Getting to “the price is right”

Companies make thousands of pricing decisions every year. But many of those decisions – up to 30 percent of them, we estimate – fall short of the best price a company can get.

Getting to the price is rightThat’s a lot of lost revenue. If you can increase the price of a product by 1 percent, that translates into an 8.7 percent increase in operating profits on average (assuming no loss of volume, of course). These pricing opportunities, however, are lost in today’s flood of big data and multichannel complexity. Price points need to keep up with the explosion of customer touch points.

Without uncovering and acting on those opportunities, many companies are leaving millions of euros of profits on the table. We believe that to increase profit margins, companies must find the best price at the product – not category – level. Business leaders need to get much more granular.

“To increase profit margins, companies must find the best price at the product – not category – level.”
Too big to succeed
For each product, companies should be able to find the ideal price that a customer is willing to pay. Ideally they’d factor in deep insights like cost of the next best competitive product vs. the value of the product to the customer, for example, and arrive at the best price.

For a company with a handful of products, this kind of pricing approach is pretty straight forward. The problem is when product numbers balloon. About 75 percent of a typical company’s revenue comes from “standard” products in their portfolio. These often number in the thousands. The manual and time-consuming practices for setting prices make it virtually impossible to see the pricing patterns that can unlock value. It’s simply too overwhelming for large companies to get granular and manage all the complexity of these pricing variables – which are constantly changing – for thousands of products. This is a “Big Data” issue at its core.

Many marketers end up simply burying their heads in the sand. They develop prices based on simplistic factors like the cost to produce the product, standard margins, prices for similar products, volume discounts, etc. They fall back on old practices to manage the products as they always have or cite “market prices” as an excuse for not attacking the issues. Or they rely on “tried and tested” historical methods, like hiking prices on everything by 10 percent.

8.7 percent Increase in operating profits by increasing price of a product by 1% without
losing volume

Value the power of value – for every product
We believe that to get granular, companies need to:

“Hear” what your data is saying. Setting the best prices is not a data challenge (companies generally are already sitting on a treasure trove of data already). It’s an analysis challenge. While the best B2C companies have gotten good at making sense of the wealth of data that they have, B2B companies have so far more administered their data rather than used it to drive decisions. Good analytics should move beyond the basics and help companies identify how factors that are often missed – like the economic situation, product preferences, sales rep negotiations, etc. – reveal what drives prices for each customer segment.
Automate. It takes too long and is too expensive to do the necessary analysis on thousands of products manually. You need to develop automated systems that analyzes customer data to identify narrow segments, determine what drives value for each one, and match that with historical transactional data. These factors will allow you to identify and set prices for targeted “clusters” of products and segments based on hard facts. Automation also allows you to replicate your program over time and make adjustments so you’re not starting from scratch every time.
Implement and track. Implementing new prices is as much a communications as an operational challenge. The value drivers that many companies articulate in their strategy papers are often different from what customers actually perceive. You need to clearly understand what drives value then communicate that, along with the new target prices, to your sales force. You’ll also need to adjust existing pricing policies and performance measurements, and create new incentives.
Then track performance against original targets. In our experience, there’s always variance at this point, which needs to be communicated back into the pricing organization so prices can be readjusted.

Margin lift off
We’ve tested this approach with a number of companies in industries as diverse as packaging, chemicals, or construction material. They all had similar profiles in terms of huge numbers of SKUs and transactions, as well as a fragmented portfolio. We identified improvements in profit margins of 3 to 8 percent by setting prices at more granular product levels. In one particular case, a European building materials company was able to identify new prices that increased margins up to 20 percent for selected products.

To get the price right, you need to get granular with your “Big Data.” Or you may find yourself paying the high price of lost profits.

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