Most brand marketers today still believe that click-through rates (CTRs) are the best indication of user engagement and media quality measurement in mobile advertising, not realizing that detailed user profiles coupled with today?s programmatic technology can provide much more in-depth and actionable data.

To fully understand how you can better measure the quality of your mobile campaign and the users it generates, let us begin a journey that will include three stops. 

Now it is important that we visit them all without skipping through anything because each stop tells an important part of the story and together they give us the most accurate picture of the user.

 

This stop is where we pull data from the first impression to the last click, also commonly known as CTR. 

CTR indicates the quality of the creative as a standalone message in relation to the media in which it is displayed. 

For native or full-screen ads, we can expect a CTR of 5-8 percent. For banner ads, a CTR of 1-2 percent will make sense. 

Following up on CTR is an important step because when there is no click, there is no install ? meaning no usage ? and we want as many users as possible to click on the ad giving us a better chance to drive them down the funnel towards using the designated service or application. 

 

Data pulled from the first user?s click to installation of an app or service is where we will be making our second stop on this journey. 

If there is a sizable gap between click and install, this likely means that there is an inconsistency between the promises of the ad and the app store or the service page. 

Bottom line, you are not providing what the user expected when he or she clicked the ad.

 

If we did hit the CTR numbers mentioned in our first stop, but the CR is lower than 1.5 percent, it could ultimately mean that we need to work either on the creative or on the app store page ? most likely both ? to find a better way to meet the user?s expectations and deliver what you are promising.

 

The third stop is where we pull data that comes after the installation of an app or service based on post install events. 

Here is where we can really see where true target audience lies based on their actual usage. 

When the data from this final stop of the journey is combined with the information we gathered on the previous two stops, we can get a clear indication of: 

? The profile of the user who is actually using the app

? Which creative generates more engaged users

? Which media source generates more users likely to be more engaged

? The quality of our app store page

? The quality of the engagement loop in the app flow

When looking at the numbers here, you will notice they vary since every app or service has a different engagement goal.  

Two examples of a good conversion-to-usage rate could be:

? 15 percent of funnel completion (registering or subscribing to a service)

? 4-6 percent conversion to paying users in the first week

Now we have a 360-degree view of how a campaign is performing and how it is engaging users or not. 

Programmatic-based technology is a game changer in mobile advertising. 

In just 10 milliseconds, programmatic machine learning can assess all available user profiles to match an ad to the most relevant ? and most profitable ? mobile user possible.  

Also, such learning can also deliver all the data layers above in an easily accessible away to allow companies to enhance their campaigns and be assured of ROI when purchasing mobile advertising.  

THERE ARE LITERALLY hundreds of available case studies of apps and mobile services already using the three quality indication measurements outlined above.  

Brands and agencies should seek these out to educate themselves and learn how to spend their money much more efficiently and effectively.