Get your detective’s hat on and whip out your magnifying glass. We’ve now bundled all of our DataSuite products under one plan, one price. All to make it simpler and easier to level up your analytics for your games and crew.

Without breaking the bank, you can now grab every feature we have in our DataSuite plan for one cost. You’ll be able to query your raw data, pump this into your tools, easily spot trends or investigate bugs across your portfolio, and run advanced A/B tests on all of your games.

So in this article, we’re going to chat about what exactly those features are, why we’ve made this change, and how you can use DataSuite to solve problems for your games, faster.

Five products wrapped in one

There’s a lot you can do with DataSuite. And after chatting with our customers, we figured that there’s no real one-size-fits-all approach to their analytics. Every studio and publisher’s setup and structure are unique, with different teams, resources, and needs.

It made sense to bring them all together. It’s now a lot simpler to figure out what exact tools you need and predict how much it’ll cost your studio. And it means any new features we roll out, you’ll have access to right off the bat.

There are five products listed in our DataSuite. Here’s what they are and what they do:

• Metrics API: Fetch your metrics for all of your games – You can build custom dashboards showing just the metrics you care about. So you can compare all of your game’s metrics and performance at a glance, making it easier to spot trends or bugs across your entire portfolio.
• Player Warehouse: The home of your data – Our very own prebuilt data warehouse that you can rent out. We bring in your data from our GameAnalytics tool into our Player Warehouse. So your data analysts can find quick insights about your games on the fly and run advanced tests on groups of players. (No engineers required, and saving you months of development time.)
• Raw Export: All of your data, served raw – You can send your GameAnalytics data programmatically (in JSON format) into your own data warehouse or data lake every day. And it’s much easier to chop this up and mix it with any other data sources you have.
• Event Export: Pull out just your events – Similar to our Raw Export, this is your data trimmed down to the event level. So rather than completely raw, you’ll see data for every single event in your games. You’ll have rows for the events each day, and every row has even more data behind it.
• Data Visualization (coming soon): Transform your data into easy-to-read visuals – We’re still working on the kinks for this. But soon, you’ll be able to use our own data viz tool for your data inside our player warehouse.

Let’s put this into practice

You own the fictional Publisher, RedLobster Publishing. You launch 20 hyper-casual games a month and work with 30 different studios and developers. And now, you’re looking to do more with your data.

This is where DataSuite comes in. (Keep in mind, we’re focusing on one main example. There’s still plenty more that you can do.)

Metrics API alerts you when there’s a problem

Your data engineer notices that players are starting to drop off for one of your games. You’ve already used the Metrics API to build a custom dashboard and monitor the health of all of their games in realtime, so you’ll always see when anything suspicious happens.

Player Warehouse helps your data analysts do initial research

Day to day, your data analysts might be running quick queries to test their theories or get more insights from the data (before investing time with the raw data and potentially bringing in any data engineers). In this case, they would use the Player Warehouse to find out where players are dropping off in-game and maybe compare this with data from different sources.

After running some queries, it looks like players are leaving after level three. And there was an ad event tied to this level, too.

Now, your data analyst has two theories which they need to figure out:

1. the level is too hard
2. players saw too many ads.

Our Player Warehouse can help identify this problem, but the ad data only shows so much (it doesn’t have timestamps). Without digging any further, we can’t know which came first: the ad or the level becoming too hard. So we don’t know which event caused the player to leave. Thankfully, you could take a few routes to figure this out.

Route one: Run A/B tests on set groups

A simple way would be to set up two groups to test. One, where you show the ad at this stage, but make the level easier. And the second is to remove the ad but keep the level the same difficulty.

Run this A/B test for a few days, and see which one performs better in the Player Warehouse. Roll out the winning version to the rest of the game. Job done.

Route two: Use event export to access those timestamps

You can use Event Export to bring in event-level data, with timestamps, to your own data warehouse. Working with the data engineer, your data analyst could run advanced queries and filter through single events in the game. Combine this with the ad data, and you can find out exactly what happened first and whether or not they left because there were too many ads or a tricky level.

The difference here is we, GameAnalytics, define the schema for Event Export. This means we still work with the data and set the columns for your event-level data (rather than sending empty and customizable columns, like in our raw export). But for the example we’re chatting about, this route would work perfectly.

Route three: Use Raw Export to get the complete picture

Okay. So you’ve analyzed the data. But you still can’t figure out why the player left. Now’s when you might turn to our raw export.

This is where you can be more thorough with your investigation. Grab the raw numbers – all that unaggregated data – and combine it with everything else you have. You’ll be able to run more custom queries to find any hidden issues. (So say, after some digging, you find out it wasn’t anything to do with the ads or level difficulty. But instead, there was a bug in the latest release of your game.)

Your data analyst would have to work with the data engineering team, and you’d use your own data warehouse or data lake to query the raw data. Which can sometimes take a bit longer and relies on more teams. But your raw data can help you understand so much more about your game.

Level up your analytics

There are plenty of ways to use DataSuite. We recently helped TapNation increase their LTV to 100% Day 30. They now collect and analyze data across every single game in their large portfolio, which they use when running A/B tests. And with this data, not only have they been able to make faster decisions, their product team has increased the average life-time-value of their games by 50% within six months of releasing a new title.

We hope this has been a helpful introduction to what our DataSuite can do for you. If you’d like to learn more about how you can use these features, or even how to get started, then get in touch. We’d love to have a chat.

Find out how TapNation makes the best of DataSuite in our latest User Case.

We’ve improved our A/B testing feature on GameAnalytics so you can optimize further your games and try out new great ideas and concepts. You can now stop user acquisition and exclude offline users from your tests.

