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Leverage Big Data Better with Automatic Segmentation

Posted on 9.19.2012

We all know that it’s difficult to manage big data, which is, by its very nature, huge and disorganized. But, as those companies that have found a way to make use of it can attest to, big data can also offer some incredibly valuable insights about your customers that can greatly benefit your Web business, if they’re leveraged correctly.

One of the simplest methods that many have found for making sense of big data is to segment it into different groups to make it easier to decipher, understand and use. This is likely why big data analytics provider Medio Systems just announced a new module for its inGenius Suite called Clustomers that provides automated audience segmentation to help increase customer engagement and monetization capabilities.

The inGenius Suite of predictive analytics solutions was built to help Medio customers gather insights about their data, and then use that information to deliver relevant and actionable content or services to their own customers. With Clustomers, organizations will be able to automatically surface important results quickly and easily, and use that information to identify the most significant factors on their sites that provoke user retention and engagement in Web or mobile applications.

Clustomers uses activity and user data that has been acquired through either Medio’s software development kits or its Data Collection Service. The module takes the information and then analyzes attributes or features that are associated with key user segments; after that, it summarizes the correlations that can provide the most value to the customer’s business. This allows users to quickly pull out actionable (and meaningful) connections about their customers without laboring through a bunch of reports.

What really makes Clustomers a useful module is that it takes data that is more difficult to obtain, such as inter-session frequency, average session length or mid-application abandonment, and analytically determines which features are the most statistically significant, thus, eliminating the reliance and cost of data analysts required to filter out findings that appear related simply by chance. This allows Medio customers to turn data into action with haste.

According to CEO Rob Lilleness, “These deep insights give our customers the ability to quickly make changes to their customer experience and acquisition efforts that will drive more effective monetization.”

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