Yet pricing strategically the most critical aspect of any retail business has somehow managed to bypass the IT department and remains driven by a remarkably old-fashioned combination of intuition and pure guesswork.
At least, that is what the new breed of retail revenue management or dynamic pricing' companies crossing the pond and promising to apply a bit of rocket science to our rsps would have us believe.
Take a typical superstore, says Tim Manning at RRM specialist KhiMetrics, which is now implementing its technology at one of the top four UK multiples. Prices are probably monitored extremely carefully on the top 1,000-2,000 products in the store. But what about the other 30,000?
Several different scenarios are likely, he suggests. One establish what the cost price is and slap a fixed margin on top. Two see what the local competition is offering and match it, or three a combination of the above.
One thing conspicuously absent from all of these approaches, he argues, is any objective measure of the relationship between price and demand. In other words, traditional pricing strategies do not reflect which products are actually sensitive to fluctuations in price, and where retailers could safely boost margins without compromising their brand.
Enter dynamic pricing.
Put simply, this means matching prices, for a seat on a plane or a can of Pepsi, with demand, within strict parameters. Which does not mean charging 10 times the going rate for the Pepsi because it's hot outside or because you are the only store around.
One thing dynamic pricing emphatically is not, emphasises Manning, is finding the highest price customers are willing to pay. What it does is find the optimum price within the framework of an existing pricing model, whether it's EDLP, Hi-Lo or anything else.
By trawling through a couple of years of EpoS data, retail revenue management companies explore the relationship between purchasing habits and price, as well as the spin-off effect on one product from discounting another and come up with an optimum price for every product.
And this can be applied across a category, a store, a region, or an entire chain.
In the laundry fixture at a supermarket, this might mean reducing prices on a few big sellers and notching them up on a few slower moving lines, boosting net profits and driving category sales without compromising your price image.
At an airline, it might mean using real time information about every seat and adjusting prices as demand changes. Indeed, this approach is now commonplace in telecoms, where different pricing bands operate at different times of the day.
Too often, says Demandtec, another RRM specialist targeting the UK, retailers will drop prices to match competition on products that customers will buy anyway, pointlessly sacrificing margin.
Demandtec, which is working with one of the UK's top three multiples, as well as US supermarket Kroger, says simply by actively managing a higher percentage of their prices, supermarkets could unlock enormous sales and profit opportunities.
In an eight-week trial, in which Demandtec optimised' prices for US chain D'Agostino across seven categories in 10 stores, sales went up 9.7%, and net profit went up 2%, says senior VP of marketing, John Shap.
"The figures speak for themselves."
AMR Research retail strategist Greg Girard says: "It's pretty well understood that UK multiples do things better than a lot of grocers in the US. But when it comes to optimal pricing, the yanks have stolen a march on the Brits!"
KSS, which is at the initial price modelling stage with one of the top three UK supermarkets and two forecourt chains, says RRM helps clients base pricing decisions on analysis rather than intuition.
KSS senior vice-president, marketing, Mark Hawtin says: "You'd be surprised how many retailers we've spoken to don't really evaluate the impact of promotions properly. Yes they know how many extra cases they sold, but they don't really know what effect the promotion had on the rest of the category, or on products typically bought with the item on promotion, or how changing the price of brands impacts sales of own label equivalents and so on. That's where we come in."
{{ANALYSIS }}
At least, that is what the new breed of retail revenue management or dynamic pricing' companies crossing the pond and promising to apply a bit of rocket science to our rsps would have us believe.
Take a typical superstore, says Tim Manning at RRM specialist KhiMetrics, which is now implementing its technology at one of the top four UK multiples. Prices are probably monitored extremely carefully on the top 1,000-2,000 products in the store. But what about the other 30,000?
Several different scenarios are likely, he suggests. One establish what the cost price is and slap a fixed margin on top. Two see what the local competition is offering and match it, or three a combination of the above.
One thing conspicuously absent from all of these approaches, he argues, is any objective measure of the relationship between price and demand. In other words, traditional pricing strategies do not reflect which products are actually sensitive to fluctuations in price, and where retailers could safely boost margins without compromising their brand.
Enter dynamic pricing.
Put simply, this means matching prices, for a seat on a plane or a can of Pepsi, with demand, within strict parameters. Which does not mean charging 10 times the going rate for the Pepsi because it's hot outside or because you are the only store around.
One thing dynamic pricing emphatically is not, emphasises Manning, is finding the highest price customers are willing to pay. What it does is find the optimum price within the framework of an existing pricing model, whether it's EDLP, Hi-Lo or anything else.
By trawling through a couple of years of EpoS data, retail revenue management companies explore the relationship between purchasing habits and price, as well as the spin-off effect on one product from discounting another and come up with an optimum price for every product.
And this can be applied across a category, a store, a region, or an entire chain.
In the laundry fixture at a supermarket, this might mean reducing prices on a few big sellers and notching them up on a few slower moving lines, boosting net profits and driving category sales without compromising your price image.
At an airline, it might mean using real time information about every seat and adjusting prices as demand changes. Indeed, this approach is now commonplace in telecoms, where different pricing bands operate at different times of the day.
Too often, says Demandtec, another RRM specialist targeting the UK, retailers will drop prices to match competition on products that customers will buy anyway, pointlessly sacrificing margin.
Demandtec, which is working with one of the UK's top three multiples, as well as US supermarket Kroger, says simply by actively managing a higher percentage of their prices, supermarkets could unlock enormous sales and profit opportunities.
In an eight-week trial, in which Demandtec optimised' prices for US chain D'Agostino across seven categories in 10 stores, sales went up 9.7%, and net profit went up 2%, says senior VP of marketing, John Shap.
"The figures speak for themselves."
AMR Research retail strategist Greg Girard says: "It's pretty well understood that UK multiples do things better than a lot of grocers in the US. But when it comes to optimal pricing, the yanks have stolen a march on the Brits!"
KSS, which is at the initial price modelling stage with one of the top three UK supermarkets and two forecourt chains, says RRM helps clients base pricing decisions on analysis rather than intuition.
KSS senior vice-president, marketing, Mark Hawtin says: "You'd be surprised how many retailers we've spoken to don't really evaluate the impact of promotions properly. Yes they know how many extra cases they sold, but they don't really know what effect the promotion had on the rest of the category, or on products typically bought with the item on promotion, or how changing the price of brands impacts sales of own label equivalents and so on. That's where we come in."
{{ANALYSIS }}
No comments yet