Using IPTV Customer Usage Analytics, Accenture generated viewer segments based on usage data for a US communications operator. Segments were differentiated based on characteristics such as total viewing hours, premier movie viewership, regional and international viewership, channel loyalty, and time and day patterns. What resulted was a highly tailored channel-bundle recommendation for segments such as Premium Movie Watchers.
Identifying leaders, followers, and managing the reaction: The unprecedented adoption of social networking is spawning a breed of super-influencers who can make or break a product, service or brand in record time. More than two-thirds of consumers search and read about brands on social-media sites, according to Accenture’s 2011 global consumer survey.
Social network analytics help to identify customers’ social communities, such as family and friends. The Leadership Index helps identify leaders and followers. The actions of social influencers are obviously important to follow. For example, if a leader churns, followers are much more likely to take similar actions (contagious churn). The same phenomena can be observed in new product adoption and service take-up.
By adding social variables to a traditional model, mobile operators are able to predict churn earlier and more accurately. For example, Accenture found that a predictive churn model built for a North American wireless operator with input from social variables achieved 42 percent uplift over the traditional model.
Social network analytics also can be used to engage influencers with customized pricing, and to manage word-of-mouth, whether negative or positive.
Using location analytics to make smarter business decisions: Enhanced call detail records with location data are combined with usage patterns to separate travel and stationary patterns, and to identify network load and bottlenecks. Location analytics enable operators to manage the network and user experience, identify customers at relevant locations and drive location-based marketing in real time.
Tailoring recommendations in the moment: Accenture’s real-time decision analytics combine real-time contextual information, gathered while interacting with a customer, with pre-defined customer engagement rules and predictive models. This tool provides a powerful capability to maximize the impact of each opportunity in every customer interaction. Inputs include customer segmentation, predictive scores such as churn and propensity, marketing offers designed for the customer, previous contact history, campaign history and response. Real-time inputs include information such as reason for the interaction, current event and request.
For a UK telecoms operator, Accenture developed a Recommendation Advisor engine powered by real-time decisioning. The following scenario explains the process. The engine suggested a list of customers likely to buy a specific broadband package. A sales agent called one of the customers with the intention to cross-sell. However, the customer complained of recent poor service and also asked about his contract renewal date. The sales agent entered the complaint and query to the engine. The Recommendation Advisor identified high churn risk and recommended a retention offer instead of the cross-sell. The customer was pleased the agent had listened and decided to renew the contract. For this company, Recommendation Advisor has improved campaign effectiveness by 30 percent.
Building next generation customer profiles: To benefit from next-generation analytics, operators will need to expand their customer data models. Accenture has a patent-pending Customer Analytic Record (CAR 2.0) that helps to produce next-generation customer profiles. CAR 2.0 promotes a 360-degree view of customers by linking social identity to internal customer databases. The extended view encompasses unified service, behavior and usage data, and social analytics, along with analytics for TV, mobile and network usage.
Technology is only part of the solution
Analytics is likely to become a differentiator, and eventually a core capability, for telecommunications companies to achieve high performance. It will move away from siloed capabilities in engineering, customer service and IT to become an integrated and holistic capability.
Making this shift will require changes to organization design, and changes in roles and responsibilities, to nurture an analytics culture. To achieve next-generation results, companies will require an agile operating model, along with technology building blocks such as data management, data mining and real-time decision solutions.
Depending on internal capabilities, business leaders will make decisions on whether to develop next-generation capabilities in-house, whether to partner with other organizations, or whether to outsource the function for greater speed and results.
From strategy to execution, Accenture works with companies to develop analytics capabilities to outperform competitors. The Accenture global network of professionals has experience in the telecommunications industry, and knowledge of business strategy and advanced tools that can provide a competitive edge for mobile network operators.