Conjoint Research for the Recession01.22.2009
It is official: We are in a recession. Markets are shrinking and wallets are tightening. So if you cannot grow by expanding the market, you have to grow by stealing share from your competitors.
These conditions are perfect for a price war, and it’s probably only a matter of time before it starts — if it hasn’t already. It could happen when a scrappy startup thinks it can deliver at a lower price and still maintain its margins. Or maybe the largest player thinks it can lose money longer than you — and force you out of the market altogether.
So, how are you going to respond? Or more important: Can you avoid the war altogether? Undoubtedly, if competitors lower their prices dramatically, you will lose market share. But how much? And if you respond with a small price cut, how many customers can you retain? Will it be enough to maintain your margins?
Fortunately, there are market research strategies that enable you:
– to predict what will happen in the market if competitors change their price; and
– to demonstrate the impact of various ways you might respond.
To put it another way, carefully crafted market research empowers you to respond with intelligence rather than fear.
Measuring Price Sensitivity
Though researchers have tried numerous approaches to measure consumers’ price sensitivity, it proves difficult to quantify. Consumers are not likely to reveal voluntarily that they will pay higher prices — as consumers, it is their job to get everything at the lowest possible price. Like poker players, they cannot tip their hand too much or they risk losing the game.
Furthermore, consumers are not always aware of their own price sensitivity — or their lack of it. Few consumers think about how much more they would be willing to pay for products or services they enjoy, nor do they consider how much of a price drop would convince them to switch to a less preferred brand. And yet, they make these types of decisions all the time: not in a theoretical setting, but in the context of actually purchasing products.
Price wars are complicated. They do not involve one single variable — such as one price drop — that could be tested in-market; they involve an action and then several reactions among multiple competitors. And they may intersect with product changes. For example, a drop in the price may be accompanied by a cut in the warranty period or the support level, or by making previously bundled services a la carte.
To consider these multiple factors, competitors, and prices in potential scenarios, what we need is a model.
Precisely the kind of predictive model needed can be constructed through survey research. Participants are recruited and screened to ensure they are a representative, statistically valid sample of your target consumers. Then they are given a series of hypothetical purchases to make.
The beauty of this approach is that the purchase decisions are constructed as elaborate trade-off exercises. The consumer simply cannot get the best of all features at the lowest price. Furthermore, the consumer is not required to consciously know or ever articulate his or her price sensitivity. Instead, we deduce the sensitivity by observing the purchase decisions. A hypothetical, simplified trade-off for a purchase might be as follows:
"If you were purchasing a new LCD television, which of the following would you choose?"
None of these
The survey respondent would have to answer a series of questions just like this, but each time the choices would change slightly. Sometimes their preferred brand would get better resolution but at a smaller size; other times their preferred brand would have all the best features — and the highest price — forcing them to either pay more or switch brands. An experimental design creates the series of trade-off exercises. Statistical methods are used to ensure the consumer sees enough options so their preferences can be quantified.
When the consumer is finished making hypothetical purchase decisions, we can analyze their choices to build a predictive model of their behavior. They still may not be able to tell you they will pay $50 more for an additional year of warranty, but based on their choices we could, in theory, deduce just that. That information then enables us to build an interactive tool that will allow us to model various scenarios that might occur in the market.
We typically start by modeling the current market scenario with the current competing brands, their key features, and prices. Then we create a new market scenario. For example, let’s assume your competitor initiates a price drop. We could then observe the change in consumer preference associated with that drop, and model what might happen if you responded by reducing your price. We’re able to estimate changes in share caused not only by changes in price, but also by product changes — such as a lower price accompanied by reduced service.
An example of an interactive tool that models consumer preference based on conjoint data. Specific features and prices of hypothetical products can be altered, showing the overall effect on share of preference for each scenario.
Ultimately, the research will reveal break points in price sensitivity, such as the points at which price sensitivity dramatically increases or decreases, as well as areas of little to no price sensitivity. Hypothetically, we may learn that a 5 percent price drop simply is not enough to send customers to an alternative in significant numbers, but a 10 percent drop will result in dramatic shifts in preferences. We may learn that a competitor’s price drop will impact another brand much more than yours. Or we may learn that dropping your price will gain more customers — but not enough to offset the loss of revenue associated with each sale.
In effect, we show you how to act based on knowledge, rather than react out of panic.
Are You Ready?
Tocquigny has substantial experience in conjoint research and can help build a robust conjoint study, with critical information about what your customers value and how much they are willing to pay. This type of study provides guidance not only for pricing decisions, but also product configurations, bundling, and message development. To get more information about how Tocquigny can help your company, call Peter Moossy at 512.532.2907 or email firstname.lastname@example.org.