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10 Conjoint Dos and Don'ts: Replicate the Market and Buying Experience

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Conjoint analysis continues to be one of our most requested market research solutions — and for good reason.

Conjoint can help you get better results in all these ways:

  1. Launch better products
  2. Design better packages
  3. Set better prices
  4. Define better segments
  5. Execute better campaigns

However, conjoint isn't easy and there are many pitfalls and challenges that beset even the most experienced research and marketing professionals. We want to make sure that you don't suffer the same fate as so many others have in the past.

So, after many requests, we've assembled 10 Conjoint Do's and Don'ts that will put you on the path to success with your next conjoint study.  Here is #3.

#3 — Do Replicate the Market & Buying Experience

In conjoint research, if you don't replicate the buying experience, you will not generate the data you need to accurately simulate the market once your study is complete. That's definitely something you want to avoid.

A bad simulator yields bad decisions and results. You must carefully structure conjoint models that replicate the marketplace so that you can make the most informed moves possible in your own campaign.

To achieve this, your survey design must use accurate images of products, logos, concepts, packages and other attributes. In addition, you must use the words and phrases that are most commonly used by consumers and competitors in the category or risk seeming out of touch. If you are uncertain about the consumers' language, you should first conduct qualitative research.

In your next conjoint study, leave less to the imagination when it comes to the consumer's actual buying experience.


Click here or the image below to download all 10 conjoint do's and don'ts.

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David W. Wilson
David W. Wilson
David W. Wilson

David Wilson has over 25 years of experience helping leading companies improve their marketing results using digital marketing, direct marketing, database marketing, consumer data, predictive analytics and marketing research.