As insightful tools go, it’s difficult to beat sales analytics. At a stroke, you’ve got ready access to all those clever Amazon-style insights into such things as ‘customers who bought this are likely to want to buy that.’ But sales analytics can do more than that—much more.
Better still, while all those Affinity Analysis and Basket Analysis data mining analyses deliver powerful insights into customer behaviour, it’s possible for basic out-of-the-box sales analytics to have an even greater impact on businesses’ bottom lines, without getting into the complexities of full-blown data mining.
How? By using sales analytics to run simple and straightforward analyses of customer profitability, pulling in sales revenue data, margin data, and—if appropriate—‘cost to serve’ data, such as logistics costs, or special packaging, or delivery stipulations.
Such analyses are quick, straightforward, and provide ready insights into which levers to pull in order to increase overall profitability.
Sales analytics: Who are our most profitable customers?
Here’s a hint: it’s not necessarily the customers who you think are the most profitable. Run the analyses, in short, and you can quickly find that the margins that your sales people are accepting in order to retain your very largest customers are in fact tending to push those customers down the profitability table.
How far down? That depends on the business. But we wouldn’t be surprised to learn that your top five customers are less profitable than your next five largest customers. Or that those ranked 11th to 20th are more profitable than those ranked 1st to 10th.
Not in terms of aggregate absolute profit earned necessarily (although that can happen). But certainly in terms of percentage margin, especially if cost-to-serve factors are taken into account.
Sales analytics: Who are our least profitable customers?
Again, these aren’t necessarily who you might think. And admittedly, cost-to-serve often plays a part here.
So rather than necessarily focusing on negotiated margins, look for concessions made on packaging or shipping charges, or special deals in terms of delivery frequency.
And again from a cost-to-serve perspective, also take a close look at what you’re selling, as opposed to who you’re selling it to. If you’re maintaining entire product lines just for one or two customers, then alarm bells should be ringing.
Sales analytics: How can we take corrective action?
Clearly, in terms of boosting the bottom line, it’s impossible to wave a magic wand and simply swap less profitable customers for more profitable ones.
But in practice, a magic wand isn’t necessary.
It’s simply necessary to know why some customers are less profitable than others—and then corrective action can be taken.
Are incentives to the sales staff encouraging too much discounting? Are larger customers imposing overly-onerous conditions? Is a process of product rationalisation called for?
Better still, by looking at those characteristics that are shared by your more profitable customers, it’s possible to shape offers so as to be more attractive to that type of customer. Capturing more-profitable customers, in short, at the expense of less-profitable customers.
It’s not an overnight process, to be sure. But it’s certainly a journey where sure-and-steady progress is very possible.
Sales analytics: the bottom line
Despite which, all too few businesses engage with sales analytics in order to find the starting point necessary to commence the journey.
Don’t be one of them. Because as low hanging fruit go, making improvements to customer profitability ranks among the most straightforward means possible of boosting the bottom line.
So start the journey today.
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