Sometimes customer experience leaders make things more complicated than they need to be.
If you ask consumers what they want, they’ll tell you quite plainly: fast, simple experiences and good prices. Fancy technology and personalization for its own sake? Not so much.
Customers want technology that makes their life easier
Plenty of studies send this message. To pick the one that crossed my desk this morning: “The top technology advancements that consumers want to utilize when shopping in store or online are self-checkout kiosks (38 percent), virtual reality try-on (23 percent) and mobile payments (15 percent). Only 5 percent of consumers selected robots and chatbots as the technologies they most want to utilize.” (The Future of Retail, Oracle Netsuite.)
Look at that carefully: shoppers want technology that makes their life easier. From their perspective, the rest is just fluff.
Of course, the business perspective is different. Chatbots save money, whether or not customers want them. And, so long as customers have the option to reach a live agent, customers won’t necessarily mind going through a chatbot first.
Capture information about individual customers and apply in real time
The trade-off between service cost and service quality isn’t new. Decisions about staffing levels, IVR trees, return policies, and much else have long boiled down to balancing the two. Customer experience managers are well used to calculating the optimal decision in each situation.
What is new is the amount of data that companies can bring to bear on the question. It’s not just that they can capture more data about aggregate behaviors and use it to refine their decision models. It’s that businesses can now capture information about individual consumers and apply it in real time – while the consumer interaction is taking place – to make the right choice for this customer in this situation.
High value customers get VIP treatment
Crude versions of this approach – such as sending high value customers directly to live agents while making less important customers wait a bit, or sometimes longer than a bit – have been deployed for years.
But new technology means those decisions can be much more closely tailored to the current circumstance.
The potential for this is huge and extends well beyond customer service. Prices, offer formats, product selection, contact channels, message frequency, promotional images, and the tone of advertising copy can all be adjusted to each customer in real time.
Systems can know not just what someone has already bought, but what they didn’t buy, what ads they saw, what they’re thinking about buying, what they bought elsewhere, what problems they had, what they told their friends about their experience, and their current emotional state. Waste is reduced, revenue is increased, and customers are more satisfied and more loyal.
Companies can finally escape from the swamp of price competition to the highlands of long-term, trust-filled relationships. Cue the rainbows and butterflies.
Data is the key to success
All it takes is data. Lots and lots of data. That’s where technology comes in: it takes advanced systems to gather all that information from its different sources, put it in one place, knit together the bits that relate to the same buyer, and make it easily available to systems that need to use it. Businesses have tried to do this for years. They’ve made some progress, often by installing department-wide solutions that can, for example, pull together all customer service interactions.
Enterprise-wide solutions have been less common because different departments often organize their data in entirely different, and incompatible, ways. An airline has one system (or more than one) to track rewards club members, another to track tickets, another to track luggage, and still others for equipment, crew members, catering, facilities, and more.
New solutions help make sense of data
Each system works with different entities yet all have an impact on customer experience – and all must be linked to give the all-seeing optimization algorithm the complete information it needs to make the best decision in each situation. Rainbows and butterflies, please come back tomorrow – we’re not quite ready for you yet.
There’s definitely hope. New solutions like Customer Data Platforms (CDPs) are designed specifically to pull in data from all sources, retain the original level of detail, handle the identity matching needed to tie everything to customers, and present it to other systems. Odd as it may sound, this is a relatively new idea: while the need for unified data has long been obvious, it was addressed until recently by custom-built data warehouses and customer information systems, which, like any custom system, were expensive, slow to build, and hard to change.
What’s new about CDPs is they’re packaged software built for the same task. This doesn’t make deploying one as easy as loading a new spreadsheet on your computer, but it does make building a unified, accessible customer database possible for many organizations that could never spare the resources to build their own from scratch. (Full disclosure: I’m head of the CDP Institute and it’s my job to promote the concept. But CDPs are worth looking into regardless of who tells you about them.)
Analyze data and use it to make predictions about actions
While we’re making confessions, I should admit something else: data isn’t really all it takes. You need systems that can make use of what’s been assembled. This means analyzing it to find patterns and relationships that can turn into useful predictions about the consequences of different actions, so you can pick the best ones. And you need other systems that can take those predictions and deploy them as customer interactions take place.
This means the central customer database needs to connect to analytical tools and to customer-facing systems like call centers, Web sites, mobile apps, and their younger cousins such as voice assistants, self-driving cars, and smart home devices. Dropping in a new Customer Data Platform is often simple compared to making changes in the operational systems – although modern systems have architectures that are much more flexible that older products. I’ll just note in passing that the integration between the central customer database and the customer facing systems needs to be two-way, so the central database can react to events as an interaction unfolds.
The biggest barriers are usually organizational
And I’ll even more casually mention that the biggest barriers are usually organizational, not technology. But you often have to start solving the technical problems to uncover the organizational obstacles that lie beneath. The good news is that even a partial technical solution, such as unified customer database that includes only some data sources and is connected with only some analytical and operational systems, can produce significantly useful results. So it’s a path worth following, even if those rainbows and butterflies are further away than it looks.
This post is written by David M. Raab, CEO, Customer Data Platform Institute.