App monetization strategies should revolve around solid analytics. Mobile app developers build businesses based on a combination of business models including app purchases, subscription, in-app advertising, upgraded PRO versions, in-app purchases and other ever-expanding lists of monetization models. The more these models are based on actual mathematical figures, the better, as any business should be. There are plenty of data points app marketers and developers are able to collect to understand where to invest the most to maximize on the monetization. Like any other business, this business intelligence should be the basis of business decisions. For an app developer business decisions include where to invest in user acquisition, targeting strategies, user communication, user flows & user interface, difficulty levels, data collected – and everything that could potentially influence user’s experience and opinion within the app and of the app.
We have put together 5 reports which we think is all you need to have rich insights into where, how and on what you are making money, and what’s giving you the most ROI, as a business. This, in my opinion, is best detached from the creative aspects of the business. Ideally, your direction of thought should be this way. 1) Collect data points 2) Make reports that make sense and help you interpret right 3) Decide on the optimization levers and steps forward 4) Add creativity to come out with the best optimization like say, decrease game difficult, add an additional in-app purchase on Level 2 etc. So here are the reports every app developer should track to optimize and maximize app monetization results.
A cohort (In this context) is any particular set of users that you may have acquired within a time frame from a particular source. Therefore, I could have, say 500 users that form a cohort, acquired from organic channels (Search, social channels, etc.) divided into weeks as shown below.
So, in this case, I clearly distinguish between those users acquired from search channels vs those acquired through social channels. User acquired within each week has been marked as distinct cohorts. What action you mark as the desired action (In this case acquisition), is entirely up to what you think is of priority within your app business. This only steps 1.
IMPORTANT: To ensure that you have all your desired events are tracked using your analytics platform and if you have specific ‘monetary’ values attached to these events – enter that as a constant. ie. say you have in-app purchase number 1 worth say $0.99 – make sure you distinctly track this using your analytics platform. For non-games apps, it could be a PRO upgrade or re-engagement metric.
Next, is to relate the 2 critical data points above. That is, the cohorts you have defined with the events attributed to them. So you will find clear trends in how cohorts across different inbound channels varying in their desired performance. This should give you further hints on how to improve monetization metrics further.
Here, we see acquisition cohort analysis based on channels (Funnels) and their effectiveness based on re-engagement and Average Revenue per User. From, the above snapshot users acquired from ‘Pandora’ on Day 30 has a retention rate of 14.19% and generating a maximum Average Revenue Per User (ARPU) of $2.62.
Stage Level Analysis
This is especially relevant for gaming apps or even apps that have gamification built into them like learning apps etc. Once you know which cohort is doing well, the next thing you want to know is at what stage are users generating the most revenue per user. The pre-requisites to track this is exactly the same as those for cohort analysis.
Analyze desired events (In-purchases, Upgrades, etc.) at a stage – by – stage level. If there is optimum revenue at a particular stage or too less at a particular stage, some questions you can ask yourself are:
1) What factors are affecting the revenue?
2) Are the in-app purchases rightly positioned for visibility?
3) Are there too many distractions?
4) Are the ads right in terms of formats, placements and sizes?
User segmentation report: Once you have analyzed based on channel-wise cohorts and stage level go on to the next level. If you are not already doing this, do segment your user base into recognizable distinct personas. This can be based on the frequency of users (Heavy users, light users), Expertise (Those that score high, those that score low), Demographics (Woman, 25-34 etc.) and other segmentation groups. You could then run a monetization performance report to deep-dive into which demographics are yielding the best revenue results for you.
Channel-wise Profitability Report: If ‘events arent of particular significance to you or if you have fewer events that an average game, a channel-wise profitability report is an essential tool to get great insights. This is a simple report that compares, cost of acquisition, revenue, and profit across multiple channels from where users were acquired. Here’s a snapshot:
Virtual Goods Correlation: If you are monetizing your apps using in-app purchases, very often, those purchases at the earlier stages can have a domino effect on those at later stages. It would be good to lay out the purchase options at different stages to understand if you are able to mark out any such correlation.
Many of the above reports, directly relate to in-app purchases and other non-advertising related revenue. These revenue channels are the ones that developers have the most controlled on and therefore are the lowest lying fruits when it comes to improving app monetization strategy.
What other reports do you run to analyze the effectiveness of your app monetization strategy? How do you check you are not leaving any money on the table. Let us know and we will be happy to add your views.