As marketers, our jobs depend on results. At the end of the day, that’s all that matters. Unfortunately, results in digital marketing can be slippery and elusive. Enter, mobile app marketing attribution, and tracking.
Theoretically, it should be easy to determine things like where quality users and installs come from, then use this information to double down on specific strategies and supercharge our efforts. But in reality, attributing credit to certain marketing actions is difficult.
It’s far from impossible, though.
Mobile app download attribution
By understanding and applying the right mobile attribution tracking model to app marketing, we can start understanding the journey most of our individual customers are on, the mindset they have, and potentially, the paid ad campaigns that drove him or her to take action.
If you’re having trouble determining who’s downloading your apps, where they’re coming from, and why some of your ads work better than others, keep reading.
What is Mobile Attribution?
Attribution, in general, is the act of crediting value to the specific marketing initiatives that led to them. Mobile attribution is the act of applying this same process to the world of apps.
Let’s say your company has developed a graphic design app that lets users craft stunning images for Instagram. In order to properly market and sell your app, you need to know who your highest quality are and how they usually find your solution in the app stores.
The mobile attribution process will guide you through customer journey analysis and help you assign the appropriate amount of credit to each touchstone in the journey, based on the attribution model you’ve chosen for your app business. (More on attribution models below.)
Mobile attribution is important because it allows you to understand which aspects of your marketing strategy are working and which need to be adjusted. If you notice, for example, that most customers download your app after viewing a specific Facebook ad, you can reasonably expect to boost revenue by increasing your Facebook marketing budget and leverage the same messaging style of that ad.
Unfortunately, while crucial to app install growth, mobile attribution has numerous challenges including:
- Technology: Mobile attribution is complex and relies on tracking, at a user level, a single person. This is done by multiple methods such as tracking the user’ device unique identifier (IDFA in iOS, and GAID in Android) as well as “fingerprinting” which means tracking multiple parameters about the user (the IP address, OS version and more). With privacy concerns rising, persistently identifying and tracking a user is becoming harder which makes attribution more challenging. Read more on the potential deprecation of IDFA here.
- Attribution Models: There are numerous attribution models that can be applied to the mobile attribution process. Each has its merits and potential pitfalls. Choosing the right model for your individual business can be a challenge.
- The True ROAS (tROAS): as ads don’t just drive value by getting users to tap on them and install the app, direct attribution models don’t take into account in their ROAS (return on ad spend) calculations installs that resulted by an ad in an indirect way. For example, a user that viewed an ad (and didn’t tap on it) and then searched for it in the store and installed it. Another example could be an ad that is driving a large number of first-time installs, pushing the app higher in rankings, thus driving a lot of installs from users that were not even exposed to the ad. Looking at direct ROAS alone could lead UA teams to make the wrong decisions and stopping strategically important campaigns.
It’s important to note the main difference between mobile attribution and its web-based counterpart. When a user engages with a company via the web, marketers are able to use cookies, pixels, and other tools to track engagement.
The mobile attribution process is distinct because the app stores make it impossible to track the user journey. Fortunately, mobile attribution tools (discussed in detail below) have solved this issue using fingerprinting technology and unique device identifiers to accurately track users who clicked on specific mobile ads.
How Mobile Attribution Works?
While the act of installing mobile attribution technology and properly using the data it gives you may be difficult, the actual attribution process is fairly straightforward:
- Step 1: First, a user discovers an app via a mobile ad and clicks on it. These ads can come from Facebook, Google, or any other ad network.
- Step 2: Once an ad is clicked on, a unique ID is sent to the app developer’s mobile attribution tool of choice containing specific details about the user. These details include the user’s unique device identifier (GAID/IDFA), IP address, internet browser, phone operating system, and a timestamp.
- Step 3: Next, the user downloads the app from either the Apple App Store or Google Play Store and opens it on their mobile device. When this happens, the same details listed above are collected a second time and cross-referenced with the previous data.
