Appsflyer vs Firebase: Which is Better for Attribution?

Attribution is a fundamental question mobile apps need to answer. Unlike web attribution, mobile attribution is hard. Really hard. This is why you will need a tool to help you do it and why we will look at how AppsFlyer vs Firebase compare in this field.

Both of these tools can offer quite a bit beyond attribution but we will stay focus on this fundamental question. Let’s start by setting expectations.

Everything in Mobile is Harder, Be Ready for It

First, let’s set expectations. Mobile is hard. Everything is harder when you’re working with mobile apps. Adding new tracking, attribution, privacy, etc. 

Let’s look at one area, tracking changes, and compare it against web apps. On web, you would write the code, test it in staging, and then publish to production. Let’s assume it takes one sprint so everything takes 2 weeks (the length of the sprint). Critical fixes could be done in a day or less. Users would see the latest changes within minutes or hours at the latest.

On mobile, it would also take 2 weeks to go through the changes in a sprint. However, you would need to push an update to your app which might take a day or so to get approved by Apple/Google. You would then need to wait for users to update the apps on the devices which might take a few days depending on how many have auto-update. Worse of all, not everyone will update right away and some users might never see the changes.

This has meant that my clients with mobile apps always had a lag of around 3-4 weeks for the latest tracking changes. This doesn’t just apply to new things but also bug fixes. Mobile needs careful planning to avoid this lag.

Privacy is also tougher on mobile. While some users have ad blockers on web, this isn’t as common as the privacy restriction that someone like Apple can impose. This is likely to get harder as companies double down on privacy.

Finally, event volumes tend to be higher on mobile especially for consumer companies. Higher event volumes limit the tools that you can use and makes it harder to get started because you need a higher investment just to join the game. B2B web companies could try different tools without much worry but consumer companies with high volumes need to think through limitations and overages.

Based on this context, we can explore how Appsflyer vs Firebase stack up for mobile apps. Let’s start by looking at the main difference between them: attribution models.

What’s an Attribution Model Anyway?

On web, we typically attribute using UTMs parameters or something else like a landing page URL (think offline ads). On mobile, these concepts aren’t as clear because of the “black box”.

The black box is what happens when a user goes to an app store. They land on your website, click on “Download our iOS app” and then get redirected to the Apple Store. What happens here, isn’t quite obvious.

Eventually, they install your app and open it. This is where we can now see the user again. Making the connection between the user who visited the website and the user who installed the app is what attribution models are supposed to do.

A good attribution model will take several factors into consideration. Device IDs, Fingerprinting, UTMs, IP Addresses, etc. All of this happens in the background and you simply see the end result: attributed users to a campaign or link.

AppsFlyer has a fantastic model which they have built with their own data. This is what makes them primarily better for mobile attribution

Firebase supports some aspects of mobile attribution but they are more limited. Google Play attribution seems to be fine (within the Google ecosystem). The same goes for Google Ads. Apple Search ads seem okay with some tweaks. It’s unclear if Facebook ads will work through Apple.

These limitations happen because Firebase hasn’t built its own attribution model. Instead, they rely on UTMs which aren’t as reliable on mobile.

What About Other Things Besides Attribution?

Besides attribution, where Appsflyer is better, the comparison isn’t so one-sided. Firebase has worked on building fundamental reports like segmentation, funnels, and cohort analysis. I think these reports are better in Firebase.

Appsflyer has a few of these reports but they aren’t as powerful as what Firebase offers. Firebase also collected a lot of data out of the box (ala Google Analytics) which becomes quite handy.

You also need to keep in mind that Firebase offers other things besides analytics. It includes everything you could ever need to develop a mobile app. This alone can make it worthwhile if you don’t some of these major pieces.

Firebase even becomes a closer comparison to a tool like Mixpanel or Amplitude which I have covered quite a bit in this blog.

Appsflyer vs Firebase in Pricing

Finally, pricing. Pricing matters especially for high volume apps which I talked about in an earlier section. 

Firebase Analytics is free just like Google Analytics. Other elements of the Fireabase platform are paid but the data and attribution products are free.

Appsflyer has plans depending on what you need. The plan that includes attribution (Growth) costs $0.06 per conversion. A conversion is typically an app install from a paid campaign. Organic installs do not count.

There’s also a world where you use both tools. Firebase for the bulk of your analysis and Appsflyer for attribution.

Finally, if you’re interested in other tool comparisons, you can follow these links:

One more thing before you go! Do you know how to get more insights out of your data? 

All companies are sitting on a goldmine of data that they haven't fully explored. It's not about technology or capturing more data. The key is to learn how to make the most of your current data and convert it into actionable insights. This is the main idea behind my first book, The Data Miage: Why Companies Fail to Actually Use Their Data

I'm excited to announce the release of the book through all major retailers. If you're interested, you can download the first chapter for free using the form below. You'll learn what the best data-driven companies do differently and how to make sure you're playing the right data game.