Predicted lifetime value (pLTV)
The predicted or potential value of a customer, which combines past learnings with current measurements, in order to allow marketers to build and optimize campaigns around their audience’s predicted consumer trends.
What is predicted lifetime value (pLTV)?
To better understand how pLTV serves your measurement and performance goals, we first need to nail down what LTV means, the immense added value of predictive analytics, and the mighty potential of their power combo — pLTV.
Lifetime value — aka LTV — is an estimate of the average revenue a customer will generate over the time that they use your app or service. But, given the recent data privacy revolution, how does one measure LTV without the same level of access to granular and especially long-term performance data?
This is where predictive analytics or modeling comes into the picture. It leverages machine learning and artificial intelligence (AI) to examine historical campaign data, past user behavior data, and additional transactional data — in order to predict future actions.
By creating different behavioral characteristic clusters, your audience can then be segmented not by their actual identity, but by their interaction with your user funnel in its earliest stages, which can indicate their future potential to drive meaningful value to your business.
Why is it important?
Armed with knowledge, predictive modeling enables you to make rapid campaign optimization decisions without missing a heartbeat. Nip unsuccessful campaigns in the bud, or quickly double down on investment that can drive even better results — without compromising your users’ privacy.
In other words, pLTV allows you to leverage data science horsepower, and predict how much money your customers will spend in your app over a predefined window of time based on their past behavior.
It also enables you to segment users by their acquisition source and forecast projections accordingly, making it an ideal tool for determining which of your marketing channels will produce your highest spending users now — and in the future.
Especially during the acquisition and re-engagement stages, understanding user behavior patterns and the typical milestones that separate high-potential users from low potential — can be incredibly valuable.