This is the most worrying part of TM Forum’s recent survey of 100 customer experience pros from within CSPs – most respondents said they their companies had completed their analysis and mapping of customer journeys. Thing is, it’s never over.
A customer disconnect
For the past 100 years or so it has been the mission of communication service providers (CSPs) to teach us how to use their technology. Every action was driven by the network. Customers were area codes and exchanges or homes passed – not individuals.
Even as network and service technology has advanced, they haven’t learned much about us as customers. Customer data continues to be inconsistently maintained by numerous systems while only a small portion of network data is ever correlated with an individual customer or made available to any system other than billing.
Technology is no longer mysterious, connectivity is everywhere and we want to use it on our terms, our way, whenever we feel like it. We don’t wait for a dial tone anymore, and we don’t dial 1 for long distance in the US, so we shouldn’t have to follow complex instructions or start over when we move to a different channel. But CSPs are having a hard time making all this happen.
We’re building massive data lakes that take in every bit of everything that the infrastructure and OSS/BSS can spit out. We’re implementing enterprise catalogs that support multiple channels using a single source of customer, service and network data. But we still haven’t learned much about the customer.
We’re not done, we’re just getting started
Mapping the customer journey requires an ongoing effort of data capture, analysis and learning that is refined by the latest real-time data about each customer and continuously shaded by network and service events. It isn’t finished when the flow chart is done – that’s only the beginning. Capturing and analyzing data at each point in the retail or support experiences, then applying that learning to the broader journey takes a lot of intelligence. To think outside the conference room requires capable and configurable analytics, and machine learning solutions.
Fast analytics that can analyze customer behavior in real-time and machine learning that can direct systems to act on it based on knowledge of the network and services is the product of learning about a customer. Before that can happen, data has to be captured from every episode relevant to that customer. This means structured data captured from the network, services, devices and applications; as well as unstructured data captured from external sources like social networks, retailers and partners.
The data is there, but only the intelligent application of a solid analytics solution can make it useful. Deriving value from the tremendous volume of data available to service providers requires rapid, smart analysis and intelligent distribution to critical business and operations processes and systems. We have what we need to learn about our customers – now we need to listen, then act.
To learn more about customer journey analysis and the role for analytics, see our new Quick Insights report, Journey to the core of customer centricity.