A/B Testing: Stop acquiring users

We notice many game developers want better control over the allocation of users in an experiment. There are situations where developers would prefer a cohort to remain active; however, no more users join this experiment.

For this reason, we introduced a functionality where you can choose if and when you’d like your experiment to stop allocating more users.

How does it work?

While an experiment is running (active), the number of users allocated to the test is displayed on the page.  When you want your test to stop assigning more users, click the Stop Acquiring Users option from the experiment menu. Confirm your action, and that’s all.

GameAnalytics take care of the rest:

• The status on the experiment page will update to confirm that the test is still active but not acquiring any more users
• Users assigned in the experiment so far will continue to be in the test cohort as long as it is active 
• Users continue to receive variant config values in their game
• The experiment will remain active until you choose to Stop from the menu or until it reaches its end of life after two months

We recommend letting your experiment run for at least a few days before hitting the ‘stop acquiring users’ button. This way, sufficient statistical certainty is achieved for the best analysis of your experiment.

Use cases and benefits

• An active experiment is populated with enough users, and the model has calculated results. You are satisfied with the experiment results but want to keep the experiment active so users continue to receive variant config values.
  This means that the events data from such users in the game will continue to include A/B Test information. So you can continue to query metrics data for your experiment users in GameAnalytics Dashboards using these Filters.

• You can start another (concurrent) A/B experiment with new user traffic directed towards the new experiment or once you are satisfied with the current experiment userbase.

Complete documentation is available here, and as usual, feel free to get in touch so we can help with your specific case.

A/B Testing: Exclude offline users

If a user is offline during their first session, we can’t assign that player to an experiment until they’re back online (that’s when our backend servers place them into an experiment and send the values to their device).

Based on your feedback, some game developers prefer that the experiment ensures such users are never allocated to a test.
So we added a checkbox in the experiment set-up flow called ‘exclude offline users’ to provide this control.

Read more about how to set up an experiment here.

You can tick the checkbox ‘exclude offline users when setting up a new experiment. This will ensure our backend servers will not consider new users who were offline during their first session. Once they are online, an attempt to assign them a variant will not be made. These players will experience the default game settings.

Use case and benefits

Enabling this option for your experiment will ensure users’ experience in the game remains unaffected. New users who first opened your game when they were offline will continue to see the default game behavior as our backend servers will never attempt to assign them to a variant once they are online.
Technically this means that such users will not influence the experiment by causing a bias in the statistical results.

However, please note that this will mean the actual population of your new users assigned to an experiment will be lower than what is defined in the experiment setup.

Practical example:

Let’s assume you start one experiment set up to target 50% of your new users. A new player that qualifies all criteria will have a 50% chance of getting assigned to this test. Assuming no other experiment is active, approximately 50% of your new installs will join the test.
However, if “exclude offline users” is checked, some offline users could be in their first session, despite qualifying the test criteria. Since they will be excluded, less than 50% of your new users are likely to join the test.

We’ve got a new ad revenue source in the mix. The best thing about it? It’s our very own ad mediation platform HyperBid. You can now get all the impression-level revenue data from HyperBid on your GameAnalytics dashboard. 

Head over to our SDK docs to get the integration started (Unity, iOS, Android).

ILRD from HyperBid on GameAnalytics

We’ve added support for impression-level revenue data (ILRD) from HyperBid. Track all your key ad revenue metrics from HyperBid directly in the GameAnalytics tool with our Ads Dashboard. Including slicing and dicing all your ad data in our Explore Tool.

Why do we make these changes?

HyperBid is our very own mediation platform built specifically for mobile games. With this integration, we make sure that you can get best-in-class mediation with HyperBid and get holistic reporting of the revenue on GameAnalytics too.

Ad revenue data is an essential influencer of your product development and monetization strategy. You can both track and optimize your ad revenue at an impression level.

What does it mean for you?

This integration is a further step in housing all your game-related data in one place.

• You can now analyze in detail the performance of your ads in the analytics tool. For example, how much revenue per user you generated or whether your ads perform better in some regions over others.
  
• You can also choose to go for our Player Warehouse service (part of our DataSuite offering) for an in-depth analysis of your ad revenue data suited to your needs. We set up a Google Cloud Project for you and load data that can be used to perform your own SQL custom queries.

Learn more about Player Warehouse here and if this is something of interest to you, let’s talk!

What’s coming next?

This integration is only our first step towards integrating HyperBid and GameAnalytics. We’re hard at work to bring you more powerful features and controls that connect your product analytics and your ad mediation. Stay tuned!
Leaving you with our VP for HyperBid: Ahmet Genc’s thoughts on the integration and the path ahead:

“Product analytics and Mediation should not be functioning in silos. Sharing the revenue data from HyperBid on GameAnalytics is only the beginning of bringing you powerful features that will allow you to make product and monetization decisions cohesively. There’s so much more to come.”

That’s all for now on the Product front. Get started on using the new integration with our integration docs (Unity, iOS, Android).

Over the last couple of years, we’ve released a new website, tools and features, completely new product lines, and even a mediation platform: HyperBid. We’ve been building your toolkit to not only perfect your titles, but to scale and thrive in an ever competitive industry.

So in this blog, we’re going to cover:

• A recap of all of the tools and products we’ve released.
• Our company structure and what’s new.
• And our plans for 2022.

But before we move on, we want to say a massive thank you to all of our users and supporters, and give a shout out to the crew behind GameAnalytics. We’re lucky to have an excellent team in our cavalry, and a great community to listen to – your ongoing support and feedback has helped shape our tools and our business.

Let’s get to it.

A look back: What we’ve done in 2021

We’ve really knuckled down over the last 12 months. If you’re an avid GameAnalytics fan and have been following our updates closely, then you’ll know we’ve been releasing products and new features left, right and centre.

