Who doesn’t want to make better decisions? We all do as individuals, and certainly in our business roles we want the most favorable outcomes as well. But as we know too well, decision making can be difficult, especially when we must choose among possibilities that seem to be multiplying before our eyes. GLG’s new ebook, How to Make Better Pricing and Product Decisions: A Fast Guide to Conjoint Analysis, takes a close look at a survey technique that produces results.

Statistics Offers a Tool

For those making decisions regarding the offering of products or services, one statistical and market research technique that can be very helpful is conjoint analysis. It is a tool that can help determine an optimal level of pricing, the most appealing product/service features, and the most attractive bundle of features, all because it helps reveal what the user of the product or service actually values.

One needn’t possess an advanced degree in statistics to understand the basics of conjoint analysis and how to apply it in many business situations. This eBook is intended as an overview of the technique and a quick guide so that business decision-makers may choose to employ it in areas where its findings would be particularly useful. Let’s start with the basics.

What Conjoint Analysis Is and Why to Use It

Simply put, conjoint analysis is a survey-based technique that asks respondents to rate, rank, or, most commonly, choose (depending on the type of conjoint analysis) which product concept they prefer. Based on the respondents’ evaluations of the concepts, we can figure out how much unique value, or utility, each feature adds to the product.

Typically, the greater value respondents ascribe to certain attributes or features, the more a provider can charge. Since charging too much can dissuade potential customers from making a purchase and charging too little can leave money on the table, research using conjoint analysis can be very useful in understanding what potential customers are truly willing to spend for a product or service.

Of course, customers and potential customers can simply be asked what they would be willing to spend — or whether they prefer one feature over another — but experience has shown that responses to direct questions are unreliable and not necessarily representative of a respondent’s true beliefs or intentions.

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About Megan Peitz

Megan Peitz is a self-proclaimed nerd with a master’s in mathematics and statistics. Megan has challenged stereotypes as the female owner of Numerious Inc. With over 10years of marketing research experience, Megan has helped some of the world’s largest companies fine-tune their products and services using math. She has a passion for teaching and has presented at many industry conferences on discrete choice techniques. Most recently, Megan’s work was published in the Journal of Choice Modeling. She also finds time to mentor females interested in STEM careers.