Authored by Duncan Shaw, Lecturer in Information Systems at Nottingham University Business School and member of Corndel’s Data Board.
This is where many organisations falter. They understand what happened to a customer in a single moment - a ‘touch point’ - but moving beyond that to see and understand the whole journey is more difficult. To achieve this ‘whole journey’ view - for each and every customer - takes more than data. It means being data-driven.
But once you become data-driven? It’s possible to understand the customer journey - at scale, consistently, and automatically - for all your customers. Customer journeys are videos, not snap shots. Being on a journey means your customers have backstories and destinations. Customer journeys have episodes and story arcs, main stages and sub-stages. And they have a cast of thousands - which includes your staff and your partner organisations.
Thinking about customers in terms of the journey they are on improves customer service in several ways.
Firstly, customer service is not just about discrete snapshots taken from customer touch points - customers still exist between touch points. They still have problems; they still need help. You can use data to find the most pressing customer problem; then the next; then the next; and so on. If a problem is occurring in between touch points, then you create another touch point.
You can ask customers (or even other people who help you) to play detective. Use information from them to figure out the pattern of what’s causing problems - or at least where they happen - and then you redesign the journey. You can also use this pattern to watch over future customers and intervene with advice if they fit the same problem pattern.
The recorded history of each customer is part of a pattern for recognising potential customer problems, spotting ways to help them and developing new services that they need. This understanding may come from behaviour data, like customers’ buying history, website clicks and/or profile information - it provides context for helping customers make decisions that get them to their desired destination. When you record, guide and facilitate customer journeys, you can learn data patterns from past customer journeys - and this enables you to predict how to help future customers.
Every customer is a segment of one. But small things that happen are often repeated, for similar people in similar situations. With the right data and the right analysis, you can spot when one event usually follows another. Alternatively, you can find the pattern to show which groups of customers routinely cause chaos, or which have a great, friction-free service and love you forever.
Journey-based thinking helps you understand how to strategically use data - this includes how to orchestrate work journeys for your staff and partner organisations. The lessons from data-driven customer service can be applied to staff recruitment, development, retention, and any other business process.
It’s a systematic smoothing out of the bumps - but it’s also about using data to quickly and cheaply test your ideas and innovate more quickly. Data, business experience and creativity go hand in hand.
Non-technical managers with huge experience have as much to offer as the most recently trained data analysts. Business transformation is a team sport.
Ultimately, customer ‘loyalty’ doesn’t exist. Retention is about each customer’s experience, how useful the service is to them, and how easy the whole thing is. Loyalty is fleeting; but being indispensable? That gets them every time, and they tell their friends. Being data-driven is the way to do all this at scale.
This article is brought you by the Corndel/University of Nottingham partnership.
Corndel and University of Nottingham offer a streamlined suite of professional development opportunities for employees with different needs of data. The partnership brings together Corndel’s expertise in high quality professional training and the University of Nottingham’s educational excellence.
Dr Duncan Shaw is a Lecturer in Information Systems at Nottingham University Business School and is a member of Corndel’s Data Board. His research and consultancy interests include AI and Big Data strategy, Digital Services and Business Ecosystems. He has more than 25 years’ experience of service innovation and business transformation projects for clients including Xerox, Coca-Cola, Danone and Shell.
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