Every action and transaction during each episode of a customer journey determines whether they will subscribe and stay, or churn. Operators cite customer experience as a key driver of digital transformation, but many customers find it difficult to do business with them via any channel, anywhere, at any time.
Ensuring a positive customer experience entails more than collecting metrics; it is about the entire experience.
Starting with the upfront buying process, operators must turn their full ecosystem of organic and third-party
capabilities into compelling offerings that customers can buy through any channel – for the same price and T&Cs. Once delivered, they must fully support them consistently via those same channels. Doing this requires analytics, machine learning and automation that are customer-focused and service-aware.
Before and after
While every customer goes on multiple digital journeys every day, there are two distinct customer journeys
operators should consider: the one to becoming a customer and the journey as a customer. The journey to becoming a customer is a typical retail journey. At the highest level, it starts with a search for a product or service, during which time the operator has multiple opportunities to engage across a variety of channels.
Second is the journey as a customer. As customers use each service, feature, function and device, it is up to the
provider to: ensure quality and performance; answer questions about options and billing; and identify the right opportunities to market additional services.
This customer journey is ongoing and enables operators to build a more accurate and detailed picture of each customer, their intent, preferences and behaviors. The graphic below illustrates both types of journeys.
Putting real-time data to use
Each episode along any customer journey can involve multiple touchpoints and engage a variety of processes
and systems. However, a challenge for CSPs is that most customer experience metrics are calculated after-the fact. The real-time data that is generated as each episode unfolds isn’t used to support a customer or potential customer while they are on the journey. At best, the data is correlated and analyzed to improve the next journey. But for many customers and prospects, there may be no next journey – at least not with that CSP.
While the two customer journeys are unique, they are ideally executed using the same channels and systems. For example, when the support journey identifies an opportunity to offer existing customers new retail services, those offerings should be available via any channel. When the retail journey is enriched with experience data and analysis from the support journey, both benefit, and the overall customer experience is greatly improved.
CSPs have always been obsessed with network performance and quality, and while that is as important now as it ever was, the quality and performance of the network is no longer entirely indicative of the customer experience. But, given that the journey can take the customer anywhere and the service provider will be blamed for any difficulties that arise, it becomes incumbent on the operator to capture, analyze and use any and all data associated with every step along the way.
Proof of concept
A recent TM Forum Catalyst proof-of-concept project called Experience journey shaping with analytics looked at how CSPs can use the Forum’s Customer Experience Management Lifecycle Model to capture users’ experiences on their journeys and then develop a decision-taking process to determine the next best action for each customer, and how and where to take it. Watch the video to find out more.