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Optimising customer experience by leveraging emerging and new technology results in a host of positive spin-offs for businesses but it must be approached in a methodical and strategic manner. Every intervention or technology application relies on how a business collects and associates data with its customers.
Ultimately, customer service, and by extension, the customer’s experience, lies in the expectations that are set and how the business is measured against those expectations. There are a number of ways to make this more efficient and proactive, but they rely on getting the basics right, in other words, how the data that already exists in the business is used.
Most businesses have data already. This comes in the form of in-bound phone calls, emails, web forms or even walk-ins to physical shops and using store cards. The first port of call lies in being able to use this data to identify the customer efficiently.
A challenge we often encounter is that a business does have data, but it is primarily focused on information about the customer’s business relationship with the business – products and services.
To improve CX, the associations need to move beyond product and towards preference. You absolutely need to get to a point where you can store a customer’s preference. For example, imagine the system picks up that the customer has spoken to the business before and interacted with a particular call centre agent and rated them 10 out of 10. That is valuable information that stores this customer’s preferences. By building up a repository of this type of information, the business is laying the foundation to start using predictive models driven by artificial intelligence (AI), for example.
However, if a business cannot efficiently identify a customer and associate their preferences, then it is wasting its time thinking about emerging technology. You cannot run a predictive model on random variables with the expectation that it will result in the outcome you are looking for.
