Tara Meyer
LTV Prediction or Predicted Lifetime Value (pLTV) is a metric that forecasts how much revenue a user will generate throughout their entire lifetime, or relationship, with your app.
Unlike traditional LTV, which relies on historical data that can take 30-90 days to fully materialize, LTV prediction (pLTV) delivers actionable forecasts within hours. Our pLTV combines historical patterns and learnings with current behavioral signals to deliver actionable forecasts immediately. It means you can act sooner, optimizing across campaigns and channels when it’s prime time.
To understand how it impacts your measurement and optimization strategy, let’s break down the fundamentals:
- What does traditional LTV measure?
- Why traditional LTV timing fails hybrid monetization apps
- How LTV prediction solves the timing problem
- Why most pLTV solutions fall short
- How LTV prediction is calculated at Tenjin
What does traditional LTV measure?
Lifetime value or LTV is the revenue generated by a user either during their entire lifetime, or within a defined time span. It’s a cohort metric that helps you understand the total monetary value each user brings to the business over their lifetime as a customer.
Why traditional LTV timing fails hybrid monetization apps
For apps with hybrid monetization models, traditional LTV measurement has an inherent timing problem. Here’s the disconnect:
- In-app advertising (IAA) revenue materializes within hours.
- In-app purchase (IAP) revenue takes 30-90 days to fully develop
This timing mismatch carries two main consequences:
- Delayed decision-making
You’re missing out on adjusting campaigns when they matter most. Within hours you may have IAA signals but little IAP insight, which can be half or more of the value. - Suboptimal budget allocation
Without a comprehensive understanding of value, you’re spreading resources inefficiently across channels. You might be over-investing in campaigns that look good on IAA alone, or under-investing in channels that drive high-value IAP users.
Since traditional LTV measurement could force you to wait months for holistic data, it creates a massive data lag and lost chances. By the time you have the data to understand true user value, most budgets have been spent and most opportunities missed.
How LTV prediction (pLTV) solves the timing problem
This is where pLTV becomes essential, since it eliminates the timing gap entirely. Instead of waiting for revenue to fully materialize, predictive modeling leverages existing data and machine learning to compress decision cycles from weeks to days.
Most pLTV solutions start forecasting around day 2-7. That’s a good improvement.
Our pLTV calculation starts on day-0.
That means, the moment a user installs, you have predictive intelligence in hand that enables real-time optimization before the traditional measurement even begins. Receiving data quicker = more rapid decision-making.
But not all pLTV models are created equal.
Why most pLTV solutions fall short
The main issue is that most available pLTV tools focus on a single monetization model (either IAA or IAP). Therefore, they fundamentally struggle to capture the timing dynamics and behavioral complexity of dual revenue streams.
“We need more tools for hybrids, they’re seriously lacking out there. But at Tenjiin, we’re super focused on solving this.”
– Senior Product Manager, Tenjin,
Jaspreet Bassan
For gaming apps, revenue distribution is trending towards hybrid monetization models. This approach is also gaining momentum beyond the gaming industry. For example data.ai reports that dual revenue streams are used by over 80% of Android apps who earn revenue from more than one source. Budget-conscious apps and those operating in developing or emerging markets often rely on hybrid monetization to maximize value across touchpoints. By blending, developers can generate returns from a wider base, while also offering their users various tiers.
That’s exactly why we’ve built our pLTV solution differently.
Our approach is fundamentally different: we unify both IAA and IAP into a single predictive model. We consider both the user’s ad engagement and the amount of purchases made within your app. From impressions to transactions, there’s a more complete picture of user value and how they generate revenue, not just how they spend.
Our model achieves 90% accuracy by delivering holistic forecasting that reflects the true economics of hybrid monetization, giving you a complete view of user value instead of partial signals.
Curious to learn how we did it? We tackle these challenges head-on in our article,”Predicted LTV for Dual Revenue: 4 Challenges Solved, ” and podcast, where our Senior Product Manager, Jaspreet Bassan, breaks down each challenge in detail.
How pLTV is calculated at Tenjin
Our pLTV model analyzes early user data and behaviors across monetization streams. It looks at behaviors such as:
- Ad impressions
- Session depth
- Initial purchase signals
- Engagement patterns
- Early retention indicators
Our neural network processes these signals simultaneously, identifying complex patterns that indicate future revenue potential. By training on millions of user journeys across both IAA and IAP, the model learns which early behaviors correlate with high lifetime value, enabling accurate forecasts from day 0. You have actionable insights in hours, not months.
The competitive advantage
This predictive approach enables faster optimization strategies, accounting for a more holistic total user value that includes both IAA and IAP components. A comprehensive pLTV metric, has a real competitive advantage:
- You can make decisions based on holistic forecasts, instead of partial signals.
LTV prediction includes both monetization streams, giving you a complete picture of user value from day-0. You’re optimizing based on predicted total value (IAA plus IAP), not just the revenue that happens to materialize quickly. - You can act on campaigns in real-time.
Fix your budget, pause low-performers, and scale high-performing campaigns based on our predictive forecast.
You’re no longer waiting weeks only to discover a campaign has been underperforming the entire time. With LTV prediction, you can understand user value within hours. You’ll be acting sooner with accurate, predictive insights that help you allocate budget more effectively, scale winning campaigns faster, and maximize return on ad spend (ROAS) in real-time.
Traditional LTV measurement is slow: waiting 60 days for data to mature is like waiting for a fax confirmation. The gap between teams using pLTV and those relying on traditional LTV widens every campaign cycle. Many other competitors with predictive models don’t have this competitive advantage. With Tenjin, our pLTV is already built in, directly into our user-friendly dashboard. Get ahead with our 90% accurate pLTV model and start seeing results within hours.
Key Takeaways
- Hybrid monetization creates a revenue timing gap.
- Most pLTV measurements focus on single revenue streams don’t deliver the full picture
- Hybrid-first pLTV provides a competitive advantage
- We’ve created a hybrid-first pLTV metric to forecast lifetime value from Day-0
- With early and accurate pLTV data, you can act on insights and campaigns sooner