To give you an idea of what we’ve achieved, here’s what we’ve done throughout 2021:

• Launched our sister company, HyperBid: It’s a mediation platform, built specifically for gaming. We crafted a tool which is committed to helping developers maximize their ad revenue. It’s currently in Open Beta, and you can sign up and get the full story in our update here.
• Released Growth FullStack, with Tenjin: We’ve created a brand new ETL tool. You can use it to bring your marketing and product data together. You’ll now be able to stack your data from different sources together to form the insights you need (without needing a data scientist or engineer). Read the full announcement here.
• Rebuilt Benchmarks+, as GameIntel: It’s a new market intelligence tool which lets you follow market trends in real-time, see which games have the best performance indicators, and supercharge your game research and ideation. It originally launched as Benchmarks+ in 2019, but we’ve layered in more data, features, and dashboards, as well as offer affordable pricing plans (and a free tier). Here’s our latest update.
• Updated our data services: The largest update we’ve done to our Data Services this year is our new Raw Export. With it, you can automatically export all of your games’ raw event data in JSON format, and pump this straight into your AWS S3 account. Here’s the full update.
• Integrated more ad revenue providers: We’ve been adding ad revenue data from a range of new partners over the last year. You can now keep an eye on your ad metrics from companies like Admob, Aequus, Applovin MAX, Fyber, ironSource.
• And much more: We haven’t forgotten about the small details either. We’ve been tinkering around with our products, tweaking and making them better. There’s new dimensions in our core tool, like our iOS Consent Status and Manufacturer. We redesigned our GameAnalytics mobile app, which you can also download on Huawei’s AppGallery. And we’ve reworked how we manage our identifiers, in response to Apple’s iOS 14.5 update.

We’re changing our structure

We’re no longer just your go-to analytics platform for mobile games. Although our speciality is bringing data and games together, we’re venturing forth into new areas of the game development industry, so we can give you the tools to thrive and succeed in the ever growing market.

We’ve grown from a three man team working on a passion project 12 years ago, to a mature SaaS provider to the game development industry. Our crew has almost doubled in size over the last year, and we’re intending to expand even further in 2022. And with this growth, comes restructure. We’ve had to adapt to how we work, build new departments, and become more agile in our strategy. So we have some news to fill you in on.

We’re now a remote-friendly company

We still have our bases in London and Copenhagen. But mid-2020, we decided to give our crew the option to work remotely. Covid-19 was a big deciding factor behind this. Lockdown made us (and many other companies) rethink how we work. And over the last 2 years, we’ve been introducing new structures, workflows, and templates into how to do this right.

But another deciding factor was talent. The tech industry is growing fast, and the perfect match is no longer around the corner. The world is changing, shifting online, and we plan on keeping up. Going hybrid not only lets us find new people from around the globe, but lets our staff have a better work/life balance, too.

We’re welcoming a new CEO

Our CEO, Ioana Hreninciuc, is taking a step back. She joined the company back in 2016, and during the last 5 years Ioana has helped grow our user base ten fold, laid the foundation for our products and restructure, and has also helped build an experienced, passionate team of experts, who are able to craft the tools you use today.

But it’s not quite goodbye. While she’s planning on taking some (much deserved) time off, Ioana will stay on as an advisor for the company, and will continue to guide and grow our team and products in the next phase to come. Meanwhile, our founder, Morten Wulff, will be stepping up as CEO fulltime to take her place.

It’s an understatement to say how lucky we’ve been to have such a talented person at the steering wheel. And we’re excited to continue our relationship further.

And what we’re doing in 2022

All of these changes to both our product lines and our team has laid the groundwork for the next step in our journey. We’re no longer just your trusted analytics company for mobile games. We’re paving the way for new tools and support for the game development industry.

So expect to see even more features and updates coming soon to all of our products. Make sure to sign up to our newsletter to follow this space. And if there’s anything you would like us to work on next, let us know here.

We’re coming to the end of the year, and what a year it has been. We’ll have a roundup blog coming out soon, but there’s still plenty to do and fill you in on before we start chatting about 2022.

Recently, we’ve had a few major updates across all of our product lines. Here are the highlights:

• You can now analyze ad revenue from AdMob in your GameAnalytics account.
• We launched a new mediation platform built for gaming teams, HyperBid.
• We also added a new DataSuite to our product family, Raw Export.
• Ranking data for over 80 sub-genres is now available in GameIntel.

So without wasting any more time with the intro’s, let’s dig into the main course.

What’s new in GameAnalytics?

We’ve created an integration with AdMob

We partnered with Google’s AdMob to bring you Impression level revenue data (ILRD) from their network directly to your GameAnalytics tool. All to help you analyze all your game’s data in one place, including insights about your ad revenue. Read our integration guides to learn how to get started:

• Overview article on impression events
• Unity SDK
• iOS SDK
• Android SDK

Over 2021, we’ve worked hard to bring onboard new partners for your ad data. So far, we’ve welcomed Aequus, Applovin MAX, Fyber, and ironSource, with many more to come. And if there’s any other ad network you’d like us to integrate with next, let us know here.

We’ve launched a new mediation platform

It’s all that we’ve been chatting about for the last week. We helped launch HyperBid, a brand new mediation platform built for mobile games. It’s currently in Open Beta, and you can get a sign-up bonus to kickstart your campaigns (rather than use your own capital).

Like we said, we created it specifically for gaming. With HyperBid, you’ll be able to:

• Get the highest bid, every time.
• Unlock higher eCPMs.
• A/B test your campaigns easily.
• Segment your players.
• And get setup quickly and easily (no faffing around).

