Why customer analytics matters
As computers and the internet have evolved, the capacity of companies to capture information about their customers has grown exponentially; but that simply means that companies have more data than ever before; but data on its own has little meaning. The challenge has always been to interpret that data and to be able to take meaning from it.
Richard Kimber
I’ve always believed that customer analytics should be focused on understanding the behavioral differences between customer groups as well as understanding segmentation.
Where we go in the future will be shaped by the systems becoming more autonomous and more predictive, gaining in specificity and granularity. We're going to have systems that will predict the next best action quite accurately for any particular customer, and help companies to anticipate what their buyers want. We’re already seeing companies like Amazon start shipping the next predicted items that they think you'll want to buy, proactively. If you don't want it, you can send it right back, but their data shows that the accuracy of their predictions is paying off.
On a broader base, there's also going to be a lot more transparency around good customer experiences versus poor. One of the things that is becoming increasingly important is that more than ever, customers have a voice. Social media means that they speak up, and it's easy to understand how companies actually operate.
That directly impacts on how you approach marketing and how you promote your services. The linkage between customer analytics and marketing is as tight as ever, and I think it's only going to grow stronger
Getting started with customer analytics
Having clarity around your strategy, and then understanding what other key metrics you should focus on are critical. It’s not over analyzing the numbers and looking at 500 different factors. It's getting it down to a manageable dataset that you look at frequently.
You can't be everything to everyone. You have to have a target customer group that you really want to delight. That's what the most successful businesses do very well; they know who their customers are, and they’re able to target their analysis towards their key desired customers. They're not trying to please everyone. They’re not trying to understand everyone. And that is an advantage on its own.
You need to look at your positioning relative to your competitors, and be clear about where you aim to be differentiated, building out a clear understanding of your strategic positioning. You can then relate your customer feedback around how well you're executing against your desired positioning.
Simply looking at the data in isolation won't always give you an insight into your performance; it's got to reflect on your strategy. For example, if you're a premium brand, are you attracting the kind of customers that you want? And are they satisfied with what you're providing? Do they feel that luxury intent?
If you’re just starting your customer analytics journey, you have to take that first step of aligning your target customers with your goals, plans and positioning, and kick off your analysis by identifying where they match and where they don't.
I've seen companies that go into analysis paralysis, and just look at data endlessly. It's got to be actionable, it's got to be insightful, it's got to be value added. At the end of the day, customers change as well. One of the dangers of becoming overly focused on numbers and data is that it is often historical; companies need to be looking forward and remaining progressive as customer attitudes and needs change. Companies that are attuned to that are going to survive. It's not about looking at what happened yesterday, it's all about what's going to happen tomorrow.