India has around 900 million mobile users which is second largest in the world. An interesting fact about India is while most of the countries have maximum 2-4 telco operators, India has around 12. Also unlike US & UK, the prepaid customers are quite large ( around 90%) of the total customer base.
While the market is huge, with number portability allowed now, Customer churn is a major pain. Customer poaching is on and retention is a big uphill task. Tough competition, depleting customer base and plummeting margins are real challenges for this industry.
CSPs are generating large volumes of data, including call data, network data, location data and customer data. Also no other industry in India has its IT ecosystem as complex as the Telcos. They have scores of OSS and BSS like Network Monitor System, CRM, Billing system etc. The contact centers have their own separate set of software. The social media too has emerged as a big data source.
Analytics could be a real game changer for this industry. Like, Call detail record (CDR) could give important information about customers “usage patterns”. ‘Who’s calling whom’ etc. could help in better customer centricity. Analytics could also help in monitoring the call drop rates on the network for better maintaining the networks and reduce customer churn.
Analytics on this avalanche of data could help a lot in offering ‘right’ packages to the customers. The prepaid customers usually recharge for as low as Rs. 10 ( 1/6 of a USD), they change the CSP quite often based on offers they get. This customer base though being huge, is quite volatile. If a prepaid customer is ‘burning’ his minutes fast its likely he is about to move to other CSP .Big Data analytics could help in offering better deals and retain such customers.
Value Added Services (VAS) could bring greater revenues if analytics is used. All CSPs have offers like ‘discount vouchers ( at eateries, travel, gym-spa etc) but are these offers based on customers data like his location, interactions with contact center, likes & comments on social media etc. News/ consultancy/ contents like devotional, sports, entertainment etc too could be curated, customized based on personal interests. Presently all are ‘ spray and pray’ offers. The approach of CSPs is to offer them to all subscribers…may be some like it.
CSP are facing pressure to reduce costs and maximize average revenue per user (ARPU), Fact of the matter is, the idea of ARPU has lost its sheen across the globe today. It makes more sense to use ARPA (Average Revenue per Account) in today’s context. Deals for the company, Family, Community etc makes much more sense. Big Data Analytics could help in offering ‘smart’ group packages.
Contact Centers are the fulcrum of customer service in Telcos. I have done ‘Agent Shadowing’ in number of call centers to identify the impeding factors in the agents works & processes. One of the pain point is that they have to toggle through multiple screens while they handle calls. Big Data analytics could directly improve call center metrics like AHT (Average Call Handle Time), ACW (After Call Work) etc by presenting consolidated ( single screen) view of information to the agents which is spread across multiple applications in the organization. All contacts these days have ‘call and data loggers’ which record data & voice. Analytics on these data could help in assessing agent performance and provide better agents training & improved customer services too.
Analytics could add lot of value to this industry.