Ford Does Conjoint Analysis Online

After giving Ford a hard time in my previous post, I’m happy to report that they’ve also been doing some innovative pricing research. According to The Car Connection, the pre-launch site for the upcoming Fusion model included randomized base and option pricing, allowing Ford to guesstimate demand for various features (all wheel drive turned out to have much more demand than anticipated). Program marketing manager Dan Geist recognized the dangers inherent in conjoint analysis:

“When you’re not stroking a check, you may be designing a vehicle that’s a little more expensive than what you’d actually buy at the dealership,” cautions Geist. But he said the automaker was able to compare the Web data with other research for Fusion. There have been the usual clinics and focus groups, but the online approach has been especially helpful in making last-minute tweaks.

I think variations on this theme will become the norm as companies turn to their customers and ask what they want and how much they want to pay. There will be mechanisms to filter out lowballers, and to correct for over optimism, and people just trying to drive down the price. In addition, the process of asking people about pricing will in some cases generate priceless “buzz” in the very target audience vendors are trying to reach.


  1. Blair Gibson

    Hi Reuben:

    I deliver a value-based pricing workshop to a high-tech firm in most of its locations. The most frequest question I get is what is the best way to determine the price elasticity of a product?

    Any thoughts?


  2. Reuben Swartz

    If there were an easy way to do this everyone would do it. 😉 Price elasticity is important. But most companies are not in a position to accurately measure it, because they have too many other unknowns in their pricing process.

    You can approximate price elasticity by looking at volume and win/loss rates at different price points. This is better than nothing, but does not tell the whole story. Effective value communication can influence price elasticity greatly.

    Price elasticity also varies across customer segments. (See the Tyranny of Averages post for more on the pitfalls of this.)

    Also, you might want to look at the Value Price Waterfall article (linked from the blog or on, for some suggestions on establishing the maximum possible value for each segment.

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