As a product or marketing owner responsible for web or mobile applications, you’re monitoring metrics like Daily Active Users, Average Revenue per Daily Active User and Customer Lifetime Value on an ongoing basis, to determine the best ways to engage and monetize your customers.  You may even monitor these metrics by location, by device or by custom segments and funnels that you’ve defined across multiple reports. If you’re doing this regularly, then you know how time consuming and difficult it is to go beyond the high level aggregate counts and determine the most relevant insights that you can use to guide business decisions.

The Clustomers feature launched today as part of the Medio inGenius™ suite addresses this challenge: simplifying and reducing time to insight. Many companies lack the time or analytics expertise to effectively interpret their customer data.  For example, beyond simple usage counts, data can also be viewed by geography, by device, by the amount of money spent by users or by specific actions performed within an application.  Without any clear way to know what’s important, analysts and application developers have to rely on intuition to decide which of these factors are relevant to their application’s success –but unfortunately, guessing can often miss the truly insightful takeaways.

Clustomers, Medio’s unique method of dynamically clustering customers, addresses this by automatically surfacing the user “attributes” or “features” that have the strongest correlation with segments reflecting user engagement, retention and monetization. Instead of mining through dozens of reports looking for takeaways, Medio’s Clustomers module will automatically identify relationships and patterns in the data that can be applied to improve user experience, target advertising and identify areas for further investment. For example, using Clustomers, companies can quickly determine factors like:

  • The top three attributes common among users who are more likely to stop using an application
  • The most loyal users and the characteristics they tend to have in common
  • The characteristics that are indicative of the types of users who will use an application only once
  • The unique, distinguishing characteristics of high lifetime value users

So, a simple example, if iPad users are consistently more likely to churn out from a particular application whereas iPhone users tend to use it longer and more frequently, the publisher of that application may want to focus user acquisition efforts to try and get more iPhone users (and potentially also spend time investigating why the application isn’t effective in retaining iPad users). Or if Scandinavian countries represent a significantly higher proportion of loyal users, then the publisher may decide to invest in better localized content and targeted advertising for users in that particular region. By providing answers and insights instead of just count and metrics, Clustomers will reduce the time it takes to get real value out of your data and more effectively transform it into action.

This is just the first application of Clustomers in Medio inGenius.  We’re excited about leveraging this technology to help with other challenging problems: like predicting customer lifetime value, analyzing propensity to churn and determining the best ways to re-engage users.  Stay tuned for more updates soon.