Finding love in the
age of TikTok
Dating is evolving. Gone are the days of simply uploading a photo and hoping for the best. Today’s daters are exhausted by endless swiping, shallow profiles, and hookup culture. Instead, they’re seeking deeper connections, authenticity, and a more intentional approach.
As a legacy brand, Tinder thrives on what has made it successful for so long, so we needed to approach change with care, balancing innovation with sensitivity to its core strengths.
Over an 8-week period, I collaborated with stakeholders to identify key challenges, brainstorm 100 potential solutions, and test the top 35 concepts with at least 50 users each. The final product vision distills these findings into actionable insights, achievable within 1–2 quarters.
Where do we start?
Tinder is experiencing rapid shifts in consumer preferences, resulting in a significant decline in monthly active users (MAU). Years of research and observation have shown that women are the primary drivers of this metric, yet many feel Tinder isn’t delivering the experience they need. With so many challenges in building a dating app, the question is: where do you start?
I started with survey data from a 2024 study that gathered insights from 10,000 users. By focusing on our target demographic—Gen Z women—this data provided the foundation to ask the right questions and define a clear path forward.
What is important to daters today?
Dating is constantly evolving, and a new generation of daters brings a fresh perspective. Instead of making assumptions about their experiences, we decided to ask them directly. We started with key questions to deepen our understanding and reached out to as many people as possible. These hypotheses served as a valuable foundation, sparking meaningful discussions and inspiring new ideas.
Leveraging the language of TikTok
With a small team of three and a tight 8-week timeline, a traditional moderated interview structure couldn’t deliver the volume needed to make a compelling case to the board. To address this, I implemented a more scalable approach: creating short, TikTok-style videos (a format our users love) and asking users to respond by providing a rating, ranking concepts, and answering a few open-ended questions. This allowed us to efficiently gather valuable feedback on each idea.
Leveraging the Equal odds rule at scale
The equal odds rule is a cornerstone of creative problem-solving, suggesting that to uncover a truly great idea, you must first explore many. Guided by this principle, we cast a wide net, generating a broad range of ideas. Each hypothesis was paired with a concept video and tested with around 50 users to identify which concepts warranted further iteration and exploration.
Each experiment gave us a better understanding of the problem
You never truly know how a concept will perform until you put it in front of users. With that mindset, we let users guide us, openly sharing what they liked—and what they didn’t. Here’s an example of one experiment from the user’s perspective. This particular concept performed well and provides insight into their responses. After answering open-ended questions, users rated the concept on a scale from 0–10 and completed a stack ranking to order their favorites from most to least.
The experiment results
This 5-minute compilation is a small sample of over 10 hours of unmoderated interviews. Initially, the results were surprising, with users showing a clear preference for features like search, personality cards, and dating games. But when we stepped back and analyzed the full dataset, the pattern became clear: users come to Tinder with one goal—to find people. Features that didn’t directly support that purpose were dismissed as unnecessary or gimmicky. Instead of adding more features, the focus should be on optimizing every pixel to enhance the core purpose: matching.
Measuring the experiments
The process for measuring these experiments was grounded in techniques inspired by Student’s theorem. For each concept, users rated it from 0–10 based on how likely it would make them to use Tinder. Afterward, they stack-ranked the full collection of concepts. These rankings were combined and normalized, giving each concept a score between 0 and 1.
As we gathered more data, the confidence interval narrowed, with high-performing concepts consistently scoring higher and low-performing ones scoring lower. Given the cost and diminishing returns of additional data collection, we determined that a sample size of 50 users per concept provided sufficient insight for directional learning.
The 10,000ft view
These experiments revealed two key themes with significant implications for Tinder's business.
Efficiency over endless swiping: Users find aimless swiping taxing and unproductive. They’re seeking more efficient features to help them connect with compatible, interesting people.
The need for better information: Dating is time-consuming, awkward, and expensive, making users more selective with their matches. Profiles, particularly for men, are often sparse and unhelpful, leaving users frustrated. On average, it takes a man around 3,000 right swipes to secure a date—a trend moving in the wrong direction. Users demand richer profiles, and our challenge is to deliver depth without adding unnecessary complexity.
Dating with depth, an active approach to dating
This artifact consolidates key insights from the top-performing concepts into a cohesive vision. It highlights two main ideas: users want a more active approach to dating and greater profile depth. Rather than a complete overhaul, we opted for a careful evolution—enhancing the existing Tinder experience while preserving the core elements that have driven its long-standing success.