I'm the Chief Product Officer at Hily dating app which stands for quality communication between singles.
“Speaking of data-driven decisions, dating apps normally don't have a flat retention curve. What are the best solutions to deal with this, from your point of view?” Alexander Snitsarenko, thank you for the question (above) in my previous post. Product managers often obsess over the dreaded flat retention curve. But here's my take: fretting about it isn't always necessary in certain scenarios. Instead of fixating on individual user retention, let's take a broader view. Allow me to elaborate. Consider social media giants like LinkedIn, Facebook, and Instagram, where next-day retention can reach an impressive 95%. On the flip side, apps, particularly dating platforms, can see this figure drop by 15-40 percentage points. In our product strategy, we categorize churn into two distinct types: good and bad. Good churn occurs when a user's needs are met, and they gracefully exit the app. In our case, this means finding a partner and no longer requiring the dating service. Through our research, we've observed that users who experience good churn are more likely to: - Return to the app if their needs change in the future. - Recommend the app to their friends and peers. Interestingly, users introduced to the app through friend recommendations exhibit significantly higher retention rates on the first days of product usage, nearly 30% higher than those acquired through advertising. Thus, even if the specific user retention after fulfilling their needs drops, we can still see they might come back later. Additionally, these users become advocates, attracting more motivated and loyal users to our platform. Conversely, bad churn happens when a user departs without achieving their goal. Several factors contribute to this in dating apps, including: - Audience quality: How well the audience aligns with the user's preferences. - Audience saturation: How many potential matches are in the user's vicinity. - Technical issues in the product Your primary focus should be reducing of bad churn in your app and boosting retention rates for users who haven't yet found what they're seeking. To tackle this challenge, we've introduced innovative solutions, like enabling users to rate their interactions with others using multiple criteria. This valuable data powers our algorithms, enabling us to provide users with more pertinent match recommendations. So, what happens when we increase good churn and reduce bad churn? We witness growth in Daily Active Users (DAU) and retention. We segment our DAU into various categories, including: - New users (from recommendations, search and advertising). - Resurrected users (returning after prior usage, a subset of good churn). - Returning users (active user base). Even if retention of your returning users doesn't skyrocket as you'd hope, but your DAU expands, with an influx of resurrected and new users, it's a remarkable outcome! In such cases, the flat retention curve need not be a cause for excessive concern. Do you concur?
