subway under construction
Delivering great customer experiences is harder than it appears. It requires a new approach and a strong data foundation PHOTO: Metropolitan Transportation Authority

Your organization is undoubtedly gathering an unprecedented amount of data about your customers. And if you’re like many, you’re struggling to operationalize that data to positively affect customer experience (CX). 

Customers want and expect personalized experiences. But before you can deliver them, you have to first understand what customers really want from these experiences and then have the data infrastructure in place to provide actionable insights on your customers. 

The former might require a change in mindset and the latter is harder than it sounds.

To deliver the kind of personalization people want, you need to connect with your customers in the moment. This throws up a gnarly problem: without data that is contextualized in the moment, you can’t deliver what your customers expect. How do you solve this problem?

Data Is the Foundation of CX

Every house needs a foundation. And in CX, that foundation is the data layer. Understanding your customers and your interactions with them, and then being able to contextualize data in real time and at scale are what make it possible for you to deliver great experiences.

However, the connection between data and experiences may not work the way you think. Customers are loyal to their experience of a brand. Deliver on the experience and they stay. Fail to deliver or stumble badly, and they leave. According to a Nielsen study, 83 percent of customers said they would stop using a brand after just one bad experience.

Given this, it’s important to realize that the traditional brand definition of customer loyalty is not how customers define it. It makes CX the last frontier for differentiation, and customers are holding brands to it: 67 percent of customers cite a bad experience as the number one reason for churn, according to ThinkJar Research.

Some companies are already able to make their CX work in context and at scale. Companies like Netflix make use of data really well, taken from interactions with millions of customers. Every interaction is unique and personalized to the customer in the moment. Tailored customer experiences that feel “just right” to the customer lead to trust and loyalty.

Why Is This so Hard?

Getting to this can be difficult. On the technology side, legacy data infrastructures can be a big issue. They can keep data in silos, which makes getting a real-time, 360-degree view of your customers impossible. Unless you can get a complete view of your customer, it will be very challenging to put real personalization in place.

For example, much of the data coming into businesses via cloud applications isn’t captured, shared or utilized on the back end for meaningful personalization or CX. For a cloud application to be successful and useful, the data layer has to be contextual, always on, operational in real-time, highly distributed, scalable and often global. Meeting these requirements and delivering exceptional CX will therefore involve looking at your data layer.

However, it’s not just a technology challenge: you have to change how you think about CX as part of a marketing strategy as well. If you think personalization is just about promoting specific products to customers based on their browsing or purchase history, or meeting specific targets on selling those products, you're doing personalization wrong.

Any CX strategy with these goals serves your needs, rather than your customers’ requirements. Rather, personalization is all about valuing the customer as an individual. If you look at product-specific campaigns rather than customer-centric recommendations, then your personalization plans will fail over time.

Take a Closer Look at Your Whole Company Strategy

One of the consequences of a strong CX is it may change your business model over time. For example, companies that rely on monthly payments from customers may choose to add to the service based on data coming through from customer behavior. Looking at interactions can guide future investments or additions.

To continue with our Netflix example, it uses recommendations to support its monthly cost-billing model, not to promote specific products. In essence, Netflix does not care what you are watching, just that you keep on being entertained.

This strategy is not relevant for companies that sell discrete products. The CX strategy has to be different, particularly as these businesses will normally operate over multiple channels. As an example, customers can use mobile apps, internet shopping and in-store locations to research their purchases. Using data from each of these channels in isolation will lead to confusion or recommendations of purchases that have already been made.

Recommendations should take into consideration the channel the customer is using at the time. Being shown products on a screen or in a browser window is very different to a person “knowing” what you might like. Rather than positioning recommendations as based on data, they can be used to augment a ‘personal shopper’ approach, which uses a different set of skills and provides more opportunity to add value to the interaction.

Solving the CX problem is going to require a hard look at your data management. This will include laying a new foundation capable of supporting the requirements of cloud applications and the CX expectations of customers today. But remember: CX is an ongoing journey and not a destination in itself. Like any real relationship, customers will know the difference.