Analytics Driven Cross Sell: How Analytics Boosted Cross Sell Ratios for one of India’s Largest DTH Companies

Abstract

In India, content distribution in television industry is a high volume and low ARPU (Average Revenue Per User) industry. Even though Direct to Home (DTH) service providers enjoy a higher ARPU owing to their higher penetration in the Urban markets, they still report ARPU to be less than 5-6$ per month. With such low revenue per user, profitability is the biggest challenge faced by such service providers. Every DTH provider usually has more than 20 value added offerings including but not limited to interactive channels, movies on demand, mobile applications, HD services etc. India being so diverse in its culture and the television consumption patterns and due to wide variance in the economic strata of the subscribers, it becomes very important to identify the right product for the right customers. We built next product purchase algorithms called Subscriber Preference Modeler (SPM) for one of India’s largest DTH Company. These algorithms aim to cross sell bundles as well as a number of unique services such as gaming applications. We have described how analytics & smart use of Big Data played a leading role in improving cross sell and reducing churn rates to industry best levels. We have articulated the techniques used on imperfect data and how they impacted business. In this paper, we have described how unique attributes of ethnicity and innovative analytics techniques were used to build the SPM engine which has now become the principal cross sell engine for the DTH Company.