The Mobile User Acquisition Show podcast

👣 Winning Q1: Maximizing Post-Holiday Subscription App Growth with John Koetsier VP of Insights at Singular, Ekaterina Gamsriegler, Head of Growth and Marketing at MIMO, David Barnard, Growth Advocate at RevenueCat and Virendra Shekhawat, Head of Mobile M

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🚀 We’re excited to share insights from our latest webinar "Winning Q1: Maximizing Post-Holiday Subscription App Growth" with Singular and Revenue Cat! 🌟 

We dove into strategies for leveraging the dip in CPMs post-Christmas to fuel subscription app growth. đŸ“‰âžĄïžđŸ“ˆ Key takeaways include the importance of scaling marketing efforts in January, leveraging low CPMs for higher conversion rates, and maintaining user motivation to combat the mid-January motivation drop. đŸ‹ïžâ€â™‚ïžđŸ’Ą

We also explored trends across various app categories, revealing insights on consumer behavior and effective marketing channels. 📊🔍 From the resurgence of Black Hat ASO tactics to the creative use of hybrid monetization models, we covered it all. đŸŽ©đŸ’°

Special thanks to our superstar panelists for their invaluable insights and strategies for thriving in Q1. 🌟

Check out the show notes here: https://mobileuseracquisitionshow.com/episode/webinar-q1-subscription-app-growth/

KEY HIGHLIGHTS:
👟 Leverage the post-holiday dip in CPMs to scale marketing efforts efficiently.

đŸ‡đŸœ Utilize January’s low CPMs and high conversion rates for growth.

đŸŽ€ Adapt strategies to maintain user motivation and reduce churn.

🎳 Explore various channels, including TikTok and SDK networks, for diversification.

🎯 Embrace hybrid monetization models to enhance revenue streams.

đŸŽ» Utilize AI and generative tools for efficient creative production and testing.

🚀 Monitor and adapt to changing CPM trends and user behavior post-Christmas.

⛱ Experiment with non-digital marketing channels for localized targeting.

🧭 Prepare for privacy changes and the adoption of SKAN 4.0 and Google’s Privacy Sandbox.

🔧 Utilize blended metrics and hybrid measurement for more accurate performance analysis.

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