We’ve gone into a lot more detail in our announcement article. But here are a few words from HyperBid’s Business Director, Ahmet Genc:

“As this platform was crafted by the experts behind GameAnalytics, it’s been built with analytics at its core. With GameAnalytics help, we’ve laid the groundwork for this platform, future-proofing its development – where we hope to truly bring together your product and monetization data. Our team has more than a decade of experience, so the crew know exactly what types of features and functions a game developer needs in their mediation strategy.

“With HyperBid, we want to make sure you can now build the best business from your game, and truly realize your monetization potential.”

We’ve released our new Raw Export

Raw Export is the latest feature added to our DataSuite family. It’ll let you automatically export all of your games’ raw event data in JSON format, and pump this straight into your AWS S3 account. What’s better, there’s barely any manual intervention. And it’ll package all of your data into a compressed file, containing unchanged raw events, with their properties and timestamps.

To give you an idea of how it’s different, here’s a comparison table against other DataSuite products:

We’ve gone into a lot more detail around this new feature here. And we have plenty more updates coming out regarding our DataSuite soon. So keep an eye on this space.

And we’ve added new features to GameIntel

We’ve been pretty quiet on the GameIntel front. But for good reason. We’ve added a bunch of new features, and polished a lot of the edges in our marketing intelligence tool. Alongside a UI refresh, you can now:

• Filter the charts by over 80 sub-genres
• Sort the ranks by specific metrics
• And unlock this (and more) in our new starter tier – only $99 a month.

There’s a lot to explain in this update. But in short, it’s the next step in creating your one-stop market research tool for the mobile games industry. You can get all of the details around the latest release here. Or dive right in and try it out for yourself.

What’s coming next

We have some big plans for 2022. It’s a bit early to go into the details. So make sure you subscribe to our newsletter to stay in the loop. We send monthly updates around our tools and any other game development news. Until next time!

Line yourself up, recruit. You can now track ranking games across more types of charts than ever before; made up of an entire new division of 80+ sub-genres. Including everything from ‘Snipers’, ‘Tower Defense’ through to ‘Romance Games’.

We have three main changes for you to get through today. In GameIntel, you can now:

• Filter the charts by over 80 sub-genres.
• Sort the ranks by specific metrics, like highest retention or longest playtime.
• Unlock this with our new Starter tier (only $99 a month).

There’s a lot to explain here. So gear up and let’s get started.

What’s new in GameIntel

1. Filter the charts by over 80 sub-genres

In addition to the standard App Store categories (such as hyper-casual, RPG, and Sports), you can now explore aggregated GameIntel charts for more than 80 additional sub-genres (like Tower Defense, Snipers, and real-time strategy).

We’ve categorized hundreds of thousands of games, and we compute these new charts for every country and feasible gaming genre. You now have much more granularity than ever before. Want to see what the best performing Shooter games are in Denmark? Now you can.

To get started, just log in and check the Top Games dashboard. You’ll see a new ‘GameIntel Genre’ dropdown option, right next to ‘Store Category’ (this is the standard chart). Click this new dropdown and pick your genre or sub-genre to load the new ranks.

So to give you an example of what this means, you can see all of the top-ranking tactical shooter games in the US on any given day.

We’ve created an aggregate ranking for each sub-genre
These sub-genres are exclusive to GameIntel. They don’t exist on the App Stores. So we’ve had to be a bit clever with how we created the ranking for them. We’ve done this in three ways:

1. Tagging more than 150,000 games with:

• Sub-genres: like sniper, tactical shooter, hyper-casual, and more
• Contextual data points: specific mechanics, platforms, audience, art style and more

2. Estimating metrics for top charting games:

• Estimation data: We use our data from over ⅓ of the world’s players to create industry-wide estimation models, and give performance estimates for top games’ metrics, like DAU, MAU, and Retention.

3. Analyzing the historical and global trend for each game to create a:

• Performance score: based on reviews, ratings, and more
• Visibility score: based on how many countries the game is published in, and how many times they ranked

And through machine learning, we use all of this data to create our own aggregate ranking for each sub-genre. That means you can now see how specific games and sub-genres are performing in the charts, instead of the standard App Store genres.

2. You can sort by metrics

Not only can you filter by different sub-genres, but you can now sort all of the top games in descending or ascending order by specific metrics.

When you check a top chart, you’ll now see a grid with many columns covering all major metrics like retention, DAU, ARPPU. These are all estimated figures for every game in the charts. So, do you want to see a list of Logical Puzzle games in the US with the highest D7 retention? Well, now you can do exactly that with just a couple of clicks. 

To give you another example, you can choose to “re-rank” all Sniper games in Russia in order of those with, say, the highest number of sessions. 

Here’s a full breakdown of what you can sort the charts by:

• Downloads
• DAU
• MAU
• D1 Retention
• D7 Retention
• D30 Retention
• Session Length
• Session Count
• Playtime
• Visibility Score
• Performance Score

3. And you can unlock all of this in our Starter tier

It’s in our new affordable pricing plan, which only costs $99 a month. And it includes everything we mentioned above.

If you’re already a GameIntel premium user (either indie or above), then you’ll see these updates immediately. But if not, you can unlock all of them on our Starter Tier. You can see what else is included and get a full pricing breakdown here.

Once unlocked, simply log in, head to one of our dashboards (like Top Games), and you’ll see the new filtering option as well as all of the new columns with each individual metric at the ready.

What’s coming next?

We have plenty more updates coming soon. We’ve been squashing bugs, categorizing more and more titles each day, and also working on some larger releases soon to come. Keep an eye on this space, or subscribe to our newsletter to stay in the loop.

