February 24, 2014 | Written by: IBM Research Editorial Staff
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Editor’s note: This article is by Dr Sambit Sahu, a manager and senior research scientist at the IBM T.J. Watson Research Center. His current research focuses on Cloud and Big Data analytics for Telco and Smarter Cities.
Telecommunication service providers are rich in Big Data, especially those that offer telephony, TV and Internet services – better known as the triple play. Telcos want to monetize that data but it’s extremely challenging to derive meaningful, actionable analytics due to the complexities of correlation, prediction, and the massive volumes of different data sources.
To fill this need I, along with other data scientists at IBM Research, am exploring ways to perform these complex analytics, so that telcos can get new customer insights that they can turn into new business models and services.
And we’re going to demonstrate this analytics tech at Mobile World Congress in Barcelona, Spain starting today.
Telcos’ Big Data
Telcos have a lot of information at their fingertips: the kind of programming customers watch and subscribe to, when they watch, as well as location and movement data that are embedded in transaction data records and signaling information between devices and towers.
But all of this data is noisy. In order to correlate space-and-time data successfully, we’re using sophisticated machine learning and data mining-based spatio-temporal analytics to make sense of different data sources — including an enhanced profile of a customer that could predict what their behavior might be in the future.
Knowing location unlocks the ability to build context about a customer’s current location and also correlate it with information already known about the customer. For example, understanding context can infer intent: will this customer like this brand; make a trip out of town soon; buy tickets to a specific sporting event; take public transport versus a car trip? Add to this, knowledge of a customer’s social media network usage, and you can build a near-360 degree picture of him or her and predict future behaviors.
My team is putting these analytics to work in two use cases.
Mobile World Congress Demo
IBM will demo a use case at Mobile World Congress, showcasing how to create targeted IPTV adver-tisements campaigns based on enriched customer profiles. The solution uses advanced analytics algorithms to correlate & analyze IPTV channel viewing history, location & movement data, and web browsing information to better understand customer’s preferences, lifestyle, predicted locations and in turn match a viewer with the most relevant campaigns.
In the first, the analytics platform is being used to create targeted Internet Protocol Television (IPTV) advertisements based on a customer’s profile. So, instead of every TV watcher seeing the same ad at the same time, during the same program, opt-in participants would see tailored advertisements that best match their profiles. Even individual family members would see different advertising based on knowing who is at home via cell phone location data, in conjunction with what programming they’re watching and their specific profile attributes.
The second use case, seeks to explore hyper-local targeted advertisements that will be delivered to mobile phones. In this use case, targeted advertisements and coupons will be delivered to a customer based on a better understanding of their profile, as well as current and predicted locations.
Imagine a customer who follows a certain celebrity on Facebook who recently launched a new fragrance. And the customer is also determined to be a fashion-forward consumer, based on IPTV viewing. The analytics platform will now predict when this customer is going shopping at a local mall, and offer a promotion on the celebrity’s fragrance sold by a cosmetics store in the mall. More importantly, by predicting the customer’s location, the offer is not sent based on current location – when often times it’s too late to act on an offer.
For Telcos, this analytics platform can form a foundation of meaningful and en
riched profiles about their customers that in turn allows them to offer more personalized programming and services, while also creating new business opportunities and innovative services built around a variety of location-based target campaigns.
Next time you’re watching your favorite sport you might be grateful to see a timely commercial that helps you book a resort for that ski trip you’ve just been researching!