The One Thing Missing from Your Data

Website activity can reveal a wealth of information about your consumers, from their buying intent to their personal preferences. This type of data is what advertisers, for example, use to create relevant campaigns, and target/re-target more accurately.

The fact is, however, that this data is largely based on customers’ web browser activity only. Mobile usage patterns, such as in-app activity, are much less visible and accessible. And advertisers, brands and mobile publishers are eager to change this. Here’s why.

The Explosive Growth of Mobile Data

Mobile usage has exploded and is only growing. Consider these statistics.

  • U.S. consumers spent 10 billion hours accessing apps on their mobile devices in December 2015.
  • 86% of mobile users access apps every day.
  • US consumers use on average 10 different unique apps per day on their smartphones.
  • There are 680 apps that have at least 1 million users each.
  • 15% of the U.S. population is now “mobile only.”

If more consumers are going mobile every day, then you’re probably missing vital data that could better inform targeting strategies. This should be your first concern (and it’s one we advise our customers on routinely).

The Next Frontier of Mobile Data: Predicting Who Your Customers Are

Number two, lack of data on mobile usage means you’re missing out on an emerging trend: predictability.

One of our data scientists, Eric Malmi, working at Verto Analytics while getting his Ph.D., recently published an exciting academic paper (“You Are What Apps You Use: Demographic Prediction Based on User’s Apps”) with his colleague, Ingmar Weber, based on a study they conducted regarding predicting customer behavior.

The study and findings are based on data exclusive to Verto Analytics; statistics that reflect the mobile usage patterns of 3,760 users, the list of the apps they had used at least once, and their demographics. Their goal of the study was to address such questions as:

  • Can you predict the gender of your consumer based on how they use their mobile apps?
  • To what extent do our smartphone applications reveal our demographics (for example: gender, age, income, etc.)?
  • Are some demographics easier to predict than others?

What did the results show? As Eric wrote in his blog: “We learned that it’s indeed possible to predict demographic information about users based solely on the kinds of apps they’re using.”

These are exciting implications for advertisers, marketers and sales teams – no wonder the study’s findings were picked up last week by both the Washington Post (Quiz: Can we guess your age and income, based solely on the apps on your phone?) and Big Think (What Your Apps on Your Phone Say about You.)

Here are some of the findings Eric reported in his blog.

  • Gender is the easiest demographic factor to predict, whereas household income is the most challenging.
  • Some demographics (gender, age, race, and marital status, for example) can be predicted with up to an 82% accuracy based on the list of apps you have used, whereas other demographics (number of children and household income) are more difficult to predict.
  • High-income people use LinkedIn, whereas low-income people prefer Job Search.
  • People who use more than 150 apps are harder to predict than people with 50-150 apps.

As we continue to help companies fill the enormous holes related to the mobile habits of their users and customers, contact us if you are interested in looking at the habits of your mobile users.