Mobile App Monetisation: Choosing the Right Pricing Model

Most founders get monetisation backwards. They choose a pricing model first, then try to make their product fit. Like in fishing, it’s important to first ‘hook’ the user before shaking them for a hefty subscription. The smartest founders understand their users deeply, then design monetisation around actual behaviour patterns.

With over 2 million apps competing for attention, choosing the right pricing strategy often determines whether users discover, adopt, and stick with your app. The wrong model can kill even the best apps, while the right one can turn modest traction into explosive growth.

Let’s take for example the new wave of ‘AI Apps’. AI-native apps face a unique economic reality: costs scale directly with user engagement. An AI writing assistant might cost $0.02 to $0.10 per request. With 1,000 daily active users making 50 requests each, you’re looking at $1,000 to $5,000 in daily API costs.

The most successful AI apps use hybrid models—base subscription with usage limits, then pay-per-use beyond that. This keeps pricing predictable for users while aligning costs with value. Consider value-based pricing: charge $10 per video generated rather than $0.10 per API call.

In this post I’ll dive into the various monetisation strategies for mobile apps and offer practical advice for choosing the right model. As for the pricing, that’s a whole topic on its own that requires experiments.

The Complete Model Breakdown

Which Model is Right for You?

The right monetisation model depends on three core factors: user behavior patterns, value delivery timeline, and your cost structure.

Start with user intent and frequency. Daily-use apps with high engagement can support subscriptions, but only after proving sticky usage patterns. Apps used sporadically work better with pay-per-use or one-time purchase models. Social and entertainment apps often thrive with freemium approaches that let engagement drive monetisation naturally.

Consider your value delivery timeline. Apps that deliver immediate, visible value can charge upfront. Photo editors, professional tools, and games often work this way. Apps that require time to demonstrate impact—like habit trackers, learning tools, or productivity apps—need freemium models that let users experience value before paying.

Factor in your cost structure. AI-native apps with variable API costs need usage-aligned pricing. Traditional apps with fixed infrastructure costs have more flexibility. If your per-user costs exceed $5 monthly, consider usage-based models from day one.

If you’re building…

• Social/Content App: Start Free ? Add Premium Features
• Productivity Tool: Freemium ? Subscription (after proving daily use)
• AI/ML App: Pay-per-use or Credits + Subscription hybrid
• Game: Free-to-play + IAP (focus on retention first)
• Professional Tool: Free trial ? One-time or Annual subscription
• Marketplace/Platform: Free for users ? Commission from transactions

Common Mistakes to Avoid

The biggest monetisation killer is introducing subscriptions before proving users return three or more times per week. Ninety percent of founders do this because subscriptions feel like “real” business models, but they’re the hardest to make work.

Underpricing is equally deadly. Founders typically price their apps 3-5 times less than their actual value because they fear users won’t pay. This becomes self-fulfilling—users perceive low-priced products as low-value.

For AI apps specifically, ignoring unit economics is startup suicide. If you don’t understand your true per-user costs including API usage, you can’t price appropriately. Many AI startups fail not because users don’t love their products, but because they gave away too much value too cheaply.

Avoid these at your peril:

1. Subscription Too Early: 90% of founders introduce subscriptions before proving daily/weekly usage
2. Underpricing: Afraid to charge what the value is worth (usually 3-5x too low)
3. Single Model Lock-in: Not experimenting with hybrid approaches
4. Ignoring Unit Economics: Not calculating true per-user costs (especially AI apps)
5. Copy-Paste Pricing: Using competitor prices without understanding their metrics

Tips for getting mobile monetisation right from the start

Start with user behavior, not pricing theory. In your first few months, focus entirely on retention and engagement. Implement analytics that track how often users return, how long they stay, and which features they adopt.

Once you understand patterns, experiment with light monetisation. A/B test different approaches with different user cohorts. Build flexibility into your payment infrastructure from the beginning—it’s harder to change than features.

Your first monetisation model won’t be your final one. The best strategies evolve with user understanding and feel inevitable to users—they align so naturally with usage patterns that users would choose them independently.

At Remagine Ventures, we partner with founders who understand that monetisation is product strategy. If you’re building something users love and want to optimise how they pay for it, we’d love to discuss your approach.

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Eze Vidra

Co Founder and Managing Partner at Remagine Ventures

Eze is managing partner of Remagine Ventures, a seed fund investing in ambitious founders at the intersection of tech, entertainment, gaming and commerce with a spotlight on Israel.

I'm a former general partner at google ventures, head of Google for Entrepreneurs in Europe and founding head of Campus London, Google's first physical hub for startups.

I'm also the founder of Techbikers, a non-profit bringing together the startup ecosystem on cycling challenges in support of Room to Read. Since inception in 2012 we've built 11 schools and 50 libraries in the developing world.

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