The pandemic is forcing retailers and distributors to make split-second ecommerce decisions. The brutal transparency of competitive pricing has these companies sweating as they figure out how to pivot from traditional channels to online demand on a dime. Distributors and retailers using old-school “cost-plus” pricing will not be able to react quickly enough to new competitive online threats — these pricing strategies are a big, fat fail.
In a nutshell, cost-plus pricing strategies are inflexible, uninformed and reactive.
Ignoring Price Sensitivity is Reckless
Cost-plus pricing ignores market competition and price sensitivity. The idea is reckless: apply peanut-butter pricing across the assortment without digging into what drives customers to buy your products. What about all the psychological factors that influence price sensitivity of customers, like reference price, ease of comparison (how obvious or easy is it to compare your product to alternatives), the cost of switching and the perception of fairness? Nope. Just pure “set it and forget it.”
Up until now, that’s just how it was done. It worked. It made sense. But now, to put it harshly, businesses using cost-plus pricing today will get their ankles broken. Does your business fall into this category? If you’re not sure, ask yourself these questions:
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Does Your Pricing Model…
- Look at market competition every day and make adjustments automatically?
- Take into account price sensitivity, or customer willingness to pay?
- Show how substitutable your product is when sold at any location or on specific channels?
- Analyze competitor prices and put context behind pricing decisions vs. blind price matching?
If the answer for these is “no,” then you do not have a sustainable pricing strategy.
AI and Machine Learning: The Buzzer Beater
Now with the availability of breakthrough AI and machine learning technologies, businesses are not only eliminating mispriced products, they are actually optimizing profits with great foresight in just a few keystrokes.
Intelligent pricing logic improves your competitive position by uncovering opportunities you didn’t even know were there.
How much are people willing to pay for your product across various locations, regions, channels, and even by customer? Or deep in the long-tail assortments that never go under the microscope? If you are blindly matching competitor prices, are you chasing someone else’s poor pricing decisions, or getting into price wars without even knowing it?
What about Amazon? Should you be paying attention to Amazon or an industry-specialist competitor for a certain product sold on a particular web channel? Maybe you shouldn’t worry about them at all, in cases where the product is not price sensitive — or has no competitive substitute available.
Tools for Measuring Price Sensitivity
All of these considerations cause a slow and unprofitable competitive price response. Unfortunately, most companies either have no idea how much competitive prices are hurting them — or they do know, but they lack the time/resources to effectively calculate and react.
A machine learning-based price optimization tool lets you quickly measure price sensitivity and run pricing analysis by product, channel and competitor. You can understand the impact of a price change before you make the change, and every decision becomes a confident and profitable one.
Cliff Isaacson is the EVP of Product Strategy for Blue Ridge, which uniquely combines demand forecasting with pricing strategy so that businesses can proactively understand the unpredictable and allocate the right inventory — right-priced across the entire mix — to accelerate top- and bottom-line results.