- Step 4: The mobile attribution tool then compares timestamps for both actions: clicking on an app ad and actually downloading it.
- Step 5: The conversion is then properly attributed to the right ad based on the attribution window (the time between ad click and app download) previously set by the app maker.
- Step 6: the attribution partner SDK will track user behavior within the app to measure in-app purchases and Life Time Value, in order to provide a Return on Ad, Spend figure for the ad.
Once your mobile attribution tool is up and running, it will do all of this hard work on autopilot, quietly feeding you data. UA team’s job is to properly interpret the information it sends you and focus spend on the most valuable campaigns and ads.
The Attribution Models
Choosing the right attribution model is vital to the success of your mobile attribution efforts. Using the wrong model can easily lead to inaccurate conclusions about who uses your app and how they discovered it. The attribution models listed below are the most commonly used:
1. First Click Attribution
As its name suggests, the first click attribution models give 100% of the credit for an app install to the user’s first point of contact. This model isn’t used very often
When to Use: First click attribution is great for measuring brand awareness. If you want to track how effective your marketing efforts are at engaging new potential customers, use this attribution model.
2. Last Click Attribution
The last-click attribution model is the exact opposite of the first click model we just discussed. Last click attributes all credit to the final point of contact a user has with an app’s marketing efforts before conversion. This is the most common attribution model and the easiest to use.
When to Use: Last click attribution can tell you a lot about which marketing channels are most effective. If you want more details regarding conversions, use last-click attribution.
3. Position-Based Attribution
Rather than attributing app downloads to either the first or last point of user contact, position-based attribution models assign equal credit to both. The engagement points between the two, though, are ignored.
When to Use: This attribution model gives app developers the benefits of both first and last-click attribution models. It will show you which channels are best for reaching your target audience and which offer the highest conversion rates.
4. Linear Attribution
The linear attribution model, like the position-based model we just discussed, is a multi-point model. Linear attribution assigns credit to every touchpoint a user comes in contact with, from initial engagement to conversion, in equal measure.
When to Use: This model isn’t used very often. It can tell you which touchpoints users come in contact with. But because credit is distributed equally, it won’t tell you which are most effective. As such, we don’t generally recommend this attribution model.
5. Time-Decay Attribution
We also have time-decay attribution, a model that distributes credit to every touchpoint, but not in equal measure. Instead, the touchpoints closest to conversion receive the most weight. For example, a customer journey that included four touchpoints might distribute credit like so:
- First Touchpoint: The first point of contact receives 10% of the credit.
- Second Touchpoint: The second point of contact receives 20% of the credit.
- Third Touchpoint: The third point of contact receives 30% of the credit.
- Fourth Touchpoint: The fourth point of contact receives 40% of the credit.
When to Use: The time-decay attribution model will tell you which marketing channels lead to conversions and how effective each of them i at turning random users into paying customers. This is a good attribution model to use unless you’re running top of funnel (TOFU) marketing campaigns because initial contact is given the least amount of weight.
6. View-Through Attribution
View-through attribution is a model that takes into account users that viewed an ad and then chose to install it. This is a model that was offered by self-attributing networks such as Facebook to credit their ads for the brand-driven installs they managed to drive (users installing an app indirectly through app store Search or Browse after just viewing an ad without clicking it).
This model is not technically possible to implement without a network that collects and provides view-through figures (such as Facebook). Given rising privacy concerns, Facebook announced they’ll stop making this data available at the user-level.
Think you got the UA side of things covered? Check our complete eBook to help you master your creative optimization side:
Attribution and ASO
Mobile attribution is just one piece of the Mobile Growth puzzle. As such, it’s important to realize how it fits into the bigger picture of effective app marketing.
No matter what you’re trying to promote, be it an app, a physical product, or a professional service, you need to understand ‘return on advertising spend’, also known as ROAS. In a nutshell, ROAS allows marketers to know, with reasonable certainty, that ABC dollars invested into advertising efforts, will yield XYZ benefits in return.
