BoxFresh: The Power of Real-time Contextual Awareness

By: Dr. Andy Tiller

Big Data Analytics is a hot business topic and one that operators are keen to take advantage of. With all-in-one, out-of-the-box systems now available to leverage customer insight, operators can finally start to make real headway.

Operators are constantly being told about the value stored in their customer data; how real time insights can assist in their scramble to increase average revenue per user (ARPU), whilst also offering significant value to partners.

The Big Data proposition is an attractive one: operators monetize customer knowledge to up sell and cross sell to customers more effectively, and generate new revenues by adding value to Over The Top (OTT) partner services.

The arguments for enhanced data analytics make good commercial sense. So, why aren’t we seeing more operators investing in the tools they need to take full advantage of these customer insights?

Perhaps for many, the fear factor comes from the transformation exercise deemed necessary to support real time data analytics. Operators want to fully exploit their data assets, but are yet to be persuaded that this should be at the expense of another big-bang IT project.

Meanwhile, the market for pre-packaged Big Data Analytics (BDA) tools is immature. This is evidenced by a lack of off-the-shelf BDA solutions available, and the fact that many of those on the market come without the components necessary to support real-time contextualized marketing.

The power of customer insight

Operators investigating BDA tools need to be asking vendors:

  • How their solutions create the data sets? For example, can the systems capture dynamic data, such as which customers use which apps, and which categories of website they browse? 
  • What triggers a campaign? How do the systems trigger an appropriate campaign at the right time for each end customer based on their real-time context?  For example, promoting a music offer when the customer starts listening to music on their phone.
  • What data use cases are supported? BDA tools should support real-time capability for in-process transactions, otherwise the operator is relying on historical data, which can only enable the pushing of generic communications to a predetermined group whose contexts have changed by the time they receive the campaign message.

The key to generating contextualized customer insights comes from combining static information, such as a customer’s gender, billing profile and preferences, with dynamic streams – for example, current location, real-time web search, content consumption or app usage. Building and accessing these data sets quickly is especially critical; operators need a system that enables this level of agility in such a fast-moving environment.


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