• Predicting your Game’s Monetization Future: An Analysis on How Top Games Developers Calculate Lifetime Value
  • Ignacio Monereo
  • The Nuggets translation Project
  • Permanent link to this article: github.com/xitu/gold-m…
  • Translator: NoName4Me
  • Proofreader: Mingxing47, Hanliuxin5

Predict the monetization future of your game

An analysis of how top game developers calculate lifetime value

Many of us dream of building the next generation of phenomenon games, games that will be remembered for their unique visuals and innovative gameplay for generations to come. As a result, we typically spend a lot of time thinking about some of the fundamental business issues behind sustainable business. For example: How much can I acquire a new player? What is the potential value of one user to another? How do I quantify the social impact of people sharing my game and bringing in new players? When will my users get bored, and how can I prevent it?

The breadth of data generated by gameplay and the ability to target the user level make customer analytics a core part of the game business. The complexity of mobile monetization and competition in the industry means there can be pressure to find more innovative ways to take action from data to give your business an advantage. One approach is to build models to help predict the lifetime value (LTV) of game players. This article provides an analysis of how top game developers calculate lifetime value. If you want to learn more about this topic, read the full white paper.

Lifetime value in the game

What is LTV?

As the name suggests, LTV is an assessment of the total monetary value of a particular player over their lifetime.

While lifetime value is a broad metric that allows game developers to understand the value of their players, there is no standard way to calculate it. Most developers either use custom methods to calculate LTV or use third-party tools. No matter how you measure it, there are three main mistakes developers make when using LTV.

  1. The first mistake many developers make is not including all revenue sources when calculating LTV. It is common practice for developers to calculate LTV only for in-app purchases (IAP) and then add a percentage to that for other revenue sources (e.g. advertising). LTV should include all monetization business models as much as possible, such as IAP, AD revenue, etc. Otherwise we may miss out on growth opportunities by not including legitimate revenue.

  2. The second mistake some developers make is to assess the impact of less obvious factors, such as a competitor launching a new game, the stage the company is in, currency changes, etc. These can lead to significant deviations in LTV without any changes being made to the game. In summary, we need to think of LTV as a dynamic indicator that changes over time as the game evolves: a) internal changes — new content or features, in-game economies, player behavior. B) External changes — game trends, competition, currency fluctuations, platform changes.

  3. Finally, some developers see LTV as a competitive advantage. However, LTV is only one metric, so it does not represent a competitive advantage over other developers. In addition, it is not an exact value, so it should also be considered a range (e.g. LTV between 1 and 1.2) or within a certain accuracy (e.g. 85% confidence). The ultimate goal is to avoid the bad behavior associated with overly optimistic/pessimistic lifetime forecasts.

How will LTV help me make business decisions?

LTV is typically used for player acquisition, but it can also be used for many other purposes: overall business profitability, optimizing online operations, and managing new feature launches. In common uses of LTV, we find:

  1. Profitability: LTV is an estimate of the total cash flow a user can provide over a lifetime. Therefore, if we compare estimated revenue to associated costs, we can estimate the bottom line of each user’s impact on the cash flow of the business.
  2. User acquisition: As long as the cost of acquiring new players is no higher than net LTV, we can theoretically still invest in user acquisition. A good rule of thumb that many developers apply to player acquisition is that costs should ideally be less than 1/3 of total LTV, depending on many other factors (expected growth, market patterns).
  3. New features and real-time operations: Content updates can affect retention, engagement and monetization, as well as all the drivers of lifetime value. Top developers test new updates before launching to see the overall impact of LTV.
  4. Build a new game: Some developers look at LTV in beta to assess the viability of an unreleased game.

A popular way to calculate LTV in mobile games

As mentioned above, there is currently no standard method for calculating LTV. However, developers generally assume that LTV is based on at least two variables: lifecycle (looking at engagement and retention) and monetization (average number of transactions, currency value, conversion rate).

While everyone agrees that these two variables must be considered in the calculation, there is still debate over the exact method of calculating them.

1. Life cycle

Lifetime is usually measured in terms of retention. This is where the debate begins, with three different views of how retention is calculated:

  1. The classic
  2. The scope of the
  3. The ups and downs

While classic daily retention measures only look at players who come online on a specific date after the install date, range retention looks at players returning over a period of time, such as a week. Fluctuating retention focuses on how players return after a period of time.

