Extensive Data in Google Sheets (Edit)

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Overview

• Hinge is growing monthly active users (MAUs) rapidly (20% in H1 2025) while Tinder MAUs are declining at around 9% (Q2 2025).
• Tinder, which generated $1.9 billion (+1.2%) in revenue in 2024 (55.8% of total Match group revenue), had around 47 million MAUs (June 2024) and 8.98 million payers as of Q2 2025: ‣
• Hinge, which generated $550 million (+38.8%) in revenue in 2024 (15.8% of total revenue), has around 15 million MAUs (September 2025 commentary) and 1.75 million payers as of Q2 2025: ‣ </aside>

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Investor Takeaway

• Tinder remains in structural decline (around –9% MAUs, with risk of further downside if bots are removed), while Hinge is the clear growth engine (+20% MAUs). User sentiment toward Tinder is increasingly negative, whereas Hinge’s perception is mixed but skewing positive. Management’s recent claims of improving Tinder engagement has low credibility since they have been wrong before (Q3 and Q4 2024). </aside>

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Prediction

• Aron: Probably a 9%-10% y/y decline in Tinder MAUs on a continued basis. The decline could even accelerate if Match Group decides to reduce fake profiles/bots like it did in Q4 2023.
• Aron: Probably a 15%+ y/y growth in Hinge’s MAUs in the medium-term.
• Aron: Probably at least 20% of Tinder’s MAUs are bots. Insights on bots/fake profiles (FTC case) </aside>

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Competitive ranking

• MAUs comparisons </aside>

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Key Growth Drivers

• According to Goldman Sachs (citing industry data for Q3 2025), Tinder has began seeing improvement in international user trends: https://forum.investmentwiki.org/t/match-group-analysts-opinions/521/7?u=aron
• Google search trends (Sheets) and Appmagic app popularity insights (row 193) suggest Tinder downloads have been relatively stable this year : ‣
• Sensor Tower data (row 45) indicates that the share of Gen Z users in Tinder and Hinge improved in H1 2025 by 3% to 4% due to new features: ‣
• Hinge is growing users rapidly: MAUs rose 20% y/y in H1 2025 (row 14): ‣
• Reports that the new Face Check feature that is slowing being rolled out in regions is hard to bypass, helping reduce bots in the platform: Insights on Face Check feature </aside>

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Key Downsides

• Tinder MAUs showed no much improvement in Q2 2025: MAUs declined 8–9% year-over-year according to management, broadly unchanged from the 9% decline seen in each of the past five quarters (row 12): ‣

• Management’s Q2 2025 commentary on improving MAU trends at Tinder are to be taken with a grain of salt since they were wrong in Q4 2024 and Q3 2024.

  • Q2 2025 Management commentaries on Tinder user numbers
  • Accuracy of management’s commentary on Tinder MAU trends

• Reviews on Tinder are largely negative, with most users flagging increased fake profiles/bots and algorithm that seems to work only when you are a free user but stops after paying.

  • Recent reviews

• Large number of fake profiles in Tinder inflates the MAUs: A judge said in 2021 (citing anonymous witness) that 20% of accounts in Tinder are fake. Similarly, dating surveys (row 244) indicate users are concerned about encountering bots on dating apps.

  • Insights on bots/fake profiles (FTC case)

• Tinder’s Face Check feature that is being rolled out across regions (so far available in India, Canada, California (USA), Australia and Columbia) will likely be a headwind on monthly active users in the near-term. Some reviews say the feature is buggy and Tinder bans your profile if you don’t pass the photo and video verification.

  • Insights on Face Check feature

• More than 50% of Tinder MAUs (around 20M) come from low-monetizing regions (as per Sensor Tower, row 39). Match Group’s average revenue per payer in APAC& Other regions is about 30% lower than that of US and about 20% lower than that of Europe:

  • User monetization

• There are several Gen Z pain points when it comes to dating apps including lack of authenticity, fear of rejection, safety, etc. Solving these pain points might take time.

  • Gen Z take on dating apps </aside>

• Important notes on the data above

• More notes

Related Task: ‣

Related Decision: ‣