Multi-Dimensional Contextual Elasticity

Why the market’s response to price depends on what else is happening at the time.

The problem with a single elasticity number

We have all seen elasticity expressed as a number. Increase price by a certain amount and demand is expected to move by another amount. It is useful. But does the same number really apply every time? Think about it. The same product can behave very differently when demand is strong versus weak. Customers may respond differently when you are priced below competitors rather than above them. A price increase may work when inventory is scarce, but produce a very different result when you are sitting on excess stock. Season matters. Competition matters. Inventory matters. Customer behavior matters.

So instead of asking:

“What is the elasticity of this product or segment?”

Perhaps the more useful question is:

“How is the market likely to respond to this price change, under the conditions that exist right now?”

Context changes the answer

That is the basic thinking behind Multi-Dimensional Contextual Elasticity. The idea itself is simple. Customers do not respond to price in isolation. They respond to price in a situation. That situation could include demand, competitive position, inventory, season, channel, customer behavior, where the product is in its lifecycle and several other factors. And these factors don't necessarily act independently. Take something as simple as being priced above the competition. Is that good or bad? The answer depends. If demand is strong and inventory is scarce, being slightly above the market may not matter much. If demand is weak, inventory is building up and the season is coming to an end, exactly the same price position could matter a lot.

Same price position. Very different response.

That is why we don't see contextual elasticity as simply adding a few more variables to a traditional elasticity model. The more important shift is to understand the combination of conditions surrounding the pricing decision.

Moving beyond the average

Historical data is still where much of the learning starts. But there is a catch. If we combine observations from very different market conditions, we can end up with an average response that is mathematically correct — but not particularly useful for the decision we are making today. The opportunity is to get closer to the response that is relevant now. In simple terms:

Same action. Different context. Different response.

That is the thinking behind Multi-Dimensional Contextual Elasticity, and it is an important part of how we are thinking about pricing and promotion decision intelligence at Gestalt and Price-It-On®. __________________________________________________________________

Gestalt has filed a provisional patent application covering aspects of Multi-Dimensional Contextual Elasticity and Commercial Response Modeling.