How Should a Firm Set the Price of Products and Services?
If your organization is simply basing its pricing strategy on competitor prices, it could be missing out on some big opportunities to boost profitability through more optimized data-driven pricing. While competitor pricing should certainly be an input to what you decide to charge, there are many reasons why your competitor’s pricing is not as relevant for your organization. Your brand, your level of quality, and your level of convenience may command a premium. The demographics of your specific locations may necessitate price adjustments. Even if you’ve tried to bake in some adjustments for these things manually, how can you be sure that you’ve adjusted your prices by the right, optimal amount? As with any business decision (even beyond pricing), the absolute best way to know that your pricing is optimized for profitability is to conduct regular A/B (or even A/B/C/D/etc…) tests on different price points to assess price elasticity (the impact of price on unit sales volume).
Looking at the relationship between past price increases and sales volume is another popular method to assess price elasticity, but it doesn’t give nearly as accurate of a read as A/B testing since there are many other factors outside of pricing (some controllable and some not) that can drive sales over and there can also be a lot of volatility in sales performance over time. The random assignment to a test (A) and control (B) group ensures that the only thing different across the groups (in aggregate) is the treatment (i.e. a difference in price), which means any difference in sales volume across the 2 groups can be attributed directly to price. Thus, A/B testing automatically controls for economic changes, other programs, and anything else changing over time. There are also generally many more data points involved in an A/B test than past periods/geographies to consider in a historical analysis, making your A/B test less volatile. Finally, A/B testing provides a superior read on price elasticity because it’s specific to the current environment and the current product (which could be brand new in some cases!).
If your pricing team isn’t A/B testing today, it’s possible that, if it is feasible for your industry/business model, they lack the analytics knowledge to build and implement robust A/B tests. Whether you’d like your pricing and analytics team to learn how to conduct regular, robust A/B pricing tests themselves or would prefer for a consultant to set up and conduct the analysis for you, Value Driven Analytics can help! See the video above to learn more about A/B testing.
