Juniper Research estimates that a total of 160 billion apps will be downloaded in 2017. Even so, the market still has room for expansion. Usage is on the increase: 90 percent of smartphone time is spent in apps versus 10 percent on the mobile web. It is therefore logical that an increasing number of apps are under development, leading to a corresponding rise in user acquisition marketing budgets (UA).
With such budgets, the mobile attribution analytics market is also growing. If you are going to spend a large sum of money to promote your app, you will also want to know the best way to spend it. Which channels provide the best users? For app marketing, this is less simple than it seems. As downloads are offered by a wide range of app stores, it simply isn’t possible to follow users after ‘the click’. And without special tools, it is difficult to attribute the results of your marketing efforts. In this article, you will find more background information about how this situation occurs and what the most important PPIs are. How can you use these for promoting your app, what tools are currently on the market, and how you can implement this data for fraud prevention and app optimization?
Facebook and universal app campaigns
There is a reason why most of the current app marketing budgets end up being used for Facebook or Google universal app campaigns. Both of their targeting options and engagement results are highly regarded.
Both Facebook and Google offer special software development kits (SDKs) that you can integrate into your app. These allow you to measure the number of installs and therefore the effectiveness of your ad campaign. In addition to this, you can track a limited number of in-app events and use app data to organize possible re-engagement campaigns.
A big disadvantage for those using these SDKs is that they are channel-specific, often displaying numbers that put that channel’s results in a slightly better light. We at Toilet Duck...
Furthermore, you will need to add a new SDK to your app for any new channel you decide to add, which may affect app speed and/or performance.
The ‘Big 5’ of mobile attribution tracking
Do you also want to measure your organic installs and effectivity from mobile display, TV or your own channels? If you do, you can hardly avoid employing the services of a mobile attribution or analytics team.
And the increase in advertising budgets for app marketing has led to a reasonably mature attribution tracking market, too. During this period, five major attribution platforms have taken a large share of the market. All five have been specifically created for app assignment; they are not used to measure other types of marketing.
AppsFlyer claims to be the current market leader, as shown in this graph, followed by the other ‘Big 5’ members:
I have not worked with all five platforms, but as far as I can see they all work in a similar way and chart the same statistics. The advantage of working with one of these groups is that you can measure the effectivity of all your channels with their SDK. They are integrated with the most important (mobile) DSPs, Facebook, Google, Twitter, Snap and so on. Furthermore, they also measure and inventorize results for your direct, organic and app store search traffic.
Data can be approached in a number of ways: by location, by device type, by creative expression and by many other categories. All of the ‘Big 5’ claim to have connected hundreds of millions of mobile devices through one or more apps which implement their particular SDK.
This immense amount of (anonymized) data is used to combat fraud - a huge stain on the reputation of app marketing - as well as for the publishing of benchmarks corresponding to various types of apps.
What’s nice to know is that Kochava recently launched Free App Analytics (FAA), allowing start-up mobile marketers or smaller app publishers to use a free version of the analytics program. This might possibly be a great initial step for measuring app efficiency.
Determining the most relevant KPIs
If you have the right attribution tools for your app marketing efforts and measure effectivity, it is important you know which are the most relevant. In order to know whether your efforts are paying off, you will need to set KPIs and maintain them over a certain period of time. Within the phases of acquisition, engagement and retention, several analytical elements can be tracked and optimized to make your app successful.
- Post-install events
After a user has installed your app, you should be aware of how it is then used. Is your app constantly in use or does it - along with the majority of available apps - get deleted in the first week? Within mobile attribution platforms, you can set up so-called post-install events to trace important steps taken along the route of the customer journey. Consider those registrations, in-app purchases, app updates, shares, or other ‘events’ important to your app's success.
- LTV/ROAS/DAU/WAU and MAUs
In the world of app marketing we love jargon; abbreviations are our buzz words. Here are some important terms which can make your marketing and business model highly scalable.
- LTV (lifetime value): it is useful to chart your users' lifetime value and calculate this for different segments/types of users. Marketing budgets can be tailored to focus on users with the highest LTV.
- ROAS (return on ad spend): unless you only have quantitative volume targets (do these still exist?), ROAS measurements are essential for gaining insight into the efficiency of your advertising costs.
The formula used to calculate ROAS is: ROAS = revenue earned from advertising/advertising expense
If the ROAS is more than 1 euro, it is contributing positively to your profits.
If the ROAS is less than 1 euro, costs are higher than turnover - a loss.
- DAU, WAU, MAU (daily, weekly en monthly active users): in order to measure your app's ‘engagement’, DAU, WAU and MAU are often used: the specific number of users within a certain period of time. Your app's stickiness is usually calculated based on the DAU/MAU ratio. A 50 percent ratio means that the average user has used your app on 15 days within that month.
Finally, you can implement many tools which will chart how your app loses users or carry out bug analyses, so that you can set up a development project for new versions of the app. Often, a new release of your app will also provide better searchability in app stores.
In short, if you want to be super successful and decide to follow an app strategy based upon correct observations and measurements, I think you will definitely need attribution platform data.
I am very curious about your experiences and personal tips concerning this subject, so please share them in the comments section.