A survey by TechRepublic shows only 5.2% of organisations are using full data analytics on a daily basis to influence customer behaviour, and thereby, differentiate themselves on customer satisfaction. That's a remarkably small percentage, given that most companies already have in their possession the kind of information about their customers that can be used to cross- and up-sell them - or, more fundamentally, create customer satisfaction. In other words, significant revenue-generating opportunities are being lost.
Collecting information about customers is no longer rocket science. There is no need, today, for cripplingly expensive software, mainframe computers, or brainy statisticians beavering away in a corner. Intuitive applications on a laptop will do.
That aside, any company that has done a financial transaction with a customer probably knows the customer's age, gender, address, phone number, marital status, and occasionally, race.
All of this quite basic information can yield some way of improving customer satisfaction. An address provides insight into a person's lifestyle and financial status. A change in the address to, perhaps, a more upmarket area, should flag the customer for offers of new products and services appropriate to his or her new lifestyle.
A change in a woman's surname could imply a marriage, and therefore, open the way for a simple congratulatory e-mail, if not the offer of new products and services.
So, the logic is simple. If the fundamental information most companies already possess can help a company create fresh revenue streams, then the advanced data assets one gets from data analytics will make an even bigger difference - to the customer, and through increased loyalty, to a company's bottom line.
Why, then, are so few companies exploiting it? One of the biggest reasons is lack of strategy, followed closely by inertia in the face of change.
Strategy vacuum
According to the Global Contact Centre Benchmarking Report, 80.6% of organisations claim to want customer satisfaction because it's a differentiator. There's very little evidence, however, that customer satisfaction is seen as a matter of strategy rather than operational, and is, as a consequence, being steered by the board or exco.
Collecting information about customers is no longer rocket science.
When it comes to data analytics, for instance, companies are not looking beyond static information, such as age and gender, to the more fluid and complex data inter-dependencies and patterns that would give them better insight into customer behaviour. They're not trying to understand what the common preconditions are for customer churn. So, they can't prevent it. They're not studying customer disillusionment to discover how long it takes to kick in, and under what circumstances, and therefore, how to head it off. They're not even examining customer value.
Small wonder there's no strategy. A strategy can't be built if a company doesn't know what the underlying problem is.
Refusing to sell the gold
Interestingly, the real problem isn't that companies aren't asking their systems about customer details. They're not even asking what it is the customer wants from them. Their focus, rather, is on what they can push to the customer. A shift from the latter attitude to the former can be initiated only at the top of an organisation.
Also, having the right attitude and information isn't the end-game. Both have to be converted into revenue by being used to satisfy customers. The medium for achieving that is customer-facing staff. So, there needs to be a data distribution strategy. Who needs what information, under which circumstances, and at what levels, in order to resolve customer queries effectively, and to up- and cross-sell?
Clearly, the data needs to be packaged in slightly different ways to suit different customer-facing scenarios. But there is one common denominator: For any customer-facing employee, whether in a branch, on the shop floor, or in a contact centre, to have a chance of truly meeting a customer's needs, he needs a single view of the customer.
More than 50% of companies don't provide this. As a result, contact centre agents, for instance, are never fully equipped to make a decision about a customer that would increase that customer's loyalty. There's always a gap in the agent's knowledge of the customer.
A remarkable phenomenon is developing. Even when they're investing in data analytics, companies are not investing in the mechanisms (software and people) for delivering essential data to points in the organisation where it can earn revenue. That's a bit like spending vast amounts of money digging gold out of the ground, but then refusing to make any money back by transporting it to those who can beneficiate it.
That can't be a deliberate strategy... can it?
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