One of the areas in which a company can drastically increase ad revenues with a relatively low effort is through the optimization of opt-in ratios to rewarded videos. Here we will show how to track and optimize opt-in rates with SOOMLA TRACEBACK.
What is opt in rate and why does it matter
Rewarded video is a unique format in the sense that it’s not forced on users. The game is offering some reward in return for watching a video and the user can accept the offer or not. These offers can be made with a pop up message, a button on different screen in the app or sometimes by replacing a call to action that would normally be prompting the users to pay. Regardless of the offer method, the users can accept or decline. The number of users who decide to take the offer is often called engaged users and the dividing them by the total number of active users is considered the opt-in rate.
One thing that is clear is that users who don’t engage with the rewarded video don’t contribute any revenue so by increasing the opt-in rate we are making the pool of monetizing users bigger. It is also known that users monetize best in their first impression and so getting more users to opt-in means you are getting a lot more of those valuable 1st impressions. Our experience has shown that increasing the opt-in ratio by x% often translates to a similar increase in the total ad-revenue.
Measuring the opt in with SOOMLA TRACEBACK
One of the easiest ways to measure the opt in rate is to use the TRACEBACK platform. You can see your overall opt in rates and number of engaged users but you can also look at specific segments and breakdowns across these dimensions:
- Versions of your app
- Traffic sources
- Date ranges
Looking at specific segments allows you to find improvement opportunities. The way to spot these is simple – a low opt in rate means there is a room to grow it.
What is a good opt in rate
Depending on your game of course and how well you are doing with IAP monetization you can reach as high as 80% opt in rate according to this study by Unity Ads. However, apps that focus more on IAP would be smart to first convert the users into payers and only then try to push them harder to videos. From this reason we should look at the opt in rate on a cohorted basis and set different goals depending on the lifetime of the users. These are good benchmarks:
- 1st month – 20%
- 2nd month – 50%
- 3rd month – 60%
Optimizing opt in rates
Once you have identified a segment that falls below the target opt in rate, you can use TRACEBACK to optimizie it. One way to do it is to track the opt in rate in different versions of your app. Whenever you launch a new version you can immediatly compare the opt in ratio to the one of the previous version and check if you are moving towards the goal or away from it.
Example – Optimizations results in higher opt in rate in later versions
Here is an export from our dashboard into Excel showing the opt-in rates in different version of the app.
While comparing opt in rates between different versions is easy to do and comes as a built in feature of the platform, a better approach would be to use TRACEBACK alongside an a/b testing tool. This allows customers to compare between different versions and configurations simulatnously in a randomized testing environment. TRACEBACK will present the opt in rate for each testing group in the dashboard so you can easily compare and pick the winning configuration.