Spend any time on the roads of Britain and the delivery trucks of catering supplier 3663 quickly become a familiar sight.
Selling fresh and frozen foods to pubs, schools, restaurants and canteens, the firm (whose name spells “F-O-O-D” on a telephone keypad) offers some 19,000 product lines to its 60,000 customers, delivering daily to their kitchen door.
Yet, behind this most ordinary of companies lies an initiative that’s firmly at the cutting edge of business technology and one which links advanced database technology to sophisticated analytics tools in order to provide compelling insights into customer behaviour.
It also provides insights but, what’s more, it delivers tangible benefits that flow directly to the bottom line. At 3663, for instance, sales of catering supplies to new accounts since the analytics solution went live have achieved a 2.6% improvement in margin, versus the 0.5% predicted in the business case for the investment. In addition, according to 3663 head of pricing Trevor Pearson, of 932 new accounts opened none have subsequently been lost, evidence, he said, of improved customer retention.
Meanwhile, in the European operations of computer and printer manufacturer Hewlett- Packard, an initiative to incentivise junior and middle-ranking sales staff on achieved gross margin, without actually disclosing those confidential margin figures to sales staff, is starting to bear fruit, driven once again by better analytics, and a proven methodology for translating analysis into hard-nosed pricing strategies.
“We were brilliant in understanding our top 1,000 customers but we had a million customers we knew almost nothing about,” said Michael Immenschuh, senior manager for pricing process and capabilities in Hewlett-Packard’s pan- European operations.
The result? As at 3663, a combination of gross margin left on the table in the form of ‘low ball’ pricing offers, and deals missed through pricing offers and bundles of products, which were out of step with customer expectations and affordability.
No longer, it seems. Now, explains Immenschuh, armed with a better understanding of customer behaviour, the electronics giant is finally able to provide detailed margin-enhancing price guidance to front-line sales staff, without risking its competitive position by disclosing actual profit margins.
Compelling stuff, in short. And behind both developments lies pricing analytics and optimisation consulting software delivering Amazon.com-style insights into products and services they are not currently buying but which are bought by customers very similar to them.
For companies like Hewlett-Packard and 3663, such insights into customer behaviour provide intelligence, not only into the extent which pricing can be improved, but also provide guidance on strategies for closing the gap between current prices and those which can theoretically be achieved.
Finnish chemicals manufacturer Kemira, for instance, is using these pricing tools to try and close a 5-10% gap that it sees between target prices and achieved prices. Danish biotechnology manufacturer Novozymes, meanwhile, is using analytics-based insights to first of all enforce existing pricing policies and then remove price anomalies that have “left money on the table,” according to the company’s global marketing officer, Peter Faaborg-Andersen.
How then does pricing technology work? Strip away the statistical jargon and a carefully- refined three-stage process is revealed. The starting point is segmentation–simply put, data- mining a wealth of customer transactions to see patterns which enable similar customers to be grouped together. In short, by using past sales data, product data and any data available on lost sales and customer attrition, it is possible to segment markets by key characteristics such as business size, likely sales volumes, transaction history and similar distinctions.
And typically, it turns out, statistical analysis provides a richer picture of customer behaviour than crude rules of thumb, or salespeople’s own estimates.
3663, for instance, had grouped customers geographically, said Pearson, dividing its UK market with a simple North-South split. Analytics, he explains, showed that not only would a three- way split be more accurate but that a better way altogether would be to segment customers by their requirement for additional services. This then demonstrated their willingness to pay.
Next comes pricing strategy. Simply put, the idea is to compile statistically-grounded predictions as to the effectiveness of given price pitches for given products and bundles of products.
Typically, for instance, analysis might suggest an ‘expert’ price, perhaps to be used as a starting point, or achieved by an expert salesperson. At a ‘floor’ price, the salesperson will be instructed to walk away, in order to counter salespeople’s tendency to drop prices to levels that might win the business but which deliver little gross margin. And in between, there’s a ‘target’ price representative of a good deal with an acceptable margin.
It’s precisely this kind of price segmentation that Hewlett-Packard’s Immenschuh regards as so invaluable in the fight against margin erosion – erosion, he points out, that less than a decade ago caused what he characterises as a “massive and surprising miss on gross margin”.
“We don’t need to disclose margin numbers, but we can still measure salespeople on margin,” he said. “How often did they go to ‘floor’? How often did they go to ‘typical’?”
That said, a recent gathering of pricing experts in Brussels made clear that the software is no ‘plug and play’ easy option. Its role is to provide the basis for better decisions, rather than actually make those decisions.
At Kemira, for instance, director of marketing and product management Peter zum Hebel freely admits to treading carefully when attempting to convert suggested prices into achieved prices.
“We did a lot of interviews with customers while performing our segmentation, and these interviews gave us clues as to likely price elasticity,” he said. “We’re trying to balance the prices and service levels that each segment of customers is after. And now, we’re running tests to see if we can increase prices to match those that the theoretical models suggest."