The Situation 

One of the largest mobile network operators with more than 260 million subscribers, intended to segment their massive customer base for targeted advertising. 

The Problem 

Automating customer segmentation for targeted advertising that involved processing hundreds of gigabytes of data. 

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The Solution 

In this challenging environment of segmenting millions of customers, Data Semantics identified that, the situation needs advanced Analytics solutions to identify the buyer persona of the client for targeted advertising.  

Data Semantics built advanced bots to scan the content consumed by the subscribers to precisely identify the area of interest of each subscriber.  

Built using Hadoop, Spark SQL on SCALA ecosystem, these advanced bots scanned about 100 Gigabytes of consumer data, every week.  

On top of identifying the consumer data, Data Semantics wrote data science algorithms to segment subscribers into buyer personas from, each of the telecom network circles. 

The Outcome 

This activity generated successful traction in terms of generating revenue by acquiring sizable clientele for advertising to their network’s subscribers, in turn, generating ad revenue by an automated process. 

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Team Involved: Data Scientists, Data Engineers, RPA Developers 

Technology Used: Hadoop on Hortonworks, Scala on Spark SQL, Hive, Talend BD. Innovative Data Science algorithms.