TINDER
As lead designer on Tinder's Revenue team, I owned design strategy and execution across premium features, paywalls, checkout, and monetization experiments. The first thing I noticed when I got there was how inconsistent it all was. Every upsell looked like it came from a different app.
I treated it as one system instead of a pile of one-offs, redesigning the paywalls and upsell moments and adding new places to sell that still felt like Tinder rather than an interruption. This led to stat significant results and a revenue high for Tinder.
Case study coming soon…
↑ 6.5%
Boost sales
↑ 3%
Subscriptons
GRINDR
I noticed people were already putting hashtags in their bios as a way to say who they were. Nobody had asked them to, and the app did nothing with it, so those signals just sat there instead of helping anyone find each other.
That became My Tags, a way to find people who share your interests. I ran user testing and worked with LGBTQ+ organizations and trust and safety, so the tags would work for everyone. Adoption came fast, as many instantly added tags to their profile.
Case study coming soon…
50%+
1st week
adoption
2-3
Average tags on profile
CHECKMATE
Checkmate only reached shoppers in one place, a widget on checkout pages that many people never noticed. There was nothing to build loyalty around, so people grabbed their discount and never returned.
To solve this, I mapped the full experience and prioritized reaching people at the moments that mattered in their shopping journey. Once someone saved money, I designed a few different ways to encourage them to download the app. From there I built the Checkmate rewards program from scratch: a balance that grows, and earning are surfaced throughout many touch points instead of only at checkout.
Case study coming soon…
↑ 5.9%
Orders completed
3M+
MAU
TINDER
Women kept running into low-quality profiles on Tinder. No photos, short bios, no verification. It made the app feel like work, and engagement and retention dropped.
I led design and user research on Just for You, a feed of curated profiles. Research came first, figuring out what women actually counted as a good profile, and that set what we filtered for. We used machine learning to build the picks, and I designed the feed so it read as a short list worth looking at instead of an endless stack.
↑ 17%
Likes sent by women
↑ 5%
Messages sent by women
GRINDR
Grindr is one of the largest LGBTQ+ communities online, and a lot of people come to it looking for more than a date. At the same time the company was making editorial content, health resources, and community programming, all of it living in separate places where most users never ran into it.
I saw the opening and designed the Community tab, one home in the app for that work, covering both what Grindr was publishing and the health resources people were already searching for. User testing ran throughout so the tab was built on what the community said it needed.
