How to measure incrementality in the App install campaign

Let us understand first why App install campaigns are hard to start. 

• First, you will have to set up conversion events which, in most cases, need an app release.

• Then, you need to understand attribution. It is not as straightforward as web attribution.

• Lastly, you have come to terms with different numbers in the various app dashboards like Playstore/Appstore, Firebase, MMP, etc.

But the most important issue you will face as the marketers understand the overall lift in the installs and purchases as the scale-up of the app install campaign.

If you were to run the app install campaign through affiliate and ad networks, the thought of whether these campaigns bring in new users to the platform comes to our mind quite often.

In this scenario, it is very important to measure the incrementality of the campaigns.

Incrementality measurements

To measure the incrementality of any campaign, we should have a control metric first. It is also called an anchor metric.

The control metric or Control group is something that doesn't get influenced by the campaign but gets exposed to all the events that influence the test group.

For the app acquisition campaigns, the most effective anchor metric is using top-of-the-funnel data from other platforms that get similar brand and marketing exposures.

Let's say we are planning to run an install campaign for the Android App.

Using iOS installs-which generally contributes ~10% of overall installation in a country like India- will be a good anchor metric. If we have a web platform, using a desktop or mobile web's daily users as the anchor metrics would also be effective.

We just make sure that the app campaign scale is at least 10% of the base number -the average daily install volume- to get a clear conclusion.

How long should we check this?

We should at least run the campaign for at least 7- 10 days to negate the 'day of the week' variation which most categories of apps have.

Generally, we don't get a clear single number when measuring incrementally; however, we can get a fairly accurate deviation with a two-week campaign.

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