We’re all about the analytics (there’s a clue in our name), and using them to help you grow your games. And we’re always looking for ways to make data work even harder for you. So we’ve added a new service to our already-impressive roster – Raw Export.

Here’s how it can help you turn your data into action.

Dive even deeper

With Raw Export you can automatically export all your games’ raw event data in JSON format, without any manual intervention. So every day it’ll ingest, preprocess, and deliver player data from your GameAnalytics account straight into your AWS S3 account. It even packages it up into a neat and tidy compressed file containing unchanged raw events, all still with their properties and timestamps. No fuss, no faff.

What can I use Raw Export for?

To get really up close and personal with your data using batch or streaming processes. You can carry out custom analysis of non-aggregated data, export it into your own tools, combine it with data from other sources, implement your own data pipeline… pretty much any data-related activity you can think of (within reason, of course).

It doesn’t stop there either. You can also use custom event fields – a set of key-value pairs you can add to all your events. You can only get this through Raw Export (it isn’t available in the GameAnalytics tool). Find out more.

How is it different from other GameAnalytics products?

Have a look at this table to see how it compares to our other Data Services.

Not sure if Raw Export is for you?

Check out this case study about how tech startup TapNation are using Raw Export to make faster decisions on game updates. You might also want to have a read of our FAQs.
We’re really proud of Raw Export – and all our other products – and we love talking about them (we’re super fun at dinner parties). So if you’d like to chat to us, just fill in this form and we’ll get right back to you.

Right, I’m sold. How do I get Raw Export?

Raw Export is one of our premium services. And that means you do have to pay for it. Because our mission is to help indie developers get their first hit by giving them access-all-areas analytics, our core tool will always be free. But adding paid-for services like this one means we can grow as a business. Which gives us more cash to make our free analytics product even more kickass.

The good news is that it’s really easy to order Raw Export through your GameAnalytics account. Just log in and click on ‘Data Services’ in the left menu to get started.

This is a slightly longer product update than you’re probably used to. The main thing is you need to update your Android SDKs, in anticipation for Google’s upcoming policy update around their identifiers.

But we have a lot more to get through, too. So let’s waste no time on intro’s, and tuck straight into our updates. Anything you want to read about in particular, feel free to jump ahead:

• Google is changing how you use identifiers for Android (update your SDKs)
• The above change has affected our Attribution Integrations
• We have a new SDK for Flutter
• We’ve added TopOn to our ad network providers
• We’ve also added new ad revenue metrics into our platform
• We’re giving our Explore tool a facelift

Let’s get to it.

First up, Google is changing how you use identifiers for Android

Privacy in tech is a pretty hot topic at the moment. It’s constantly evolving. Earlier this year, we saw Apple make changes on their iOS identifier. And now Google will soon be changing how developers use the Advertising ID (AAID).

You can read more about Google’s policy change here. But in short:

• You’ll see less Advertising IDs: If a user opts out of ad personalization, you’ll no longer have access to the Advertising ID (AAID, also called GAID). Instead, you’ll see a string of 0’s.
• Google is introducing App Set ID: This is to help you identify unique users for the purpose of analytics (among other non-advertising purposes). This identifier is still in ‘preview-mode’ at the moment. But it’s intended to potentially help you identify users between apps from the same vendor (so your portfolio of games). But it may be limited, and we don’t know how useful it’ll be yet. Here’s their docs.
• These changes will start soon: They’ll be rolled out in phases starting late 2021.

We’ve been preparing for this for a while. You’re going to need to update any SDK targeting Android devices ASAP, which you can do here. But here’s some more information about the changes, and how we’re getting ready.

How we’re ready for Google’s upcoming release

We’ve been preparing for this ever since Apple’s announcement for iOS 15. But before we go into the nitty-gritty details, we need to give you a quick recap on how we track users (feel free to skip if you’re already up-to-speed).

How we track users on Android

At the moment, we create a unique identifier for each device that sends data to GameAnalytics. We call this the GameAnalytics User ID. We usually get this value from a device identifier. And if that’s not available, then we create a random User ID when that person installs an app, and we then assign it to that device.

For Android, our SDK has used Android’s Advertising ID (AAID) for identifying unique devices (that is, assigning the user_id).

In preparation of Google’s upcoming release, we have made changes in how we identify devices. Before, we used AAID. But now, our SDKs will instead generate a randomized user ID on the first app launch and keep using this user_id for all future activity.

How this affects you

1. For new Android installs in your game using GA SDK v7.+ → Your game metrics shouldn’t be affected. We’ll assign the new user_id based on our new identifier logic.
2. For existing Android installs in your game which update to GA SDK v7.+ → These will continue to use our previous identifier logic (that is, we’ll continue to assign user_id from AAID). This may impact your metrics when Google restricts AAID. This means for the players that do not consent, Google will not return AAID, and it’ll change our user_id to a random one. You’ll see them as new users in GameAnalytics. And for a short time during the transition period, you may see an impact on certain metrics like retention, new users, returning users.
3. For existing Android installs in your game which don’t update → If users are on SDK 6.6.0+, then their devices should start using a randomised identifier. If their SDK is below 6.6.0, then for the users that do not consent, they will all end up with the same identifier (0’s). Unfortunately, these will have a high impact on your metrics.

You need to update your SDK as soon as possible

To avoid scenario three, we highly recommend you update your SDKs. It’ll make your transition a lot smoother when Google releases their update.

Update your SDKs here. Please note, for Unity, you’ll want version 7.+.

This has impacted our Attribution Integrations

At the moment, we support postbacks from all of our attribution partners (you can read more about this here). Which means when one of our attribution partners informs us of an app install, we can stamp our events data with attribution dimensions (essentially where that user came from). This lets you filter your data in GameAnalytics by different install campaigns, and other install dimensions you may use.

