Blog Using player cohort data to open up new ...

Using player cohort data to open up new sources of funding for mobile gaming studios

Imagine if you could unlock the future value from your existing user base, today. Depending on the genre of the game, lifetime values (LTVs) can be measured in months or even years. So the journey to realizing the expected LTV of a user can be a long one.

At Pollen VC, we’re using Adjust data to help us price Residual Cohort Value (RCV) —the expected future value of your live user cohorts—as an asset that gaming studios can borrow against to open up a new source of funding. A simple way to think of this is to imagine you stopped all new UA campaigns today. What would the expected value of your long tail of users look like, until these existing players stopped spending in your game?

Examining Residual Cohort Value in gaming

The amount of RCV is dependent on the LTV profile of the game, as well as the historical spend. For example, take a hyper-casual game with an expected LTV of 30 days before the player gets bored and moves on to another game. There is almost no residual value detectable beyond this point as the retention drops off very quickly and players stop playing.

Now consider game genres with longer LTV profiles, like mid-core, merge, social casino, etc. These games expect to keep people playing—and paying—for months or even years.

Whilst the investment in UA is front-loaded, i.e., the payment to acquire a user via Facebook, Google, TikTok, etc., is made upfront, the monetization of users takes place over a much longer timeframe.

Estimate LTV by tracking cohort data

By tracking data available from existing users within the game and players' spending patterns, it’s possible to estimate the LTVs of users acquired. More time series data enables us to make better predictions over what LTVs will likely be achieved over time.

From a financial viewpoint, we can think about this journey at a cohort level, from start to finish. We can think of the financial journey of a cohort in three different states.

Young cohort example

In this young cohort, just 15 days in, the revenue accrued is held by the platforms before being paid out within their normal payment terms (up to 90 days post-event). These revenues are considered accounts receivable (AR). The rest of the  cohort’s journey is thought of as an expected receivable or revenue that will be delivered as the cohort of players progress through the game.

Mid-life cohort example

In this mid-life cohort, 60 days old, there is more money trapped in AR, with a shorter journey left to recover the ultimate LTV of the cohort. No cash has actually been paid out by the platforms at this point.

Mature cohort example

Lastly, in the mature cohort, the oldest portion has already been paid out by the platforms; the middle section is the AR held by the platforms, with just a small percentage of the overall cohort revenues left to be recovered.

The more mature the cohort, the easier it becomes to predict the final LTV as you have more certainty. Zooming out to look at an aggregated view of all the existing cohorts allows us to create an estimate of residual value of your existing cohorts and these models are dynamically updated every day based on performance.

How can I use this information to my advantage?

Firstly, having an estimate of what your existing users are worth creates a useful starting point for an M&A valuation of your gaming studio. This is going to give a potential acquirer a present value (PV) of your existing users which should rationally be expected to return value over time.

More immediately though, the residual cohort value can be used as an asset that a studio can borrow against to fund its own growth through an increased pace of paid UA. At Pollen VC, we provide on-demand credit facilities to app and gaming studios, lending against a combination of accounts receivable (AR)—the value trapped in the payment cycles of the app stores and ad networks, which can have a delay of up to 90 days—plus the residual cohort value. All of this data is digitally verified every day, and is dynamically priced and not priced based on snapshots at a point in time like typical lending products (E.g., a bank loan repaid over 12 months).

If a studio has figured out positive ROAS on their ad spend, then rationally, they should want to keep doubling down on paid UA for as long as the economics continue to work, and users can be acquired where LTV is greater than the customer acquisition cost.

In order to know whether borrowing against AR and cohort residuals makes sense, it’s necessary to look at the overall profitability over time, and then narrow down to a monthly return on capital.

In this example, the cohort delivers a 66% return on capital over a 1 year period. Broken down to a monthly ROI on ad spend, this delivers a 5.5% return on capital each month.

If the ROI on ad spend outweighs the cost of capital required to finance it, then rational UA and finance managers should want to continue to reinvest into more UA efforts. Understanding the valuation of these residual cohorts and being able to borrow against them alongside AR can offer a very capital-efficient way to grow as the studio does not need to rely on external equity financing, which also dilutes a founder's shareholding.

In this current economic climate, finding efficient ways to scale a game is more important than ever. Having an on-demand UA financing partner like Pollen VC that can integrate with a mobile analytics platform such as Adjust will allow your gaming studio to scale effectively and smartly.

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