Pricing

The Torrent of Data and What it Means for Pricing

By James Marland
June 27, 2012

numeratiThe book The Numerati by Stephen Baker looks at the effect of big data and mathematics on many areas of society. He has chapters on the power of massive databases and predictive algorithms on the Worker, Shopper, Blogger, Voter, Terrorist, Lover and Patient (key quote: “The next Jonas Salk will be a mathematician, not a doctor”). With no chapter for “Pricer” yet, what can we learn from the way the torrent of data is being used in these other disciplines?

The loyalty card is the secret weapon for retailers and supermarkets. With the patterns of your purchases and the amount you spend, they can see your budget. When they see you starting to buy skimmed milk, they know you are on a diet. They can tell from your history if you are general “brand-loyal” or “brand fickle.” There is even a humorous story wherein Target deduced that a woman was pregnant and began sending her promotions, all before the woman know it herself. With this information they now have the ability to target specific deals to you, and you alone, using sophisticated mathematical algorithms.

Once an adjusted price has been calculated, how to transmit it to the shopper? For on-line grocers this is easy, the web page itself can adjust with messages and new prices. Traditional grocers used to do this with customized coupons on the checkout: but coming to a supermarket near you is a trolley with a screen, indicating special discounts just for you after you swipe your loyalty card.  With their razor-thin margins, it is worthwhile for a retailer to make these kind of investments. In B2B with our double digit margins, we have not typically invested in either the algorithms, or the delivery mechanisms. But the ever-decreasing cost of data warehouses and the availability of algorithms from pricing vendors is changing the dynamic.

If you have a Web channel, then you already have a way to deliver a customized price. Get with your IT department on ways to offer different prices to different segments. If you are using a direct sales force, then you will need a technique such as a Guide Price, or Target Discount which has the ability to change depending on who is doing the buying. If you are selling through a distributor then the way to do this is to use a rebate (also known as price support). For example, suppose you are a manufacturer of domestic boilers, and sell through retailers to businesses and consumers. You have discovered that there are differential price points depending on who is buying, so you allow the retailer to charge only £900 to a business, but £1150 to a consumer. However you don’t trust the retailer (who might claim that every boiler he sold that month was the £900 variety, pocketing the £250 for each consumer purchase), so you require them to send a copy of their invoices once a month to show who the end customer was, in order to claim the rebate.

Ever wonder why you have to fill out those little cards when you buy a product like a boiler? That’s so the manufacturer can get information about you, the end-user: because in the distributor environment they know nothing about you. Not even your name. How valuable is this information? Very valuable, that’s why in certain situations they will bribe you with an additional $10 rebate just to fill out the card (common in US consumer electronics).

Big data and the mathematicians are already here: and are already being used by your suppliers, your doctor, your MP, your supermarket , and your girlfriend (who is right now looking for an upgrade on match.com).

– James Marland

  • B2B Pricing , big data

    James Marland

    James Marland is the Director of Business Consulting at Vendavo based in London. In this role he helps diagnose Pricing Opportunities and develops business cases for pricing projects with ROI models. James has been in the pricing software space for many years, both on the customer and supply chain side: so he has a view from “each side of the table”. Prior to his pricing career he was VP of Solutions at Ariba and has also spent 5 years at SAP America. He has a Bachelor of Science degree in Mathematics from the University of Southampton.