We’re able to do this by using identifiers that we and our partners track. It lets us match all of the data together accurately. But as the industry is shifting (take Android’s upcoming AAID changes as an example), we’re no longer able to rely 100% on these cross-app identifiers. Which affects how our attribution integrations work.

We’re still evaluating the impact this will have on our attribution data. But we’ve listed out what this means for you just below.

What does this mean for you?

• iOS → The integration will not work optimally for devices that are on iOS14.5+.
• Android → Currently this still works as expected, but we anticipate that this will be impacted when Google releases their new AAID policy later in 2021.

For iOS15, Apple suggests that developers should add a URL to also send the SKAdNetwork conversion postback. This is Apple’s own solution for Attribution. We’re currently planning and working on solutions to provide insights into SKAdNetwork data (conversion values etc.).

Other updates to note

We’ve released a new Flutter SDK

Our family of SDKs is growing. We’ve just created a new one for Flutter, Google’s UI toolkit for crafting beautiful, natively compiled applications for mobile, web, and desktop from a single codebase.

Our SDK currently supports Android, iOS, and Web Flutter builds. It uses native Android and iOS libraries which means it will send native device identifiers with the events.

To get started, you can download and follow our integration guide here.

We’ve added TopOn to our ad network providers

We’ve been adding more and more partners to our list of ad revenue providers recently. At the moment, we’re working with MoPub, Fyber, ironSource, Aequus and Applovin MAX.

And in the next few days, you’ll also see TopOn added to the mix. You can find the docs to get started here: Unity, iOS, Android. And once you’re all suited and booted, you can head straight to the Ads Dashboard in your GameAnalytics account for a predefined view of ad revenue in your game. Or query for the metrics data in detail in the Explore Tool.

We’ve also added new ad revenue metrics

We’ve added two additional ad revenue metrics in the Explore Tool: Ad Revenue (Total) and Impressions (Total). If you’ve enabled impression events from multiple supported providers in your game, then these metrics will give you a combined view of your impression-level data.

We’re giving our tool a facelift

Lastly, we’ve redesigned the Explore Tool in our GameAnalytics platform. We’ll soon release the early versions of this new updated feature inside GA Labs. With the early designs of our Dashboards feature soon to follow in a couple of months.

We want to build the next-gen analytics tool. And this is the next step to rebuilding and redesigning our platform. These are still early-stage designs. So if you have any thoughts on our new look, then we’d love to pick your brain. Let us know what you think.

That’s it for now. As we’ve mentioned, we’d love to hear from you. So share your feedback and ideas here. And when you’re ready, log into your account to get started.

Roll out the carpets and call the paparazzi. We have a big announcement we can’t wait to share with you.

We’ve teamed up with Tenjin and launched Growth Fullstack – a new ETL tool that’ll help bring your marketing and product data together. So you can now get more granular insights about your players, and improve your advertising and performance campaigns.

Growth Fullstack will help you overcome new challenges in the mobile marketing world. How? By turning your data into insights. Here’s everything you need to know.

What exactly is Growth Fullstack?

A lot of developers use analytics (so GameAnalytics, in this instance). And a lot of those same customers use attribution (let’s say Tenjin). But at the moment, there’s a wall between these services. With data working in parallel, but not together.

That’s where Growth Fullstack comes in. It’s an ETL tool that, as it stands for, will let you extract, transform, and load your player datasets from different sources (like Applovin and Tenjin) into a few different Storage and Data Warehouse platforms (like Google BigQuery, or Amazon S3). Which you can then use to merge and cut up the data (using tools like Google Data Studio or Tableau).

Our new ETL bridges the gap here. It makes it possible to bring all of this data together.

Growth Fullstack tackles Apple’s latest update

When Apple released iOS 14.6, IDFAs quickly became almost useless. And it was suddenly a lot harder to scale your apps and games using good old-fashioned techniques that we all know and love. It especially affected indie developers and SMBs (small and midsize businesses).

It caused a big gap in everyone’s campaigns and strategies. Developers and studios were stuck on how they could use their data, and how they could get actionable insights they needed for their campaigns.

The industry demanded something new. So we listened.

It gives developers flexibility with their data 

There isn’t a one-size-fits-all solution out there for managing data. It’s not that straightforward. So what’s great about FullStack is that it gives developers the building blocks (stacks) they can use to create what they need. It’s completely flexible. How you then use your data is up to you. But the possibilities are endless.

We’re excited to see what you guys use it for. In the past, you would need to have a data scientist or engineer to even think about doing this. But now you don’t.

Here’s an example, to help paint a better picture of what you can do.

Let’s look at how SKAdNetwork adjusted to iOS 15

iOS 15 marks the start of a new Apple-centric attribution model on iOS devices. Developers now have all of their SKAdNetworks data (e.g. the source app ID, which hasn’t traditionally been shared by ad networks, until now). But also, these developers (advertisers, in this instance), will be able to compare the ad networks reported data with what Apple reports to them.

Which is great. But you can probably expect to see some discrepancies in this data. Using our Growth FullStack, we stack this data together to form the insights you need.

How to get started

What’s especially great about this is that you don’t need any dedicated resources or data teams. We have training guides and the tools you need to get up and running.

To get started, you’ll need to:

1. Give us some information about your current stack
2. Pair up your favorite Data Source with the Data Destination of your choice (feel free to check out our recommendations).
3. Then when you have your data, you can connect it to any data analysis tool of your choice. You’ll also get free training for this, so no stress there.

How much does it cost?

You only pay for the ETL service. Connecting the tools, and all of the training is on us.

