Know Your Users: What is the Difference Between Profile Data and Behavioral Data?

trianglesAs app marketers, we spend so much time slicing and dicing analytics data, becoming so immersed in it, that it’s easy to lose touch with the fact that these are actual people interacting with your app (and not just numbers). But app users have feelings too! They have hometowns, favorite bands, teams, shoes and styles of music. Often, these user characteristics are the driving force behind all of this behavioral data. Through analytics, we can speculate on a lot of these user attributes. But wouldn’t it be nice to just know for sure? Well now you can with profile data!

Over the past few months, we’ve published some pretty in-depth content around analyzing behavioral data. And although behavioral and profile data may seem similar, they have some distinct differences. We’ll highlight these differences and how they can work together to strengthen your app marketing campaigns.

 

Behavioral Data: What Are Your Users Doing?

austin-powers-behave.jpg

You guessed it, behavioral data is all about how the user behaves in your app (not that kind of behave, Austin!). It’s the nitty gritty details about how users interact and engage with your app. How long are users staying inside your app? When do people come back after their first visit? How many people abandoned the checkout process? These types of questions can all be answered with insights from behavioral data.

It’s especially useful to marketers because we can target our users based on this information. Rather than sending blanket push or in-app messages to every user, we can target specific user segments with more personalized language and calls-to-action. When the marketing results come in, you can optimize and repeat with more defined user segments.

localytics-engagement.png

 

Profile Data: Not What You Do, But Who You Are

Profile information is not about how the user behaves - it’s actual characteristics about the user. This can be as simple as favorite sports teams or bands, or as robust as whether or not they use an in-store loyalty card. All of this information can be collected in real-time through the app, or outside the app and imported to your analytics platform.

localytics-user-profiles

 

Examples of Profile Data:

Interest Categories:

  • Sports Teams = Boston Red Sox, Liverpool FC
  • Music Artists = Paul Simon, Dr. John
  • Hobbies = Guitar, Marketing, Traveling
  • News = World, Technology, Finance

Static Data:

  • Birthday = 1982-03-10
  • Gender = Female
  • Hometown = Checotah, OK
  • Annual Income = $200,000

In-App Info:

  • Subscriber Type = Trial
  • Linked Twitter Account = True
  • Registered User = False

Outside Channel Attributes:

  • In-Store Purchaser = True
  • Frequent Buyer Member = False
  • Rewards Status = Non-member

One of the best features of user profiles is that it doesn’t require the user to sign up or sign in. You can still collect a lot of this information anonymously. This is how an app like Yahoo Weather! can remember my home location, as well as my other favorite locations without ever registering or signing in.

yahoo-weather-screenshot.png

 

The Perfect Marriage: Behavioral + Profile Data

There was a time when behavioral and profile data existed as separate entities. They knew of each other’s existence, but had never met. One glorious day they were introduced by a mutual app analytics platform, and they never looked back. Although this may sound a little silly, behavioral and profile data do have a truly interdependent relationship with each other. Here are a few examples to illustrate:

#1. The Retail Clothing App

  • Offer: 25% discount coupon via push notification
  • Behavioral User Segment: Users who have made an in-app purchase within the past 30 days

The Game Changer: Profile Data

While visitors are in your store, offer them an exclusive 25% in-app shopping discount in exchange for making an in-store purchase using their loyalty card.

Why It Works: Not only does this incentivize your shoppers to buy using their loyalty card, it also encourages them to open, engage and shop using your app.

#2. The Daily Newspaper App

  • Offer: Free 30-Day Premium Trial
  • Profile User Segment: Registered App Users

The Game Changer: Behavioral Data

There is a large segment of users who viewed the “Premium Subscription” page within an app, but never converted. Rather than send one free trial push notification to all registered users, send it only to those who have viewed this “Premium Subscription” section. It’s like remarketing to your own users!

Why It Works: You really don’t have a good idea of whether or not the average registered user is interested in subscribing. It’s best to ease them in with more lightweight conversions like social sharing or clicking on suggested articles. By leaving the free trial to users who are farther down the subscription funnel, you’re spending your marketing dollars (and their screen space) more wisely on user segments who are more likely to respond.

 

How Smart Is Your App Marketing?

brainSmart app marketing is about communicating important offers to your users using push and in-app messaging. Smarter app marketing is about knowing the difference between your users, and how to effectively target them with unique and relevant offers. But the smartest app marketing transcends the app. The fusion of behavioral and profile data allows you to share web, offline and in-store behavior with your in-app marketing efforts (and vice versa). It provides you with a holistic, cross-platform view of your users resulting in higher levels of engagement and a stronger loyalty to your brand.

Download the Beginner's Guide to App Marketing by Localytics

X