How Big Data platforms can benefit loyalty programs

Improving customer loyalty, attracting new customers and increasing ARPU are key goals that all telecom service providers strive for. Promotional campaigns are widely used by operators to achieve these goals.  A typical form in which a loyalty program is run is by providing bundle plans, whereby subscribers are given call time or data in bulk at a fixed monthly rate, for instance, a $30/month plan that includes 500 MB Data, 500 min of voice calls and unlimited SMS and so on.

In a more competitive marketplace, particularly prepaid markets, online rating and charging systems are used to provide real-time promotional platforms. These systems seek to engage customers through offers that are created on as-needed basis. These promotions could be as simple as giving a free call to more complicated inter-services incentives – in fact, flexibility of available capabilities at times allows marketing to be hyper creative in trying to woo customers. But one thing still remains, and that is the effectiveness of promotional campaigns is hard to accurately measure, thus the value of running marketing campaigns remains debatable.

With the advent of Big Data platforms, the promotional campaigns can be measured for their effectiveness much more efficiently. The assortment of tools and algorithms available to analyze large data sets can now be employed to fine tune marketing campaigns.

Let’s take a quick example – marketing wishes to upsell a service package for home automation by offering a signup bonus of free 5GB Data or other rewards. The incentive is rolled out and marketing would like to know the effectiveness of the campaign as the campaign proceeds. In a traditional system, capturing, populating, correlating, analyzing and reporting data from various sources is a resource and time consuming task. Big Data platforms are designed to crunch through large volume of data, and data analysis can be done easily with minimal effort and marketing gets to understand the effectiveness and fine-tune the campaign as required.

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