Mobile attribution can help with this because it will pinpoint for developers where users come from and how their apps are discovered. This information can then be used to inform marketing decisions and craft app store product pages that convert at higher rates.
For example, if your mobile attribution efforts have led you to believe that most of your traffic comes from Facebook ads, you can create an app store product page that caters to this specific group of people, thus improving ROAS along the way.
Half of the ROAS calculation is dependent on the cost per acquisition. That cost in turn is reliant on the conversion rate of your App Store or Google Play page, which is driven by your creatives and messaging on-page. As a UA person trying to increase ROAS, without improving your user acquisition costs by increasing app store conversion rates, you’re working on only half the ROAS equation. Use a solution such as Storemaven to methodically increase your paid conversion rates.
Now we’ve come full circle: mobile attribution can be used to identify ROAS, which can be improved by implementing standard ASO best practices like optimizing your app’s product page.
The Top Mobile App Attribution Tools
Accurate mobile app attribution relies on attribution tools. Without these solutions, it’s nearly impossible to give proper credit to each of your marketing initiatives. Here are four top mobile attribution tools you should consider investing in:
- Adjust: Adjust is the “industry leader in mobile measurement.” That’s why it’s trusted by over 32,000 apps around the world, including Rakuten Viber, Runtastic, and Zynga. As an app developer and/or marketer, you need access to the data behind every acquisition, which is exactly what Adjust gives you. Use this solution to track every channel and discover which perform best, link specific users to specific marketing campaigns, and spot customer trends quickly and easily.
- Appsflyer: Appsflyer takes a customer-centric approach to provide app developers with accurate attribution data. Join top brands like McDonald’s, HBO, and Nike and use Appsflyer to attribute every single app install to the marketing campaign and/or media source that produced it. The solution’s analytics dashboard will tell you the networks or channels, ad types, ad groups, and ad creatives that best produce customers. The platform is also robust enough to handle TV, multi-touch, and retargeting attribution.
- Singular: Singular is powering marketers to grow faster with next-gen attribution and analytics. Leading marketing teams from LinkedIn, Rovio, Microsoft, Lyft, Twitter, EA, and more rely on Singular to get a complete view of their marketing performance. Singular is the solution to drive faster growth for your apps by combining mobile attribution with the industry-leading cost aggregation, including thousands of integrations, easy set-up, accurate and flexible analytics, plus automatic loading directly into your BI tools.
- Branch: Working with Branch for mobile attribution is like wearing a pair of x-ray glasses because it tells users so much about the customer journey. Brand uses a “people-based” attribution system that makes it easy for app developers to “connect touchpoints from every channel with conversions on any platform.” In other words, Branch is a single source of truth that tells app developers where a user first came in contact with their brand, which channel led to conversion and every piece of marketing material he or she consumed along the way.
- Kochava: Lastly, we have Kochava, a powerful mobile attribution platform that combines configurable attribution options and a multi-view analytics dashboard into one rock-solid solution. Using Kochava, app developers can easily determine which marketing channels provide the greatest ROI and optimize their efforts to produce higher revenue. The app also includes user segmentation and A/B testing features so that developers can experiment with different strategies.
In Conclusion
As we’ve seen, mobile attribution is an important part of your overall ASO strategy. By investing in an attribution tool like the ones listed above, you’ll be able to learn who your customers are, where they’re coming from, and why they respond to some ads and not others.
This is important information. Fortunately, you now know exactly how to find it. Simply choose a mobile attribution tool, pick the attribution model that suits your goals, and adjust your marketing strategy accordingly.
Just remember, while powerful, mobile attribution is one piece of the ASO puzzle. To significantly boost ROAS, you need to take the information your attribution tools tell you and improve every aspect of your ASO efforts, including your app product page. Good luck!
