Pricing Leadership

In one of our latest implementations, we had a scenario where we were getting lower than expected sales adoption of the optimized price guidance in one division of our large distribution customer. Initially when we were trying to determine potential causes, all seemed OK – this division had followed the same change management plan, same training schedule, etc. We had recommended two additional paths to help with sales adoption – matching commission rates to the price recommendations, and publishing a weekly ranking of sales reps and their performance against the price envelope.

Our recommended commission plan changes had largely been adopted. These changes allowed sales reps who priced according to the recommended prices to be paid a higher commission, aligning their goals with our customer’s. 

However, upon a further deep dive into the details, we learned that the head of the sales force for this particular division was not utilizing our recommended published weekly ranking. These “peer pressure” tools were designed to engage the human side of adoption to foster a feeling of competition among the sales reps. 

Each week, the top performing sales reps were noted on their achievement towards the target prices. On this particular implementation, we suggested measuring “value lost” – a metric that measures the number of transactions and associated dollars below the floor price in the price envelope. The top performers had the smallest “value lost”.  Similarly, the worst performers had the most margin dollars to gain by following price recommendations. Both lists were posted in a public place each week, without much fanfare, I might add – people catch onto this type of thing pretty quickly. 

When we asked why he did not post the rankings, the division sales lead said “I already have the financial alignment; I don’t need the rankings.” This is a common misconception, but an important one.  Sales reps in particular are competitively motivated, and using rankings such as these can engage the human side, not just the wallet side. Also, people generally do not share their compensation, so the rankings provide a competitive outlet that can be shared by the team. 

After instituting the weekly sales competition rankings, we saw the adoption of prices noticeably improve, and the basis point increase in margin for this particular division actually outpace the remainder of the company, moving from well-below-average to among the leaders in margin gain! It also fostered a sense of competition among the reps, and became a common discussion topic.

I think the lesson here is important – pricing software implementations are complex beasts, and making sure your company realizes the value that was promised via sales adoption is critical. Use every tool in your toolbox to make sure this happens!

If you are a pricer, marketer, or are in the market for a pricing optimization solution, you have surely heard about “segmentation” and probably have some questions about exactly how it will help you do your job better. I’d like to share some insight from a high-level perspective of how this can help.

Even before the time of the Assyrians, people were segmenting their customers, trying to determine what they would be willing to pay for a particular good. However, we have moved from local markets, where a trader may know all of his or her customers, into today’s varied markets, where businesses may have thousands to tens of thousands of customers. How can a business know each of these customers’ willingness-to-pay for each product they have to sell?

There are many ways of estimating this willingness-to-pay. Most companies have some sort of a “marketing” segmentation, derived through common sense ideas about their product and its value to a particular customer set as well as analyses of customer groups, often via focus groups or survey-based methods. While these methods are good, they suffer from two basic problems: the segments tend to be large, and if a survey method is used, it is subject to interpretation or bias.

Scientific segmentation uses facts that exist in a business’ data to generate micro-segments and isolate small groups of customers, products, and transaction sets (including channels) who have similar willingness-to-pay. The data sets can be entirely historical or include some evaluation of future demand, but they are based on real world data. The challenge is to identify segments such that they are small enough to meaningfully identify willingness to pay but large enough to still contain variance in the data, for the value in segmentation is in the variance: identifying which customers are UNDERPERFORMING their peer group and correcting prices to those customers.

The segmentation process uses attributes to create these micro-segments that often go far beyond what are considered in marketing segments. For example, in the much sought after “25 to 40 year old single male” market segment that many consumer electronics companies target, chances are that a particular customer’s willingness to pay depends on many more factors than his age, gender, and marital status. Including additional attributes such as income level, geographic location, and others starts to get a better picture.

The end result is a segmentation of your customers, products, and/or transaction types – whatever is appropriate for your business. These segments can help you identify a multitude of things: what price to charge for a given transaction, what terms should be on a contract, what products to bundle together, or even what products to offer at all.  Having a granular approach to segmentation along with a process for implementing pricing decisions influenced by these segments can dramatically increase a company’s profitability.