Free tools for ‘stupid simple’ game analytics: retention, LTV, DAU, ARPDAU

Game analytics is hard. Retention curves are hard. Calculating LTV can be hard, and knowing how many DAU you’ll have after 7 months of growth campaigns is also hard. Fortunately, there are some new free tools to help  you figure it all out without knowing Python, without having to write complex scripts, and without even having to do some complicated spreadsheet work.

It’s called Professor Arpdau, and it’s a suite of (mostly) free online tools designed to help game developers and marketers predict user retention and lifetime value (LTV), plus optimize pricing for different global markets.

It’s from Russell Ovans. If that name rings a bell, it’s because he wrote a massive book on analytics for mobile games called Game Analytics: Retention and Monetization in Free-to-Play Mobile Games. The book is great, but it has some parts with lots of math and code, and Ovans wanted to make game analytics “stupid simple.”

I recently had a chat and got a demo from Ovans.

Click play to check it out:

Engineering mobile growth via game analytics

Ovans is an entrepreneur, software engineer, and computer scientist. He’s also the former director of analytics for East Side Games, makers of Star Trek, The Office, and Trailer Park Boys games, among others. He’s still on the board there.

So he knows a bit about mobile growth and game analytics.

And he knows what’s key to your app growing.

• Things like retention, where tiny improvements in D7 or D30 metrics can have a huge impact on revenue.
• And pricing strategy, where just letting Google or Apple set your global prices based on exchange rates will result in much lower sales and profitability than you might think.
• Or live ops investment, because games with good retention (8%+ at D90) typically invest in events, new content, and player engagement.
• And LTV forecasting, because by understanding expected revenue per player, UA managers can bid confidently on new installs.

But calculating retention, LTV, and expected DAU over time are challenging. And implementing a global pricing strategy on Google Play, for instance, is tedious and painful.

So he built some tools to make it easier, and is releasing them for free.

Free tools for game analytics: retention, LTV, DAU predictor

There are 3 free tools in the Professor ARPDAU game analytics collection:

1. Retention Curve Creator
   This tool helps game developers predict long-term retention by inputting early retention numbers (D1, D3, D7). The model fits a curve to the data to estimate D30, D90, and even D365 retention. Retention curves are the foundation for all other game revenue and performance predictions, so this is critical.
2. LTV Predictor
   The LTV Predictor uses the retention curve that you’ve just built, plus your ARPDAU (Average Revenue Per Daily Active User) to forecast customer lifetime value over time. It provides D7 ROAS (Return on Ad Spend) targets to help UA managers determine if an ad campaign is on track to break even, providing insights like break-even timeframes. For example, if D7 ROAS is 29% of CPI (Cost Per Install), you can expect to break even by Day 90.
3. DAU Predictor
   The DAU Predictor estimates how many DAUs and revenue a game will generate based on your retention curve and daily installs, which helps marketers forecast how big a game will get and whether their retention strategy is working. For example, with 2,500 installs per day and a retention curve of r(n) = 0.33 * n -0.238, the DAU Predictor estimates you’ll have 95,000 DAU after a year with daily revenue approaching $150,000.

This is super-helpful for the non-technical mobile marketer, but it’s also super-helpful for technical marketers. The reason: it’s incredibly simple to pop in different numbers and check what a different retention curve might do for your break-even period. Or what slightly increased UA might do for your daily revenue numbers in a year’s time.

It’s “stupid simple” game analytics, which means it’s also really really fast. And speed is just as important as ease.

1 paid tool: country-specific pricing

There is 1 paid tool as well for country specific pricing.

The reason is that if you have 20 different items that can be purchased, implementing a price for each in each geo you’re releasing the game is almost impossible. It’s tedious and time-consuming. And many games have 50 or a hundred items players can buy. Multiply that by 150 countries, and you’ve got a recipe for a wasted week.

So you let Google Play do it automatically.

The problem: it doesn’t understand the Big Mac index. In other words, it just does a straight conversion between currencies without taking into account affordability.

The result is lost revenue.

“Professor ARPDAU not only uses current exchange rates and understands which countries have a value added tax or goods and services tax that must be included in the price, it will go through and adjust all of your prices using the Big Mac index or purchasing power parity, whatever it has data available for, to try to come up with a price that’s more comparable in the 100 other countries that your game may be available in,” says Ovans.

It then gives you a CSV file with all the right pricing to upload to Google Play: updating all your pricing all at once.

Ovans learned of this problem when seeing lack of profitability for East Side Games in Mexico, where automatic currency conversions resulted in prices that were unaffordable for locals.

After adjustment, revenue went up significantly, as did profitability.

Much more in the full podcast

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Here’s what you’ll get in this episode:

• 00:00 Introduction to Growth Masterminds
• 00:59 The Goal of Making Game Analytics Simple
• 02:09 Challenges and Feedback on the Book
• 03:39 Launching ARPDAU’s Free Tools
• 04:54 Demo of Retention Curve Creator
• 10:51 Predicting Customer Lifetime Value (LTV)
• 16:52 Estimating Daily Active Users (DAU) and Revenue
• 21:57 Future Enhancements and Feedback
• 24:05 Introduction to the Big Mac Index
• 24:30 Country-Specific Pricing Strategies
• 25:08 Challenges with Global Pricing
• 26:31 Implementing the Big Mac Index
• 28:06 Google Play Console Pricing Features
• 30:39 Using Professor ARPDAU’s Tool
• 31:52 Adjusting Prices with CSV Files
• 39:33 Final Thoughts and Q&A