Getting customers is one thing; keeping them is something quite different. There was a time in the past when price was considered the only factor, but of course it is so much more complex than that. The many ways in which customers now interact with a brand on- and offline now make it hard to identify an individual customer, let alone understand them. Where the transaction was tied to the store in the past, interactions can occur in any number of ways online now – following a customer’s behavior, likes and dislikes is harder than ever before, despite the information available. But like it or not, it is a critical factor in being a successful retailer.
Understanding the point at which a customer increases their contact and purchasing with you is important but even more so when the opposite occurs. When that moment happens, there is a tiny window of opportunity to regain their love and keep them, before they move on to another brand. The cost of regaining that customer could be massive.
There are several components to succeeding in this area. The first is learning where you have information about your customers. But that in itself can be extremely complex – how many discreet systems and channels does your business use to interact with customers? Some of them may even be provided by third parties.
Once you know the channels, you can start to look at the discreet information that you are (or are not) capturing that you could be using and how that could be unified across your entire data ecosystem. The temptation is to capture it all, of course, but you could be making life hard for yourself by doing that. It all has to be stored somewhere, and ultimately you have to be able to process it.
The final piece is to think about the processes, people and analytics that are needed to make sense of all of that data. Without a major change-management effort, most people will keep thinking, planning and executing in the same ways. Everything will be on a micro –level when what is needed is wholesale macro-change. The right people with the right mix of analytical and business experience need to be on board to use much more rigorous decision-making processes; standardize processes across systems, analysis and geographies; and synchronize efforts across the organization. Superior data management is essential to providing refreshed and regular customer insights, and powerful tools need to be available that don’t require an advanced computer science degree to use.
Transformation on this scale is difficult and takes time. The “chain to impact” includes both human and organizational factors such as people and process, as well as technical enablers including data, solutions and advanced insights. A typical transformation effort has a roughly 30 percent chance of achieving the targets set by the company. But companies who commit to using an evidence-based approach, building the right analytical team, and leveraging the latest insights and solution breakthroughs succeed with transformation efforts 90 percent of the time.
It’s not an easy journey, but as a business grows it becomes harder to stay close to the customer and even harder to implement wholesale change management. There’s never a good time to undertake a project of this nature, but the same could be said about losing customers.
I’ll leave you with this thought. It doesn’t matter how your customer shops or interacts with you. They see you as one brand — one organization. Can you really say you can see and understand them in the same way?
Contributor
Lars Fiedler, VP and Solution General Manager Marketing Solutions at Periscope By McKinsey.
