Assessing Price Sensitivity

Price sensitivity is a tricky subject to interpret correctly – doubly so in the tight timeframes common to current diligence windows. I’ve seen a lot of consulting reports that I believe misinterpret price sensitivity – either overstating or understating price in a ranking of decision makers’ Drivers of Choice. The importance of price in decision making is a critical question in any maturing (or mature) industry and can become a greater factor in an economic downturn.

The literature on technical pricing methodology is vast, but applying theory to real-world diligence (or value gen exercises) can be a challenge that is subject to significant and costly misinterpretation. I have outlined three common problems that make measuring price sensitivity challenging – and my recommendations on how to address these challenges.

Problem 1 - Self-Reporting: Asking business owners and operators to self-report price sensitivity may produce false positives or false negatives. Acknowledging that you pick a product or a vendor based on price carries an uncomfortable load for many buyers – and can lead to false testimony about its importance. In a recent diligence case, decision makers were reluctant to admit that price mattered as much as it does, because they did not want to give the impression that they cared less about product quality or about differentiation. However, as we dug deeper throughout the analysis, we found that price proved to matter more than these other factors due to the perceived tight range of quality and differentiation among qualified vendors, and the margin pressure within the sector.

Recommended Diligence Approach - Indirect Questioning to Remove Bias: To help address the risk of failing to admit the importance of price, we can take a lesson from a little-known political polling firm called The Trafalgar Group. Trafalgar ran one of the few polls that predicted Donald Trump’s 2016 presidential victory. In addition to asking survey respondents who they planned to vote for, Trafalgar asked who they thought their neighbors would vote for [1]. Trump performed better in the latter question, which caused Trafalgar to adjust its model and predict the election outcome accurately.

By following a similar methodology for Drivers of Choice research, in which we ask about how a B2B customer sees price as well as how they think their competitors and peer companies see price, we can create a more accurate understanding of how customers really consider pricing.

Problem 2 - Competing Incentives: Another mistake I commonly see is when diligence efforts neglect to consider specific performance management measures and/or incentive structures that exist for buyers. Oftentimes, these serve to compromise what you would expect to see as rational economic behavior. I find the existence and impact of functional and role-specific incentives can be even more profound in larger companies, given more complex hierarchies, bonus structures, and internal reporting practices.

Recommended Diligence Approach - Unearth Incentives that Drive Personal Behavior: In a recent engagement, we discovered (by asking multiple rounds of "why") that procurement managers for a somewhat commoditized set of industrial products were particularly focused on the shipping cost line item in the P&L, more so than actual unit costs, which helped explain strong margins despite limited differentiation. The buyers acknowledged paying less attention to unit costs - i.e., they were willing to forgo shopping for price on these purchases and instead commonly elected to take advantage of shipping cost discounts (for volume) offered by certain vendors. Why? Because the procurement managers found that the easiest way to get credit for realizing savings was to point to the shipping line item in the P&L; they were rewarded for being able to demonstrate their ability to drive “savings” (which appeared even more enhanced due to their employers measuring shipping costs as a percentage of unit costs). We learned two things from digging deep: 1) these commercial customers were not especially price sensitive (for these goods); and 2) the buyers were not especially sophisticated.

Problem 3 - Competing Budget Priorities: In many organizations, there is a persistent battle for the CAPEX budget. Customers often find ways to reduce low-priority CAPEX purchases, in exchange for back-end OPEX expenditures (Finance may encourage variable, over fixed, costs). In many cases, lower upfront spend will result in increased purchases and a reduced focus on consumables, add-ons, license renewals, or maintenance services. The downstream consumers in these circumstances will often express frustration with price but prove to have little ability to do much about it. Considering this, the question for suppliers should become: How do I optimize pricing to capture the most life-cycle value?

Recommended Diligence Approach - Consider Organizational Structure when Segmenting: The answer to this question can come from investigating who within the organization is consuming the product or service, and whether the consumers are the same people, and/or sit within the same organization structure as where the upfront spend decision maker(s) sit. If you find that these are different people/functions among a class of customers, determine if the circumstance warrants consideration as a stand-alone customer segment, and determine how large this segment is. In a recent assignment related to building products, a pattern emerged whereby less specialized buildings were most likely to have initial purchasing decisions made by the developer/owners, rather than the actual users of the downstream product and associated consumables. The result was a lower willingness-to-pay for the upfront hardware purchases, which materially affected market share and moderated price pressure of the downstream consumables.

[1]Jim Stinson, “Polls Show Your Neighbor Is Voting for Trump,” November 2, 2016.

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