In Data analysis, Free to play, Uncategorized

As a CEO of a company that makes free-to-play games, you need to juggle many things to make sure that your business is successful, and often information may be coming at you from all directions. There’s a plethora of metrics that you can monitor to give you a good overview of performance and inform your decision-making, and you’re probably already using many of them. It’s important to know, however, which ones you should focus on and how they can paint a misleading picture of what’s working in the game if they’re not being used correctly. This list covers some of the key free-to-play game metrics you should know, as well as explaining how and when your team should be using them.

1. Day 1 Retention

Day 1 Retention is up there as one of the most revered metrics, and this is particularly true in free-to-play games, where revenue is often directly related to how long the player sticks with the game. It’s not unusual for all players not to return after one session, so a strong value for Day 1 Retention is 50%, with many games treading water at around 20-30%.

If your Day 1 Retention is low, this tells you that you need to make improvements to the game. On its own though, this metric can’t actually tell you all that much, like why are players leaving, so it’s often analyzed alongside the First Time User Experience (FTUE) to determine the drop-off points. Your team should consider the two together to avoid painting an ambiguous picture of what’s working and what’s not.

2. Day 7/14/30 Retention

We spend a lot of time talking about Day 1 Retention in the games business, and rightly so, but looking at Retention later on in the game is just as necessary. Where Day 1 Retention is a measure of your on-boarding and First Time User Experience, measuring Retention later on in the game will give a more insightful look at player engagement and overall enjoyment.

Measuring engagement is not just about keeping players happy, your team should be using this metric as a vital indicator of game monetization, as players that play longer are generally more valuable. Our research shows that the average transaction value of players increases with every purchase, so we know for certain that players that play longer, spend more.

3. Lifetime Value

When you’re responsible for return on investment, it’s absolutely essential to understand the value of each install so you can justify your acquisition spend and plan your marketing budget. If your analytics team uses the right model, lifetime value (LTV) can be used to give you a prediction of what players are likely to spend in your game. This can prove very helpful when developing engagement strategies for different player segments and evaluating acquisition channels.

The approach your analytics team adopts can depend largely on the data available to them, the number of players you have, and the extend of variations in lifespan and spending patterns.

4. Spender Fraction

If you want to determine whether your game is monetizing well, then you need to look at Spender Fraction, that is, the percent of all players who are spending.

Spender Fraction is used with metrics such as Day 1 Retention to diagnose the cause of monetization issues in the game, i.e. whether poor monetization stems from players leaving early or from a lack of incentive for them to convert. As a CEO, you need your game to have a healthy spender fraction. However, if it is low, while Retention rates are high, it could be that you are missing opportunities to monetize loyal players.

For your insights team, it’s important that they relate Spender Fraction to other metrics to avoid making a bad judgement on game performance.

5. ARPDAU

Average Revenue Per Daily Active User (ARPDAU) is an important metric to help you understand how well your game is monetizing. While Average Revenue Per User (ARPU) tells you what you can expect to earn from each player, ARPDAU tells you how any changes made in the game, e.g. engagement campaigns, are affecting monetization performance.

In the world of free-to-play, your job is not done once the game in published, and most games will require some tweaking to optimize engagement and monetization for different types of players. Most games companies now understand that their games need to be personalised to suit different player segments through Player Relationship Management. There are often many variables to consider when doing this, and their effectiveness will need to be assessed separately, but ARPDAU will give a general overview.

A really strong ARPDAU tends to sit around $0.15 to $0.25, with most healthy games making around $0.05.

Many game designers focus heavily on the number of Daily Active Users (DAU) a game has, while financial teams may be more focused on Monthly Active Users (MAU). This metric can be used with either (e.g. ARPDAU or ADPMAU), depending on the timescales that are being reported (e.g. looking back at a year’s performance), and the length of campaigns.

Bonus metric: Mission Start / Login

This metric may not be so familiar, but it is an excellent one if you’re using rewarding in your free-to-play game.

It’s old news now that rewarding in free-to-play games can be super-effective, so if you’re not using it already, it should be on your agenda. A popular way of applying this is to offer daily rewards. This, however, opens up the risk that players will return just to farm them. If your analytics team aren’t looking out for this, you can end up with a view of retention that is misleading. You really need to determine whether your users are genuinely active and are engaging with the game.

One way to do this is to compare the number of Mission Starts to the number of Logins. You can also look at different stages reached within the game, such as missions completed, to determine how engaged these players are in the long term. This will paint a much more accurate picture of game stickiness and the reveal effectiveness of your rewarding strategy.

 

What metrics are you currently using, and which do you think are most important? Leave us a comment in the box below. 

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