{"id":3013,"date":"2021-12-08T09:13:52","date_gmt":"2021-12-08T15:13:52","guid":{"rendered":"https:\/\/www.dmsi.com\/?p=3013"},"modified":"2024-02-02T11:15:50","modified_gmt":"2024-02-02T17:15:50","slug":"the-aa-bb-ccs-of-pricing-optimization","status":"publish","type":"post","link":"https:\/\/www.dmsi.com\/resources\/the-aa-bb-ccs-of-pricing-optimization\/","title":{"rendered":"The AA, BB, CCs of Pricing Optimization"},"content":{"rendered":"<p>Variable pricing is gaining a lot of attention. Everyone wants a system that can crunch data and spit out a magic number. But chasing a magic number misses the real value of the process. Pricing optimization is not just a software function or calculation. It\u2019s a powerful managerial tool. More specifically, it\u2019s a strategy for improving profit by changing behavior. And when done correctly, it helps provide better service to your customers.<\/p>\n<p><strong>Learn Your AA, BB, CCs<\/strong><br \/>\nPricing optimization starts with customer stratification. Many businesses only use gross sales to rank accounts as A, B, C, or D. But not all \u201cA\u201ds are created equal. For instance, an A customer with a lot of returned items and late payments may not be very profitable. The stratification process accounts for these \u201chidden costs.\u201d It provides a more comprehensive picture of your customers and their impact on your bottom line.<\/p>\n<p>Stratification plots customers in a quadrant. (So instead of simply using A, B, C or D, rankings are AA, AB, AC, AD, BA, BB, etc.) The quadrant is based on two axes: buying behavior on the x-axis and profitability impact on the y-axis. The value for each area is based on a set of variables. For instance, profitability factors include delivery costs, will-call orders, returns, and days past due. Using the quadrant helps separate dependable A and B customers from those with sporadic buying behavior or chronically late payments.<\/p>\n<p><strong>Changing Behavior<\/strong><br \/>\nCustomer stratification doesn\u2019t just show which accounts are most profitable; it shows how to make them more profitable. It\u2019s similar to looking at a class\u2019s test results. The overall grades don\u2019t reveal much, but reviewing the test questions can pinpoint which students have problems with spelling and which have problems with grammar. Likewise, a customer\u2019s AB or CD rating only tells you so much. The stratification process, however, breaks out specific factors. When you know what areas to target, you can respond more effectively. The goal of pricing optimization, after all, isn\u2019t to charge the highest price, it\u2019s to make the highest profit. To really improve profitability, you likely need to change the behavior of both customers and your sales reps.<\/p>\n<p><strong>Change #1: Account Management<\/strong><br \/>\nConsider this (highly simplified) example. Acme Lumber has two customers: Jay Construction and Haas Builders. Both have a profitability ranking of \u201cC.\u201d But if we dig into the specific variables, we can see they have different issues.<\/p>\n<p>Jay Construction usually has just a few items per each order. Haas Builders, on the other hand, makes a lot of returns. This information gives Acme\u2019s sales reps a strategy beyond \u201csell more.\u201d If the reps can help Jay\u2019s Construction consolidate deliveries and Haas Builders improve order accuracy, it would reduce the cost to serve each company. Those accounts would become more profitable, even if their sales didn\u2019t increase. This doesn\u2019t just benefit Acme. If these customers improve their ranking and move into a higher quadrant (say from BC to BB), they may be eligible for better pricing. It\u2019s a win all around.<\/p>\n<p><strong>Change #2: Policy Updates<\/strong><br \/>\nIf a particular variable causes problems across many customers, an account-by-account response may not be sufficient. It could suggest the need for company-wide changes. For instance, if \u201creturns\u201d are a problem for the majority of Acme\u2019s customers, Acme may want to solve the underlying reasons for returns, add a service charge, or change its return policy.<\/p>\n<p><strong>Change #3: Resource Allocation<\/strong><br \/>\nStratification also provides insight about employee performance. Identifying which reps are most profitable can help make decisions about assigning accounts. Instead of going by seniority or sales volume, assign your most profitable people to the most profitable customers. You can also evaluate \u201cstar\u201d reps and look for behaviors that other team members can adopt.<\/p>\n<p><strong>Pricing<\/strong><br \/>\nOnce a business stratifies their customers and performs a similar process with their items, they can calculate optimized prices. Exactly how a business uses optimized pricing is up to each organization. Some may decide to lock down prices, while others may allow reps a bit of flexibility on AA-BB accounts. A third possibility is to use optimized prices as a goal, and reward reps when they near their target.<\/p>\n<p>While owners and managers are excited about the potential of pricing optimization, sales reps are less thrilled. The stratification process may reveal some A and B accounts aren\u2019t very profitable and should be charged more. Reps aren\u2019t going to be happy about raising prices on their \u201cbest\u201d customers and may feel like they are gouging good accounts. Help reps understand that prices stem from both the products and services you provide. Extra attention and handholding represent real costs. It consumes time and money to constantly update orders, process returns, and wait for late payments. You shouldn\u2019t gouge customers, but it\u2019s OK to charge what you\u2019re worth.<\/p>\n<p><strong>Going Forward<\/strong><br \/>\nSome people see pricing optimization as the rise of the machines, with software poised to take the jobs of hapless sales reps. This scenario couldn\u2019t be farther from the truth. Pricing optimization is an extremely hands-on process. It demands deeper conversations about pricing strategy. It prompts businesses to consider the \u201chow\u201d and \u201cwhy\u201d of their decisions.<\/p>\n<p>Software is tremendously helpful. It processes huge amounts of data, runs complicated formulas, and delivers more precise answers. It\u2019s a powerful tool, but it\u2019s still just a tool. It doesn\u2019t know customers, understand goals, or enforce policies. Without active participation, software can\u2019t improve your profitability any more than a FitBit can improve your waistline. Instead of searching for magic numbers, businesses should use pricing optimization as a springboard for greater change.<\/p>\n<p><em>This article originally appeared in Building Products Digest.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Variable pricing is gaining a lot of attention. Everyone wants a system that can crunch data and spit out a magic number. But chasing a magic number misses the real value of the process. Pricing optimization is not just a software function or calculation. It\u2019s a powerful managerial tool. More specifically, it\u2019s a strategy for [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[97],"tags":[],"class_list":["post-3013","post","type-post","status-publish","format-standard","hentry","category-article"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>The AA, BB, CCs of Pricing Optimization - DMSi<\/title>\n<meta name=\"description\" content=\"Pricing optimization is not just a software function or calculation. 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