Tackling Customer Attrition with Real-Time Intelligence for Communication Service ProvidersPosted on November 16, 2015 by TheStorageChap in Big Data and Analytics, Use Case
In most regions in Europe, the mobile market is saturated. This means customer wins and losses are harder fought for than ever before, and the growth figures of the golden age of mobile are somewhat diminished.
The challenge of customer loyalty is as important as the contest for winning new customers. It’s not just about price: a war on price is one everyone loses, as customer service deteriorates and service innovation slows as funding gets diverted into sales incentives and discounts. So, what’s the answer? Recent research found that good service makes consumers feel more positive about brands, and 22% would renew or upgrade products even if it wasn’t the cheapest option, to follow a provider that went the extra mile.
Communication Service Providers (CSPs) recognise the need for Real-Time Intelligence (RTI). They are dealing with ever increasing data to manage and analyse, they have constrained infrastructure and a need for real-time analysis. Big data helps them find new opportunities, but fast data allows them to respond to those opportunities before they are gone. Being able to understand and then act upon correlation patterns that span multiple sources of data is critical.
With this in mind, there are some really great ways in which network data can be used to build a better customer experience automatically, in real time.
- Using ‘dropped’ call information to support customers: If an analytics platform notices that specific customers are experiencing consistently poor experience over a period of time; operators can automatically provide a perk, discount or incentive to apologise for and attempt to mitigate the impact of that negative experience.
- Using ‘dead zone’ insight to patch the network: Everyone gets frustrated when they don’t have mobile reception. If a specific geographic region has a particularly high level of drops or packet loss, mobile operators can prioritise investment in the network to improve it. These insights can be tremendously valuable, as they can help keep customers connected, as well as directing network investment to where it is most urgently needed.
- Using network data to assess handset issues: Specific traffic patterns or lag can indicate a suffering handset. Using this information to drive tailored incentives such as discounted upgrades could not only keep the customer happy, but up their usage of data and other services, not to mention provide a touch point to extend their contractual relationship with the provider. This means it’ll also grow the profitability of the network provider, so it’s a win-win all round.
- Strategic network optimisation: Similarly, if a 3G network is being battered in an area because customers haven’t upgraded to LTE handsets and there is too much pressure on the network, it may be cheaper to give or subsidize 4G handsets for customers than it would be to add to the available 3G bandwidth through network upgrades. Doing this will also improve the overall customer experience.
Analytics can evidently help communication service providers improve the customer experience dramatically without incurring high levels of cost. They can prioritise which customers to assist, where, and when, in an extremely fair and reliable way. With real-time analytics, customer problems can be addressed as they emerge. Having this kind of data and intelligence available will enable CSPs to keep their customers, attract new ones and remain competitive.
EMC has developed an open reference architecture for a Real-Time Intelligence platform. RTI is a modular, general-purpose, “fast and big data” solution that consumes data streams and provides real-time analytics capabilities to generate unique insights that affect outcomes in real-time. For Communication Service Providers, RTI can ingest data from access and core networks, provide real-time analytics on subscriber or device-related events and trigger actions based on network behaviour and individual user profiles, thereby affecting outcomes in real-time.
RTI provides a generic real-time analytics platform that can support a large number of specific use cases, such as customer experience management, network optimisation, or contextual services (e.g., location-based advertising).
Of even more interest is the potential to now take the capabilities developed for Communication Service Providers and apply these across multiple verticals.
What are your thoughts on this? What are the other ways data analytics can help CSPs? I’d be keen to hear your thoughts below.