Future LTV calculator for subscriptions

LTV (Lifetime Value) is the total revenue a company expects to earn over the lifetime of its relationship with a single customer.

LTV prediction will help you calculate return on ad spend. For example, it can give you an idea of what channels will not work for your ad campaigns, as users will generate less revenue than you spend to attract them. LTV prediction will also give you the big picture of how efficient your paid and free channels are.

LTV prediction can be useful for website and app marketeers engaged in paid product promotion. It helps to estimate revenues by advertising channel and campaign before you spend money on them. LTV prediction may also prove to be a good analytical tool, as the data can be exported via RAW API and used for analytics.

1. With MyTracker's predictive model, you can forecast revenues from any group of users. Thanks to the model mix, we are less dependent on having historical data for a similar cohort. Even if no historical data is available, the system makes calculations based on user behavior in similar apps. This means that you can have an accurate estimate for any cross section (by age, sex, country or ad campaign).
2. Different types of payments (in-app payments, subscriptions, ad monetization, S2S) can vary substantially. Subscription payments can drop, while ad revenues may increase. Their trends can often move independently of each other. MyTracker employs different approaches to tackle each type of payment. Some of them would need a regression tree model, while for others a simple approximation of the logarithm function works better.
3. Most of the predictive models are based on quantitative probability methods, and they face difficulties when it comes to predicting user behavior after sudden and significant changes. For example, you announced a big discount or promo, resulting in more customers buying your products. After such promos, LTV prediction may be less accurate. Another factor likely to impact the analysis is a change in ad monetization or the overall app development strategy.

The system detects unexpected activity and makes relevant adjustments to models by flattening the peaks. However, 100% accuracy cannot be guaranteed in this case.

MyTracker can predict Lifetime Value (total revenue from a user after app installation) with an accuracy of 90% on the 30th, 60th, 90th and 180th day from the app installation, as well as one or two years in advance.

Relying on billions of actions, MyTracker models are capable of making up-to-date predictions from the first days of use. As your app data accumulates and the models are trained to adapt to a specific audience, predictions become increasingly accurate.

Payments, launches, sessions, ads, and sociodemographic data. The key input for LTV prediction is payments, while other data serve to improve the prediction model and quality. Custom events can also be used as inputs.

MyTracker has free LTV forecasting (30 or 180 days) for ad campaigns on iOS 14.5+ via SKAdNetwork. Learn how predictive analytics works and how to predict LTV using SKAdNetwork functionality in our article.

MyTracker can also predict churn and export segments of users who are highly likely to stop using your app. This will allow you to work on their retention and adjust the forwarding of this data to ad networks for retargeting.

Yes, LTV prediction is also available for websites, helping their owners to calculate revenues from purchases and advertising. To do this, you need to set up the reporting of revenue from different monetization methods using S2S events. You will obtain a forecast that enables you to estimate the cost of purchasing and earnings from a particular channel.