How important is it to get pricing right? According to McKinsey, a 1% price increase, on average, yields an 8.7% jump in operating profits—assuming no change in volume. But as many as 30% of pricing decisions made by companies every year are not achieving the best price. The result? A lot of money is left on the table…a lot of lost profit opportunities.
Price optimization, which I discussed in my last blog: What Happens When You Get Price Optimization Down to a Science?, gives you the target price—the bullseye. But above and below that target is a range of prices that give you an acceptable probability of sales success. This range is known as the price corridor.
The corridor provides the guardrails which guide your sales reps when negotiating a deal. For example, your corridor may suggest you have an 80% chance of success if you sell your widgets between $5.00 and $6.00 apiece.
When your sales rep goes in, there is an opportunity to negotiate. But how much wiggle room do you really have? The price corridor is your playbook for negotiation. It helps you know where to start and how low you can go. Should you try for $7.00 per widget? Do you have to discount to $4.50 in order to get most deals? Knowing (and trusting) the corridor helps you know what leeway you have.
Many companies establish price policies for sales to use in negotiation, and sales reps can’t offer a price above or below those spelled out in the policy without approval. But how are these policies established? If the spread is too narrow, you may lose sales, and if it’s too wide, you can give up too much margin on the low end—if you don’t scare away business with quotes that start too high.
A price corridor is based on a deep analytical understanding of customer behavior, recent wins and losses, and market trends. It is also based on data science. Using machine learning, software can analyze which customers behave similarly and for which products. The software can analyze wins and losses to establish levels of probability for winning at a price for customer/product combinations. Deriving your company’s price policies from scientifically determined price corridors is a better way to provide guidance to sales teams so they can hit close to the mark in opening bids and be more confident in preserving prices—and more importantly, margins.
Advanced software can calculate your high, low and target prices more scientifically and faster than you can do it manually. It can also help you set and enforce price policy by preventing activation of an agreement (or launch an additional workflow for exception approval) if the numbers fall outside of the policy. This supports the process of keeping sales reps on target, with a smart way to allow them to deviate when necessary.
Price corridors move all the time, sometimes only a little and sometimes suddenly and significantly. Another advantage of software with machine learning is that it can constantly look at your transactions to see if your corridors—and consequently, your price policies—need to shift.
You can be more agile when the software does it for you. If you’re doing it manually, you probably aren’t shifting as soon and as frequently as you should after a major market event. For example, the COVID pandemic changed sales patterns dramatically for many products. With software constantly looking at sales data as it comes in, you can quickly evaluate how your corridor is shifting and how you should be changing your pricing.
At Vistex, this functionality is built in so you can be sure it all adds up to the best price every time.