Suffering from Price Matrix Drift

Taking the big picture view, how do you think about all the various types of pricing? How are they structured in your company? What’s their purpose?

For instance, do any customers ever purchase at the published list price? Do large groups of customers get price schedules that are slightly, or significantly, less than list? Do your best customers get the most favorable, custom pricing in your contracts or agreements? Do you have some or all of the above, yet still find that prices are frequently negotiated down at the time of order?

It’s been my experience that, while B2B companies can vary greatly when it comes to pricing most have some mix of the price approaches, or price modes, listed above.

Price Structure & the Matrix Drift

In an ideal scenario, price structure would be perfectly optimized across all modes. Large, strategic accounts would receive better prices than one-time orders. On-the-spot negotiations would happen within a range of start, target, floor prices that win business without sacrificing margin.

The long tail of customer accounts, or those in the middle, would be segmented into similar groups based on buying attributes and given appropriate pricing levels i.e. they would be assigned to the price matrix. For example, customers in the automotive sector, with $50,000 - 100,000 annual purchase volume, purchasing for delivery in the southeast, will receive prices from Matrix B, and so on. There may be dozens of defined matrix levels available to address your markets.

However, we operate in imperfect scenarios. If not continually and correctly tended to, your price matrix itself can drift significantly over time. The results are unattractive: Non-strategic customers get sweetheart deals you really don’t believe in, or premium products get underpriced compared to their more basic cousins, and overall your profitability suffers. No single thing is to blame, but when it happens across thousands of daily transactions, the aggregate impact is sure to hit your P&L.

Pricing drifts because of decision complexity – and complexity is what prevents us from noticing the symptoms. B2B company datasets are too large for BI and fancy spreadsheet wrangling to continually surface issues, or better, preempt them from happening.

Symptoms, Diagnosis & Cure

Based on my experience using AI and data science to address matrix drift, here are the top four symptoms you’re suffering from a major case of matrix drift in your organization:

• Symptom No. 1: My matrix prices are irrelevant (generally too high) and Sales ignores them by frequently using overrides and customer agreements. 
• Symptom No. 2: My matrix prices are irrelevant (generally too low) and I’m leaving money on the table every time I price an invoice on-matrix. 
• Symptom No. 3: My matrix is too large and cumbersome to keep it updated properly so prices are often outdated or stale. 
• Symptom No. 4: Over time, Customers tend to cluster onto the matrix with the lowest prices even when they don’t deserve them.

If you’re experiencing one or all these symptoms, the good news is that data science can course-correct matrix drift. This ensures that customers are appropriately assigned, price levels are aligned to the market, and provides you with the system and process to conduct matrix health checks and update as often as necessary.

Please reach out to us if you’re interested in diagnosing the data in your own organization to see if the symptoms of matrix drift are present.

About the Author

Barrett leads the Business Solutions Consultant team, aligning Zilliant solutions to customer needs and promoting pricing and sales best practices among our customers. Over the past two decades, Barrett has built and delivered optimization and pricing solutions to Fortune 500 businesses in diverse vertical industries including: building materials manufacturing and distribution, industrial components manufacturing, semiconductor manufacturing, office-supply distribution, hardware-software distribution, pharmaceutical and medical-device distribution, telecommunications, and multiple travel & transportation verticals. Barrett received both his Bachelor of Science in Applied Mathematics and his Master of Science in Operations Research from the Georgia Institute of Technology.

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