A match made in heaven

It made sense to buddy up with Tenjin. Developers need to make the most of their marketing and product data, without any barriers. It was a no-brainer to come together and solve this industry-wide problem. 

A lot of developers in the industry use both of our free platforms. And we both share a mission to help every developer in the industry. So we’re excited to come together to help apps grow in the new privacy-first world. 

If you fancy signing up, or just want to learn more, then get in touch with us. We’d love to find out how we can help you.

Earlier this year, Apple released iOS 14.5. It was the dreaded update among all app developers, studios, and publishers. It meant that if you wanted to access a user’s mobile identifier (called IDFA), you had to specifically ask for their consent.

If you’re not sure why this is important, the IDFA is basically used for advertising purposes. When Apple released the update, pretty much every user now needed to opt-in (rather than opt-out), which had a huge impact on advertising and ad revenue. (More about this here.)

But we’ve been seeing some interesting findings around the opt-in rate for mobile games. Which is what we’re going to cover in this blog.

We have data on Opt-in Rates

We’ve read tons of articles and blogs within the industry over the past few months. All speculating what they think the Consent Opt-in Rate would be – especially for games.

And for us, we don’t need to guess anymore. We have the data.

Here’s what we’ve found:

Opt-in Rate

How many % of players (who were asked) chose to consent.

Opt-in rate = 43%

You read that right. We’ve shared our findings on how we came to this result below. But to understand the full picture, we need to look a bit deeper.

iOS identifiers

To know just how impactful this update was, we first need to learn how 3rd party services track iOS users (including GameAnalytics) via device identifiers. If you’re already up-to-speed on this, then skip right on.

IDFA (identifier for advertisers)

The IDFA value is unique across all iOS apps on a device. It plays a crucial role in earning money from your ads (and does much more), as it lets you track data from different apps and services on the same device, and then later correlate all of that data to the same device/user.

This identifier would let you collect data from lots of different sources (like install attribution) which you could use in a data warehouse. And with this data, you could optimize your gameplay, monetization strategy, and more.

For every device that has iOS 14.5 onwards, you can only collect this data if the user opts-in. And with these changes, many services (including Facebook), decided not to use this identifier at all.

IDFV (identifier for vendors)

The IDFV value is unique across all iOS apps from the same vendor on a specific device (so an app developer account, for example).

You can’t use this to correlate data from different app vendors (so games from different studios or developers). As an example, you can’t use it for install attribution, as you would need to track an identifier from the specific game showing the ad, through to the advertised game being installed. It’s a bit complicated. But in this case, there are too many vendors involved, so the IDFV wouldn’t work here.

But what the IDFV does do is let you collect and correlate data across your own portfolio of games (if they’re published from the same company account). And it works fine for analytics purposes for that specific app, too. You can always get access to the IDFV value without asking for consent.

Here’s some info from Apple’s guidelines:

“The ID for Vendors (IDFV), may be used for analytics across apps from the same content provider. The IDFV may not be combined with other data to track a user across apps and websites owned by other companies unless you have been granted permission to track by the user.”

Random identifiers

Some services use a random string as the user ID which is created in the app when launched for the first time. You shouldn’t compare this to creating a fingerprint, as Apple won’t let you do this.

It’s simply a randomized string (often in a GUID format). If the user of the app were to reinstall, then an identifier will be created again and they would be seen as a new user in terms of metrics. It cannot be correlated across apps on the same device.

For GameAnalytics, we’ll use a random string user_id as a backup in certain cases, or on specific platforms where it’s used exclusively.

A lot of services still rely on IDFA

So as you know, with iOS 14.5+, all games need to ask for consent to get the IDFA. A lot of services are still using the IDFA. Adjust, for example, shared their documentation on how to increase the opt-in rate for IDFA, to try and track more users.

So these services still use IDFA data, specifically to model user behavior, and then use this to predict the non-IDFA users’ behavior. For example, if 40% of users behave in a certain way, then it’s likely that the other 60% have similar patterns.

So the higher the opt-in rate, the bigger the sample size, and the more accurate their models.

We’ve already moved to using the IDFV exclusively for the user ID. Alongside this, we now only attempt to call the IDFA value if the user has given consent. We only use the IDFA when processing or matching attribution callbacks from other services (like Adjust). Or to share the data (for a specific game studio) via our Data Services.

Introducing ATT (App Tracking Transparency)

For you to know how many of your users opted-in, we need to go over how Apple introduced ATT (App Tracking Transparency).

Apple released the ATT framework in iOS 14.0, but they waited until iOS 14.5 before you needed to ask for consent. This is important to know, as the data between 14.0 and 14.5 can be a bit misleading.

In short, the ATT framework can report the current AuthorizationStatus at all times. There’s more on this here. But to give you an idea of what this means, a device can report four different AuthorizationStatus values:

Back to the opt-in rate details

That was a lot of info. Well done for getting this far! In the following table you can read more specific details on how we queried the data to derive the opt-in rate.

The results

Worldwide consent status distribution

Opt-in Rate was 43% worldwide.

U.S. consent status distribution

Opt-in rate of around 36% in the U.S.

Final thoughts

So there we have it. Our numbers are much higher compared to, say, what Flurry is reporting. And there are a few different reasons as to why.

• We calculate differently. So how we calculate the results may differ slightly (what users or apps we included) to what Flurry used.
• GameAnalytics is purely focused on games. And a lot of these games are monetizing heavily via ads. They depend on efficient install attribution. And a lot of them use Adjust (who have been actively encouraging app developers to ask for consent).
• We see a higher restricted status in our data.

Consent status in GameAnalytics

You can get your hands on these numbers as well.

In GameAnalytics, it’s easy to both track and visualize your player’s consent status. Simply install the latest SDK and the consent status will be tracked automatically.

