pLTV Isn’t for Everyone, Is It for You?

Most ad networks focus on quick, short-term revenue from new users. This means they might overlook customers who could bring more value in the long run. If ad platforms knew a customer’s long-term potential upfront, they could better target high-value users. In this piece, we explore how pLTV helps you find and attract these valuable customers.

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What Predictive Lifetime Value (pLTV) Can Do

pLTV provides a better way to target customers by focusing on their long-term potential, rather than just the immediate returns. Instead of optimizing for quick wins, pLTV helps you attract customers who are likely to generate more value over a longer time, such as 60 days or more. Using historical data and machine learning, pLTV forecasts a customer’s potential future value early in their journey, offering a more complete view of customer quality.

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When Does pLTV Make Sense?

Before investing in pLTV, it’s important to see if it adds value to your business. There are two key factors to consider:

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1. Post-Optimization Conversions

If a significant portion of your customers’ revenue happens after the typical 3-day optimization window, you might be missing out on valuable customers. Our tool measures how many conversions happen beyond this window and helps identify the missed opportunities.

As fans of the open-source approach, here is exactly what we compute for you.

1. We define the anchor event from which you start counting the time windows to calculate conversion rates. This could be the timestamp of the install, first visit, registration, etc.
2. We calculate the conversion rate to a key event (e.g., purchase) at different time windows: 7, 14, and 30 days.
3. We compare the conversion rates across these different time windows. A significant increase in conversion rate from a shorter window (±3 days) to a 30-day longer window indicates delayed conversions.
4. We quantify the percentage of total conversions outside the initial shorter optimization window.

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Run the analysis for free on your own data.

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2. User Value Re-Ranking

Are the users who spend the most on day one still your highest spenders a year later? If not, your short-term strategies may not predict long-term success. We use your customer data to see if there’s a disconnect between early purchases and long-term value. If there’s a weak correlation, adopting pLTV can help you target customers who will bring in higher long-term revenue.

To determine if your business re-ranking effect and pLTV modeling will benefit your business, we built a tool that computes this metric using your historical customer data.

Our tool runs a Spearman correlation analysis, which does the following:

1. Selects a Cohort: Chooses a cohort of customers who made their first purchase approximately a year ago.
2. Ranks by Initial Purchase: These customers are ranked based on their spending during their first interaction day (Day 0 ranking).
3. Ranks by Long-Term Revenue: After a year, the same cohort is ranked based on the total revenue generated over the entire period (long-term ranking).
4. Calculates Spearman Correlation: Computes the Spearman correlation between the Day 0 and long-term rankings.

Run the analysis for free on your own data.

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Assessing the Impact of pLTV

In user acquisition, the ability to predict long-term value is crucial. Short-term revenue signals might not always align with your broader business goals. By evaluating your conversion patterns and the correlation between early and long-term revenue, you can determine if pLTV will enhance your strategy. For businesses where short-term and long-term value don't align, pLTV can help attract more valuable users and drive better outcomes over time.

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