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Evaluating or Even Predicting Lifetime Value (LTV)

We know that you all dream of building the next iconic game that will be remembered by future generations, you generally spend a lot of time thinking about some of the fundamental business questions for a sustainable business.

How much can I spend in acquiring a new player?
What is the potential value of this user versus another one?
When will my players churn and what can I do to prevent it?


And of course, building models that help to predict the lifetime value (LTV) of your game players.

We are here to take advantage of the benefits data can bring. Here, capability to detect and predict the behaviour of players as early as possible is the most important factor for promising mobile game.

LTV prediction and its period should based on the your game type. Here we applied 14-day LTV prediction for Hyper Casual Game while we apply longer time period for Casual Game such as 30-days, 60-days etc

Predicting determinant attributes of users is valuable both in terms of reducing expenses and increasing revenue. These effect directly to the LTV prediction. An urgent need in F2P mobile games is to convert players from “Non-spending” to “Valuable” users to reach sustainable Life-Time Value. So firstly, AppNava detect “Valuable” users to predict LTV. Next step is predicting number of purchases. Last step is predicting the amount of purchase. All these three steps take you to successful LTV prediction.

The breadth of data generated by gameplay and the ability to target actions at a user level has led to customer analytics becoming a core part of a games business.

Let’s see the result of the ongoing partnership with Idle Tycoon Game.

The goal of the collaboration was to increase the LTV of players. AppNava found that almost half of the newcomers leave no money in the game (LTV=0, no in-app purchase, no rewarding video watching). Then, AppNava's LTV Model was initiated for Newcomers.

The first step is to distinguish people into "valued players" and "unvalued players" in the game.

The second step: After the newcomer players finished the first session, AppNava detected "unvalued players" in the game, and they were shown interstitial ads. The most significant benefit of interstitial ads is to monetize (almost) all players. These include "unvalued players" who don't interact with opt-in ads and in-app purchases.

The following results were obtained;

The LTV of "unvalued players" increased by 200% by accurately identifying their Life Time Value,

There is no change in Day-7 and Day -10 retention rates (even slightly higher like 0.80% points less than 1%) of "unvalued players",

But Day-14 retention rate of "unvalued players" drop from 9.5% to 8.16%.

LTV Increased by 200%

Tag Players

Churn Reduction

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