Read our previous blogpost for more details.

Our collection of Ad Revenue providers is growing. A couple weeks back, we were shouting about Applovin MAX being added into the mix of things. And this time, we’re thrilled to let you know that we’ve just partnered up with Aequus. Meaning you can now analyze your ad revenue from Aequus in your GameAnalytics account.

Again, this is another great addition to our analytics platform. Here’s the docs to get you started. And if you want to learn exactly what this means for you, then read on.

Let’s get to it.

What’s new in GameAnalytics?

• We added support for impression-level ad revenue data from Aequus (like we did earlier for MAX, MoPub, Fyber, etc)
• This means you can now:
  • query and filter data for ad revenue metrics from Aequus in the Explore Tool
  • optimize ad revenue from Aequus using A/B Testing
  • see the most popular metrics related to ad revenue data for Aequus in our Ads Dashboard. If you are using more than one ad network provider, this will show a combined view.

What is Aequus?

Aequus is a leading mediation and bidding platform. A place that’ll help you buy and sell your ad space, and help you make money from your ads.

A couple of words from Aequus:

“We give publishers a neutral, open and transparent bidding and mediation platform. Our platform is built to help publishers and developers have the freedom to work with any demand partner they choose. Keeping our pricing and bidding model clear and transparent, game publishers have the best tools possible to take their ad monetization to the next level”

How does Aequus work?

It’s purely a mediation and bidding platform. But Aequus does things a little differently. Which is why we’re so eager to partner with them.

Here’s some more words from Aequus:

“We’ve pushed aside the blind revenue sharing pricing model (which is fairly common with other providers). Besides, we’ll never have our own demand — which usually creates a conflict of interest — as we don’t publish games to compete with our partners. And on the demand side of things, we let publishers connect directly with any network or DSP they choose. Aequus doesn’t charge bidders a fee to compete inside the platform. We just focus purely on mediation and bidding.”

How does it work?

Here are the links to all SDK docs:

• Unity
• iOS
• Android

Once you’ve read through our docs and downloaded all of the correct SDKs, then you can get started. It’s a fairly straightforward implementation. When you’re ready, log into our platform and:

1. Head to the Explore Tool.
2. Open the Metric Picker.
3. Select ILRD events > Ad revenue (Aequus) or Impressions (Aequus).
4. And then feel free to filter the data down even further (by different dimensions like country or platform).

What does this mean for you?

With our new partner, it means:

• It’s now easier for you to refer all your game related data in one place (by including ad revenue reporting from different ad network providers).
• You can analyze in detail the performance of your ads: e.g how much revenue per user is generated, whether they perform better in some regions over the others, and more.
• And you can test different variants using A/B Testing and see exactly how these impact their ad revenue (optimize for player LTV).

How will this integration help you?

Other than the obvious reason that we wanted to expand our networks, we were really excited about working with Aequus. They have a neutral approach, which means developers and publishers can bid fairly, without the fear of conflict of interest getting in the way.

Our partner has a few more words to say around this: 

“We’re thrilled about this new Aequus integration within GameAnalytics. It means publishers and developers will be able to see and work with all of their data in one place. There are a lot of gaps in the industry at the moment, and we think this is a first step into helping developers make better decisions about their user-level ad strategy and campaigns.”

A while ago, a bunch of you asked us to add Applovin MAX to the mix of ad networks we integrate with. Well, we’re thrilled to announce that we’ve crossed the finish line, and you can finally analyze your ad revenue from Applovin MAX in your GameAnalytics account. There’s now nothing stopping you from making more informed decisions around your monetization strategy.

That’s the biggest news in this update. So if you’re struggling to sit still and want to get started right away, then head to our docs here to grab the integration guide and go go go.

But if you fancy digging into the details, then read on.

What’s new in GameAnalytics

Including the news we mentioned above, here’s what’s changed in GameAnalytics and what you can expect to see next time you log in:

• We’ve added support for impression-level revenue data (ILRD) from Applovin MAX. Which means you can now track your ad revenue metrics from MAX directly in the GameAnalytics tool. Including slicing and dicing all of your ad data in our Explore Tool.
• Also, you can now see the most popular metrics related to ad revenue data, including MAX, in our Ads Dashboard. Recently, we gave it an uplift making it easier to view all your ILRD metrics. So if you’re using more than one ad network, you’ll get a unified view of all your ads data.

Why we made these changes

Ad revenue plays a huge role for any game developer looking to monetize their game. So it’s important that we make it as easy and accessible as possible for any developer to both track and optimize their ad revenue.

Throughout the past year, we’ve been integrating with more and more ad network providers to help studios skyrocket their monetization game. Many of our users requested ad revenue data from MAX, as it’s among the most popular providers. So when Applovin MAX added SDK support for ILRD, we decided to flip the switch and turn on reporting and tracking in GameAnalytics.

What does this mean for you?

• This integration now makes it easier for you to see all of your game-related data in one place (by including ad revenue reporting from different ad network providers).
• You can now analyze in detail the performance of your ads. For example, how much revenue per user you generated or whether your ads perform better in some regions over the others.
• And you can test different variants using A/B Testing and see exactly how these impact the ad revenue (and optimize for player LTV).

What’s coming next?

• Soon, you’ll have an option to save and share your queries in the Explore Tool with other users in your organization. This should boost the collaboration in your team and let you save some precious time.
• We’re also working on integration with another ad network provider. In a while, you’ll be able to see and track ad revenue data from Aequus. Stay tuned!

And that’s it for this product update. If you’d like us to add some other ad networks, have your say on our feedback portal. Or jump straight to the GameAnalytics tool to start analyzing your ad revenue (just don’t forget to integrate the SDKs first).