There are many problems that face telecoms operators today – network congestion, investment challenges, dissatisfied customers. But probably the one that keeps CEOs awake at night is churn.
Churn is proof positive that if customers think that the service they receive is bad enough, or they can get a “better” deal elsewhere, they are willing to jump ship. The churn rate in the US telecom industry was 1.28% to 2.19% in the third quarter 2014, according to Statista. That may not sound like a problem but take a carrier with 40 million customers and – well, you get the point.
To counter this challenge, operators have tried many approaches over the years. Bundling products and services certainly helps; solving customer queries and complaints right the first time works; even screwing up, solving the problem, apologizing and being human works better than it should. Having a network that does what the operator says it can do should be a given. But putting pushy salesmen into customer service “save teams” and trying to sell deserting customers back into your world is probably the most offensive and least effective way of operating.
Now, though, after many, many presentations, conferences, papers, articles and discussions, it seems that analytics also works – in the real world. Vodafone, the giant that posted revenues of around £40 billion ($63.2 billion) last year, claims it boosted its revenues by between 1-2%, “thanks to real-time anticipatory selling propelled by big data analytics.”
Although it is not clear just how much of their customer base they are addressing with analytics, it seems they are definitely using the technique to offer prepaid customers conducive deals when their balance drops below a certain point.
This ties in with a survey conducted by the TM Forum last year that showed that the emphasis for real time functionality today is to help customers avoid bill shock, through balance management services. The survey also showed that in two years’ time the emphasis will shift to supporting OTT collaboration, dynamic pricing and innovations in areas such as zero rating certain apps.
That analytics is clearly still in its infancy is not in dispute. What is encouraging is that a telecoms giant has put its money where its mouth is and is beginning to replace lost revenue by offering customers what they want, presumably when they want it.
It must be noted that we are still in the early days of using data analytics to the fullest. The old rules about what telcos think customers want and what they really want is changing rapidly, almost as quickly as their loyalty if they fell they aren’t being treated the right way.
Today’s data scientists are actually learning from experience. It would be foolhardy to think that they will get it right first time, and there is a distinct risk that customers will be lost. It is inevitable. Determining who is about to churn is one thing – knowing what to offer or do to keep them quite another. Then there’s the option of dumping customers that are simply not profitable, actually costing you money or simply not worth the trouble.
This is a brave new world we are entering. The ability to combine real-time big data analytics with data originating from more static databases within the enterprise is still a work in progress for many companies. The move to real-time transaction processing and real-time data collection will certainly help the business optimize efforts like anticipating and encouraging positive actions like customer buys – but it could quite easily have an adverse effect if left purely in the hands of the scientists and analysts.