The 3 principles fueling Hinge’s growth, according to its CEO

As many dating apps have been losing users and reshaping their strategies, Hinge has emerged as a brand to beat.

In the second quarter of this year, Bumble’s paying user base was down 8.7% year over year and revenue dropped 7.6%. Tinder, which is owned by Hinge parent company Match Group, has lost 1.2 million paid users since the beginning of 2024 and saw revenues drop 4.6% in Q2 2025. Meanwhile Hinge notched a 25% year-over-year increase in revenue and 18% growth in paying users for the quarter.

The secret, according to cofounder and CEO Justin McLeod, speaking at the Fast Company Innovation Festival, are two principles that have guided the company since its early days—and one that is emerging alongside broader use of AI. They are:

Prioritize the free experience

Long before Cory Doctorow coined the term enshittification in 2022 to describe the process by which once-useful online platforms slowly get less user-friendly as they attempt to improve their bottom line, daters on apps had experienced it firsthand. Many apps have added monetization strategies that seem at odds with the goal of connecting singles: They push users to paid versions by degrading the free experience.

McLeod said Hinge is different because it actually wants to live up to its “designed to be deleted” tagline.

“It is absolutely in our best interest to keep the free product experience very good, because if it’s not, users will start leaving,” McLeod said. “And the primary value for a dating app is the other people who are on the product. No one will continue to pay if there aren’t lots of people on the app who are happy and satisfied using it.”

Hinge is also selling premium tools, including the ability to filter potential dates based on things like height and political preferences, plus features like Roses (which users can send to express extra interest) and Boosts (which allow someone’s profile to be seen by more people for a limited amount of time). The trick, McLeod said, is being strategic by charging for features that aren’t necessary but that nevertheless improve the experience for people who are willing to pay for them. 

“What we charge for is basically things that we can’t give away for free, things that are valuable because they’re scarce,” he said. “If you had unlimited Roses, then they wouldn’t mean anything. If everyone is showing up more [via profile Boosts], nobody is showing up. 

Build for underserved users

One of the newer features McLeod outlined is Match Note, which was built with LGBTQ+ and neurodivergent users in mind. Launched in February, it allows users to disclose certain information with matches before chatting—details that some might not want to put in a public profile, such as their gender identity or communication style. It’s a way for them to avoid “hard, awkward conversation with every single person after you match,” McLeod said, noting that Hinge worked with organizations TransTech Social and Disability:IN.

“It was designed for [these groups] but we’ve actually found that single parents use it, people with STIs use it,” McLeod said. “All kinds of different people will use this feature, which just increases the general usability and accessibility of the app for everybody.” 

Make AI features useful

Though McLeod noted that machine learning has underpinned Hinge’s algorithm since it launched, he said the company has more recently been using generative AI strategically to improve users’ profiles and how they communicate with others. 

The new Prompt Feedback feature encourages users to answer profile prompts more fully, preventing short answers that might be unhelpful to potential matches. “It doesn’t necessarily cut generationally,” McLeod explained. “But certainly some people, especially in the realm of social media, have atrophied social skills and need a bit more help showing up and connecting with other people.”

He said Hinge also uses generative AI to help users choose the best photos, and it employs AI for a feature called “Are you sure?” that double-checks with a user before sending a message that might not be well-received. “There are a lot of what we call accidental bad actors, who aren’t quite contextually aware of what’s an inappropriate thing to send at this stage in the conversation,” he said. “We can help nudge them in the right direction.”

McLeod said that down the road he sees AI leading to much more personalized matches: “Three to five years from now—sooner, honestly—it will feel relatively arcane that you had to go through hundreds of profiles in order to get out on a date.”