The Need for Custom Metrics – Monetization by Moving Beyond the BasicsAugust 24th, 2012 at 7:36 am by Ereika
Basic metrics like DAU/MAU, ARPU, and others are great for getting a top-level view of how your social game is performing, but they won’t give you the specifics you need in order to successfully monetize your game. For that, you have to take these basic metrics and use them to inform the implementation of custom tracking that will give you the insights you need in order to turn players into payers.
Let’s take the following hypothetical social game scenario:
A social game has been active for the last 12 months. Their initial MAU numbers increased rapidly in months 1 through 3, increased slightly in months 4 and 5, but have now leveled off to an even number. Meanwhile, DAU continues to increase. The overall conversion rate for in-game purchases is 2%.
From this high-level assessment, we can make some general (and potentially conflicting) assumptions:
- The game may not be retaining new players well. – increasing number of new players engage with the game, but few are retained to subsequent months.
- The game may be retaining some subset of new players well, but not in general. – players who engage in a certain subset of activities are retained, those who do not engage in these areas are not well retained.
- The game may have a core following of well-retained players brought in via a specific channel. – players who are brought in by friends are retained, regardless of the activity played, while users who come in on their own are not retained well.
- The game converts well early on, but not later in the player lifecycle. – Most new players make a purchase, but then aren’t retained. Continual influx of new players keeps conversion rate steady.
- There are issues with conversion for new users, but not for users who are retained. – the same subset of retained players continue to make purchases month after month, with only a small percentage of new players making an initial purchase.
Any of these explanations may be true. It is only through deeper analysis that we can uncover the insights that will help this game to improve. Looking at the assumptions above, we can clearly see the need to track (at minimum):
- Which acquisition channels bring in retained users
- Which areas of the game have the most activity from new and retained users
- Which areas of the game are largely abandoned and/or cause users to stop returning
- When do monetized players typically make a purchase – here we can break this down even further into:
- New players’ purchasing habits
- Retained players’ purchasing habits
- Where in the purchase flow do most non-monetized players drop out, including:
- Problems with the conversion flow itself (drop-offs)
- Technical difficulties (failed transactions)
Answers to these types of questions require in-depth tracking capabilities and are unique from game to game. While some games may have multiple mini-games to track, others may have only one. Likewise, competitive games will have different measures (leaderboards) versus cooperative games (gifting) that make a direct impact on the level of engagement.
Knowing What to Track
Even with this basic scenario it’s easy to see that the analytics involved could potentially become overwhelming. It’s best to pick one area of your game to focus at a time, with the understanding that there will be overlap between these areas, such as acquisition channels potentially being covered by retention rates or monetization.
For example, if we wanted to understand the current monetization within our hypothetical game, we might measure the following:
- How long monetized users have played the game
- What areas of the game monetized users spend the most time with
- When in the play cycle monetized users are more likely to purchase
- What are the acquisition channels for monetized players
… and so on. In this way, we build out an accurate idea of what makes for successful monetization in this particular social game. We might also drill down further and gather information about whales versus more average purchasers.
Understanding what brings in your best players and payers, along with what keeps them engaged in your game isn’t as simple as running a few generalized reports. It’s only by digging into the data and gaining insights as to how players are interacting with your social game that you can truly start to optimize the play experience, and from there, your monetization rates.
Sound off: What do you think is the most important metric for social game success?