature concept to target user feedback is now a rapid process that has immediately led to increased interactivity across the app. Parekh points to increases in the number of sessions per user, number of medications saved, number of searches, and number of discounts redeemed, all of which lead to higher revenue.

According to Parekh, “Alpha helps us quickly validate assumptions, learn about our target market, and prioritize initiatives on our roadmap.”

Aligning around data

Most product teams regularly debate different directions and feature concepts for their portfolio of products. But instead of sitting in endless meetings doing so, the OneRX team puts their assumptions to the test. Alpha enables the team to rapidly generate user insights and make data-driven decisions.

For consumers, the experience of finding pharmacies with the best prices is often overwhelming. In a recent release, OneRX added the ability to sort pharmacies by price/distance and filter by services offered (e.g., open 24-hours, drive-through option, availability of on-site clinic) and languages spoken.

There was a lot of internal debate for how to best implement this from a UI/UX perspective. They narrowed it down to two options and tested both using Alpha to create interactive prototypes (Variant A and Variant B). They had users complete two tasks to test and validate which experience was more user-friendly.

Case Study (2)

“From the results provided, it was clear that Variant A enabled the majority of users to complete both tasks successfully,” said Parekh. “When we have data like this, internal debate stops. We have an objective measure of which version will be more effective.”

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Mayowa Fadina

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