Transform the customer experience you offer with data analytics

Breakthroughs in data analytics mean that firms are starting to see what their customers really think of them. B2C companies are leading the way, but understanding the customer experience is arguably even more important and more challenging in the B2B world.

Dr Mohamed Zaki and Dr Benjamin Lucas from the Cambridge Service Alliance describe new approaches to data analytics and how they can help manufacturers shake up their customer experience and achieve competitive advantage.

Customer Experience Customer Relationships Supply Chain Digital - image courtesy of Depositphotos.
Access to unprecedented amounts of customer data combined with advances in machine learning means tools that really delve into the customer experience can be developed – image courtesy of Depositphotos.

Customer experience (CX) is a rapidly growing field of research, and a new industry of CX agencies is already springing up around us.

Why all the buzz? Well, it is only now, with access to unprecedented amounts of customer data combined with advances in machine learning, that we are able to develop the tools that really allow us to delve into the customer experience.

Until now, companies have tended to rely on simplified ways of measuring customer satisfaction using techniques such as net promoter scores (NPS) and customer satisfaction surveys – traditional management methods used to quantify the loyalty of a firm’s customer relationships.

Not only do these techniques fail to provide a true insight into the customer experience, but they are often actively misleading, lulling firms into a false sense of security until they notice – too late – that they have haemorrhaged customers.

CX analytics, by contrast, allow managers to develop a much richer view of a customer and their interactions with a firm throughout the ‘customer journey’. It is this understanding that will allow firms to stand out from the crowd.

This article first appeared in the March issue of The Manufacturer magazine. To subscribe, please click here.

The jump to B2B

We are already seeing many examples of firms competing on customer experience, whether it’s Lenovo’s quick response time policy, or Disney personalising its customer interactions or omnichannel retail.

But is this something that concerns B2B companies? The answer – emphatically – is ‘yes’. A McKinsey report in March 2016 pointed out that B2B customer-experience index ratings significantly lag behind those of retail customers. Yet, B2B customer expectations are rising fast.

As we all experience what can be achieved in areas such as retail and banking with smart, real-time services and customer-friendly apps, we will become increasingly unimpressed by a lack of service innovation in the workplace.

And for B2B, where the value of each customer tends to be high, customer loyalty is paramount.

At the same time, however, the notion of a B2B customer is complicated. Whereas in B2C scenarios a customer is usually one person, in B2B, purchasing decisions are usually made by multiple stakeholders.

In this scenario, understanding the customer experience needs sophisticated analytical tools.

Big data

Another common misapprehension about customer analytics is that big data is the answer.

Thanks to an increasingly digitalised value chain, firms may have huge volumes of data at their disposal. But sheer volume does not – in and of itself – deliver new insights into customer behaviour. We need to know what questions to ask and how to ask them.

Graph visualisation showing a sample of customer feedback, with individual responses coloured by net promoter score (green = promoter, yellow = passive, red = detractor).

A research project we are working on at the moment demonstrates some of the problems with current data analysis techniques. We have taken the data from a client survey carried out by a UK-based manufacturing firm.

It contained around 3,000 responses to questions about how well it maintained the physical assets it supplied and how effectively it delivered its wider support services.

The survey used scale questions to create metrics such as NPS, as well as open text fields to allow respondents to comment in their own words. We first narrowed our focus to analyse only the textual responses relating to the physical assets, looking for similarities (and dissimilarities) between customers’ vocabulary.

In the graph above, similarities between customer responses are shown by the larger circles, while smaller circles show less connected customer responses, denoting less similar responses. These have been overlaid with the NPS categories: promoter (green), passive (yellow), detractor (red).

The important message from this diagram is that not only is there not much similarity in customer experience (evidenced by the vocabulary used), there are also no clear clusters around the NPS results.

This tells us that metrics based on self-report surveys are not giving us an accurate picture of customer experience, whereas the words customers use to describe their experiences are a much better starting point.

Focus on CX

This is where CX comes in. CX is able to develop a much deeper understanding of customer decisions along the whole customer journey, not just at the point of transaction.

It does this by creating a framework for interrogating the data based on a deep understanding of, for example, the cognitive, emotional, behavioural and social dimensions of customer behaviour, alongside the more functional measures of how well a particular product or service performs.

Once these dimensions have been defined, they can then be used to interrogate the data using machine learning to score customers on only those aspects of the transaction that matter to them.

This enables firms to properly identify critical pain points, unmask underlying sources of friction at the touchpoints along the customer journey and provide insights into how and where firms need to implement change to improve their responsiveness.

Understanding, managing and measuring customer experience will become more and more important for manufacturers. But with greater connectivity comes greater expectations.

As manufacturers, these new analytical approaches give you the opportunity to develop more accessible, more bespoke, more responsive services and, by doing so, ‘lock in’ your loyal customers.

The challenge is that if you do not start to provide that level of service, your customers may look for it elsewhere.


Dr Mohamed Zaki is Deputy Director of the Cambridge Service Alliance, University of Cambridge’s Institute for Manufacturing.

Dr Benjamin Lucas is Assistant Professor at Nottingham University Business School, University of Nottingham and a Visiting Researcher at the Cambridge Service Alliance.