Each calculation method can be better suited to specific types of games. For example, if a story-driven game releases a new story or season at a certain point in time — so players don’t come back until the new season is released — then the classic retention calculations are no longer applicable and they may be more interested in scope retention and season/episode completion rates. Some super casual game developers think about hourly retention rates rather than days, because in this case, the success of the game depends on the first hour (not the first day).

One final word of caution about retention: Retention is usually defined as the user opening an application. It’s worth noting that there are still significant differences between opening apps — for example, collecting daily rewards, or fighting a battle in an online multiplayer game. Therefore, we may need to redefine retention as the act of opening the app and performing certain actions.

How long do you want LTV to last?

Before calculating the LTV metric, developers usually determine a time period for the purpose of the LTV calculation, for example, evaluating the LTV for the next 90 days, 180 days, 1 year, 2 years, or even 5 years.

Note that some people may find this concept contradictory, as the term “life cycle” itself theoretically refers to the total duration of a person’s life. However, since LTV is usually an average estimate, developers may want to be conservative and calculate LTV over time. It’s also important to note that the further into the future you estimate, the less accurate it becomes.

There are several factors that affect your time slot choice, and developers often take many into account, including:

  • Genre/genre of the game: A more specific lifecycle expected based on the genre of the game. For example, a super casual game may have a shorter lifetime than a core game running as a service, so LTV will be calculated at different times.
  • Business model: IAP, subscription, or advertising. For example, the average subscriber may have a longer life and therefore a longer time to choose.
  • Company stage: early and mature stage. When calculating LTV, early-stage companies often opt for longer and more optimistic timeframes because they are dependent on the future evolution of a particular technology, or simply due to a lack of historical data.
  • Payback cycle: A well-funded company may be able to invest in user acquisition for a longer period of time, thus extending the life of the game. For example, 180 days is the time period in which enough revenue is allowed to reach the break-even point.

2. Monetization

As far as retention is concerned, there is debate about how to calculate monetization variables. Most game developers consider ARPDAU (average revenue per daily active user), but some consider ARPU (average revenue per monthly user) or ARPPU (average revenue per paying user). As we will see later, it depends on the models used to estimate LTV, one of which we will use.

Whichever monetization variable you choose, it’s important to be consistent with the time period you choose, and to understand some limitations on the average number of outcomes. For example, if we estimate a game’s ARPDAU based on the last quarter, month, or week, it can fluctuate wildly.

LTV model common in games

Assuming that as the complexity increases, the accuracy of the models also increases, we can cluster them in the following way:

  • Historical averages and benchmarks: Based on historical data or old games.
  • Simple prediction model: Predict some variable, such as retention or cost.
  • Advanced predictive models: such as “Buy until you are no longer active” (BTYD) from Pareto/NBD and BG/NBD models or machine learning models.

If you want to learn more about the various models, please read the full white paper, which provides more best practices and insights on gaming LTV.

The idea of closure

As we can see, lifetime value metrics have a variety of uses and are widely adopted in the mobile game industry. However, we also see that there is currently no standard calculation method, so there may be several effective ways to implement it, depending on several internal (game nature, company resources, available data) or external (audience type, competition) factors.

Therefore, whenever we calculate the lifetime value of our players, we need to be prepared to make trade-offs between accuracy and the resources required to make the most of this valuable resource.

When using lifetime value metrics for user acquisition or online operations, we need to try to avoid common mistakes such as over-optimistic calculations, missing revenue streams, or treating them as a competitive advantage, which can lead to under-estimates or over-estimates. We may also want to consider key aspects such as calculating net LTV, discounted cash flow, or full split calculations.

Hopefully this overview has helped you better understand LTV’s potential to drive better business decisions. Given the complexity of the topic and more insights on it, download our white paper to learn more about best practices for LTV in computing games.

What do you think?

Do you have any other thoughts about LTV for game developers? Join the discussion in the comments below or tweet with the hashtag #AskPlayDev, and we’ll respond via @Googleplaydev, where we regularly share news and tips on how to succeed on GooglePlay.

The Nuggets Translation Project is a community that translates quality Internet technical articles from English sharing articles on nuggets. The content covers Android, iOS, front-end, back-end, blockchain, products, design, artificial intelligence and other fields. If you want to see more high-quality translation, please continue to pay attention to the Translation plan of Digging Gold, the official Weibo, Zhihu column.