In a digital world, every user is connected and the resultant experience determines the value of a service – and affects revenue, costs and reputation. Every customer journey is made up of a complex series of interactions with individuals, technology and automation. Each of these episodes contributes to the overall customer experience and impacts the quality of service delivered by the communications service provider (CSP) and its brand.
To accomplish digital transformation and become truly customer-focused, CSPs need to better understand the customer journey. This requires sophisticated analytics and machine learning to take mountains of structured and unstructured data from multiple sources and use it to understand and support customers. In addition to the ‘past’ data that many operators already collect, they also need to take advantage of ‘fast’ or real-time data.
Defining and delivering digital services is complex, and ensuring that the resultant customer experience is efficient and effective requires careful planning and execution. This report investigates customer journey analysis and the role for analytics. Read it to understand:
- What it means to analyze customer journeys
- Why using advanced analytics and machine learning are important
- How resultant data can improve customer journeys
- How Telefónica is modeling customer journeys
- What to do next