Tynker Chief Marketing and Growth Officer Lomit Patel on Building Smarter, Faster Growth Engines for Mobile Apps

Growth marketing veteran Lomit Patel has spent over 20 years scaling apps across consumer tech, gaming, and education. Currently the Chief Growth Officer at Tynker (a leading kids coding platform), and author of Lean AI, Patel recently shared some hard-won insights for app marketers with Bidease. The conversation centers around mobile growth, where he touched on everything from user segmentation to balancing brand and performance campaigns, improving retention, and leveraging automation.

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Watch the full interview below, or read on for a selection of key takeaways.

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Key Takeaways

• Focus on your users and experiment continually. Understand your ideal customer deeply and run rapid experiments to find what works.
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• Segment your audience and personalize messaging. Tailor your product experience and marketing messages to each segment to maximize engagement and conversion.
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• Balance performance with brand marketing. Invest in brand-building to create trust and organic demand, so your funnel stays full even as ads get pricier.
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• Treat user retention as a core product priority from day one. Design an onboarding process that delivers an immediate “aha” moment and keeps users hooked in the first week, rather than depending only on CRM emails.
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• Leverage machine learning to optimize campaigns and user value in real time. Automate modeling, targeting, and personalization where possible to work smarter and react faster than any manual effort could.

Focus on Customer Insights and Rapid Experimentation

Lomit Patel has led growth teams in industries ranging from social apps to edtech, and he observes that certain principles remain constant. No matter what type of app you have, success begins with truly knowing your users and continually testing new ideas. Building a growth strategy on these fundamentals creates a strong foundation before you worry about channels or tactics.

“[Have] a deep understanding of your customers, really hone in on the ideal customer profile… The other part is having the mindset of doing a lot of rapid experimentation, because you have to continuously test, learn, and iterate. And most importantly, be data-informed in how you make decisions instead of relying on your gut. Regardless of the company, it's all about understanding the user journey from how people come in at the top, how to engage in the mid funnel, and how they're retained at the bottom funnel. It comes down to figuring out how much friction you want to keep or remove in that process, and that varies depending on the business.”

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This focus on customer insight and experimentation is a hallmark of high-growth apps. Dating.com employed such a strategy in 2020, when the pandemic caused a surge in interest in online dating apps. The team used machine learning and committed to understanding user preferences. By rapidly testing ideas and iterating based on data, Dating.com maintained an edge in user experience, which helped lift key metrics across the board, including cutting CPI by 93%. 

Tailor Your Approach with Segmentation

Not all users are alike, and treating them as a monolith limits growth. Patel stresses the importance of segmentation: identifying distinct user personas or cohorts and crafting experiences to match each one. At Tynker, his team markets to kids, parents, and educators, and each audience requires a different message. Effective segmentation ensures every user sees value in terms that resonate with them.

“For Tynker, we target three different personas of users: We have parents, we have educators, and we have kids. For parents, it's about emphasizing the things that matter to them, which is giving their kids the skills and mindset to succeed in the future of work. For educators, it's about highlighting how the product aligns with STEM curriculum standards in their state, giving them reassurance. And for kids, they don't care about that stuff; they want things to be fun. So it's about emphasizing the gamified approach of how learning to code can be fun.“

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Real-world app marketing is full of examples where segmentation pays off. For instance, the shopping app Joom used data-driven segmentation to target and convert high-value users. Joom used real-time data to optimize deployments across ad formats, delivering highly relevant creative to ideal users. As a result, Joom drove 140,000 new installs, greatly expanding the active user base. When you speak directly to what each user cares about, they’re far more likely to listen and respond.

Balance Brand and Performance Marketing

Marketers often specialize in either performance marketing or brand marketing. Patel has learned that long-term growth requires blending both approaches. In the privacy-first era, where tracking is harder, a strong brand is becoming an essential growth engine. Performance ads alone can’t sustain momentum if you ignore brand trust and recognition.

“What you realize, if you spend enough time in marketing, is that there has to be a balance between [performance and brand]. It's not about one being better, but about coexistence. The more I've come to appreciate this, with today's attribution challenges on iOS and browsers, is that ultimately brand becomes your moat. If you focus on building a compelling brand that people trust, it differentiates you and keeps a consistent flow of new users coming into the top of the funnel. But if you only focus on performance, that top of funnel will eventually dry up, because you're targeting a much smaller well of users long term.”

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Language-learning app Duolingo invested heavily in brand marketing through its playful TikTok presence, essentially becoming a cultural meme. Duolingo subsequently tripled its user base from about 40 million MAUs in 2021 to over 116 million today, while dramatically increasing engagement. That surge was largely organic, fueled by brand-driven content that kept Duolingo in users’ minds. Ads might have missed Duolingo’s target market, but their recognizable, trusted brand continuously brought in new audiences and served as a buffer to harmful algorithm changes. 

Make Retention Product-Led from Day One

When it comes to user retention, many companies make the mistake of handing it off to the CRM or marketing team as a separate task. Patel argues that retention is won or lost through the product experience itself, especially during onboarding. Emails and push notifications can help nudge users, but they cannot save a product that fails to hook people early. The key is to deliver value from the very first session so that users stick around naturally.

“The best way to improve retention is with a product-led initiative, because ultimately, people come for the product. Retention starts from day zero. It's not day thirty; day zero is the first-time user experience, and you want to get the user to that ‘aha’ moment as quickly as possible so they see value. Then have a repeatable process so they keep seeing value within the first seven days. If they fall in love with the product in the first week, your retention rate will be much better.”

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The importance of a strong Day 0–Day 7 experience is backed by well-known examples. Facebook, for instance, discovered that new users who added at least 7 friends in their first 10 days were far more likely to become long-term active users. This insight led Facebook to laser-focus its onboarding on connecting new users with friends, thereby dramatically improving retention and propelling growth to a billion users. 

Leverage AI and Automation to Scale Growth

With user acquisition getting more complex, machine learning can crunch data and optimize campaigns far faster than manual analysis. From modeling customer lifetime value to automating campaign management and personalization, smart use of AI lets marketers react in real time and focus on strategy rather than just number-crunching.

“You have to create a dynamic, fluid model for how you measure lifetime value, because it changes with different businesses, seasonality, and channels — even macro factors. Before, we used to build these models and re-evaluate them every quarter, and I don't think that's good enough anymore. But now with AI, you can build machine learning models around this and start looking at it more frequently, whether it's monthly or even weekly. I think that's important, because it gives you more confidence in your payback periods and your LTVs.”

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Mobile game developer Bagelcode used an AI-driven segmentation tool to automatically identify dormant players who were likely high-value, then targeted them with win-back offers. The result was a 33% boost in ARPU from those re-engaged players. AI systems can uncover patterns and micro-segments that humans might miss, ensuring the right users get the right message at the right time. Similarly, AI-powered advertising platforms now adjust bids, creatives, and budgets on the fly based on performance data, which vastly improves efficiency. 

Stay Ahead of the Curve

Patel’s Successful app growth in 2025 requires both high-level strategy and tactical finesse. Marketers need to ground themselves in fundamentals: Know your users, segment and personalize, balance your acquisition approach, and never neglect the product experience, while also leveraging new tools like AI to work smarter. The common thread in Patel’s advice is integration: growth happens when all parts of the business work in concert toward delighting the user. To learn more about Patel’s philosophy, check out his book Lean AI.

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If you want to learn more about what’s next for mobile growth, download Bidease’s 2025 State of Mobile App Growth Survey. Get it here.

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