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I believe the future will see real time analytics technologies embedded directly in devices

How do you see real time analytics changing the competitive landscape for CSPs, particularly mobile operators?

Charlie: Three ways. It allows for more precise (custom-based on preference, demo and geography) and more timely (proactive) communications and creates new monetization opportunities based on such. It will expand the existing revenue “pie” by enabling exponentially greater value for the same digital media assets. Finally, real time analytics adds a new level of personalized touch, thereby improving the customer experience which increases Customer Lifetime Value while offering new incremental revenue opportunities – such as on-demand video content based on location and preference.

Will the Big Data analytics business change, too, as a result?

Charlie: Absolutely – I see business evolving in three tiers: Big Data analytics, Micro Data analytics and Real time analytics.

Big Data analytics will continue to be used to consolidate and perform some of the basis work, serving as a prime source for the analysis and creation of the heuristic and absolute rules, as well as for measuring and monitoring business success.

Micro Data analytics will be used to identify the longer-term trends in customer behavior upon which so many statistical algorithms are created to optimize the business – retention, cross-sell, up-sell, campaign optimization, ad impression forecasting, and so on.  These elements rely on historical trends to identify pre-indicators of a significant change in customer behavior, but don’t require real time data.  I believe Micro Data will remain a significant source of targeted offers. Many of these apps will be built on top of Big Data Analytics platforms.  They both feed and are fed by the Big Data.

Real time analytics will be vital for the cases that require more time-sensitive information and can be used to override the Micro Data Analytics in certain cases. 

For instance, if a customer has five dropped calls in an hour, Micro Data Analytics typically won’t capture that for a day – or longer in many cases.  But real time analytics will catch this situation at the speed of the data. 

So we’ll see analytics develop into three integrated realms?

Chris: Exactly. There is a very clean and clear intersection of between Big Data, Micro Data and Real time analytics. 

Take this scenario. A customer experiences four dropped calls in an hour. The Big Data analytics platform gathers the streaming information for that customer with dropped calls in real time and triggers the Micro Data Analytics platform. 

The Micro Data analytics platform has assessed the optimal set of campaigns for dropped calls based across a multitude of client profiles, profitability levels, channels and touch frequency.

Real time analytics statistically assesses the impact to the client’s loyalty in the moment, prioritizes the campaigns for the individual client, selects the optimal channel and message, and delivers the information to the execution channel.

Big Data Analytics continues to gather the effects of the Micro Data and Real time analytics treatments through the feedback and self-learning features.

Micro Data and Real Time will then use the feedback and self-learning features to continually improve the treatments and identify new micro- and macro-trends

What does real time analytics hold for the future?

Charlie:  Real time analytics has only just begun to “create what’s next.” I believe the future will see real time analytics technologies embedded directly in devices, just as Google Glass has embedded technologies once spread across dozens of devices into a set of cutting-edge spectacles.

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This article is sponsored by Razorsight. For more information on Razorsight and Real time analytics, go to www.razorsight.com.



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