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This episode is about market research – what’s in your toolbox for conducting consumer and market research? Does it include Conjoint Analysis? Well, if not, it will after you listen to this episode. To explore the topic and walk through an example of using Conjoint Analysis, I tracked down a previous guest from way back in episode 008. In that episode we discussed quantitative and qualitative research tools but didn’t go into details about applying Conjoint.

My guest is Brian Ottum, a market research specialist with 30 years experience in new product development. He started as a chemical engineer and joined Procter & Gamble, contributing to Charmin, Pampers, and other products you know. He went on to earn a PhD in Market Research. Today, he helps companies with product development. He has also developed a new online course called “Tools for Early Innovation.” It’s a little over an hour of videos, case studies and downloadable materials. The usual price is $30, but he is making it available to listeners of this podcast for just $10 for a limited time – until the end of January, 2017. See the link section below to get the discount.

In this interview, you’ll learn about:

1. the types of information Conjoint Analysis can provide, such as pricing specifics,
2. when to use Conjoint, and
3. the specific steps for using Conjoint.

 

Practices and Ideas for Product Managers and Innovators

Summary of questions discussed:

• What do we use Conjoint Analysis for? Conjoint Analysis is a powerful market research tool. It is a highly quantitative, sophisticated tool, and we use it to predict what are people going to do in the future. We actually present scenarios to them and see what they do. It relies on the old human adage, “You don’t know how important something is until it’s gone.” So what Conjoint does, is it offers people things and then takes them away. Then you find out which things were missed the most.

• When in the NPD process is Conjoint Analysis helpful? It usually applies in the middle to the late part of the design process, after features have been identified but before they have been selected. An example is where the developers say, “Hey, we could put 10 different features on this new product but the marketing people and the finance people said we can only afford three.” Well, which three are you going to select? That’s what Conjoint does so well. It helps you pick. It helps you use customers to pick which of those three are going to make you the most money and sell the most new products.

• What are the steps performed to conduct a Conjoint Analysis? The steps are…
  1. Identify all potential product features
  2. Select a subset of features (around 7) to evaluate
  3. Create scenarios incorporating combinations of the selected features
  4. Create a questionnaire/survey with scenarios
  5. Collect customer preferences for the scenarios
  6. Perform the statistical analysis
  7. Summarize your findings

• Can you take us through a practical example? It is much easier to explain the steps using an example. I like bicycles so I often use a bike example. Let’s assume that we are Trek or Specialized and we’re designing the bike for the next season.  The engineers have come up with three features they could add to the new bike design. They need to pick the best one or two and figure out how much people are willing to pay. The features are: (1) an improved full-suspension frame, (2) a folding frame, and (3) a lightweight high-performing frame. We want to exam four price points also – $300, $600, $900, and $1200. An Experimental Design tool, present in some statistical toolkits, can help build the scenarios. Below are 16 scenarios. Brian provided this to me and I added the BuyRating for each based on my personal opinion of how appealing the scenario was.  The scale is: 1=Definitely Not Buy, 2=Probably Not Buy, 3=Might Buy, 4=Probably Buy, 5=Definitely Buy

 

 

Brian applied statistical analysis using regression analysis, which can be run in Excel or dedicated statistic systems.

 

Brian’s analysis of the data allowed him to conclude that… “Chad is willing to spend $333 extra to get the lightweight frame (and cut 10lbs).  Willing to pay $250 to get suspension. BUT, we’d need to pay him $83 to take a fold up bike.”

 

He also examined my price sensitivity based on my preferences for each scenario, finding… “Chad is VERY willing to buy any $300 bike.  But really has trouble considering bikes at $600 or above.  If it is $600, it had better have the Lightweight frame and Suspension!  We can even predict his score for such a bike.  It would be “4”, Probably Buy.”

 

Useful links:

• Brian’s LinkedIn profile
• Brian’s “Tools for Early Innovation” course on Udemy

Special Offer… just for Everyday Innovators, get Brian’s eCourse for only $10 when you use this Coupon Code: TOOLS10. Just go to the course on Udemy and click on Redeem a Coupon and enter TOOLS10 to get the eCourse for $10. This is a limited-time offer, so get it soon.

 

Innovation Quote

“Your customers can tell you the things that are broken and how they want to be made happy. Listen to them. Make them happy. But don’t rely on them to create the future road map for your product or service. That’s your job.” –Mark Cuban

 

Raw Transcript

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Thanks!

Thank you for being an Everyday Innovator and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.