conjoint analysis specialists

Improve your grasp of Pricing Strategy & Consumer Behavior for as little as $3,000

In a world of complex product and service offerings, sellers lose potential profits because they cannot accurately determine what customers are truly willing to pay for product features.

Companies cannot capture their market with random and haphazard pricing strategy decisions.  The winning firms will be those who develop and price their products, especially those with new features, according to market demand after scientifically collecting data from target customers.

Conjoint Analysis

But the direct survey question "how much would you pay for xyz?" is unreliable and misleading. So instead, we ask the consumer's opinion on a series of products with differing features over a range of prices. Our techniques then use regression analysis to compute mathematical values that explain consumer behavior -  how much value is placed on price, or location, or features, etc. and then correlate this data to demographic, lifestyle, or other consumer profiles.

A software-driven regression analysis of data obtained from actual customers makes this possible. As a result of conjoint, the current product offerings or price can be tweaked to match consumer behavior and expectations. Also, vulnerabilities - like weak brand or uncompetitive prices - can be exposed with conjoint analysis.

Eligibility

This model requires a relatively large number of respondents to a marketing survey.  For this reason, it is usually best suited to B2C applications, as data can more easily be collected from individual consumers.  Additionally, a time commitment is required for the participants - in order to gather data in the powerful way that conjoint analysis allows, a survey needs about 15-20 minutes to complete.

Questions answered by Conjoint Analysis

  1. Do I have the right pricing strategy?

Conjoint Analysis determines how your customers trade-off different price levels with the features of your product that they most desire - without asking them directly. That's the magic.

  1. How important are new features?

Conjoint Analysis tells you the must-have features of your product by segment, so that you can tailor your marketing efforts to a particular demographic or behavorial profile.

  1. Does my brand matter?

Conjoint Analysis reveals what factors drive consumer behavior:  brand, price, or features - and whether your brand can command a premium.

If you've been asking these questions, then Conjoint Analysis can help. 

Sample Conjoint Surveys

Entertainment Industry - Compact Disk ConjointFood and Hospitality Industry - Ice Cream ConjointPolitics - 2008 Presidential Party Primary Conjoint

Click on one of the samples above to view actual online conjoint surveys. Ajjan Associates can help you use this powerful method to understand consumer behavior in any industry for as little as $3,000. Learn more about us.

Conjoint Method

First, select what attributes of the product you would like to test, and what the possibilities are for each attribute.  To demonstrate, let's use the example of an ice cream shop, which might want to know consumer attitudes about:

  • preferred flavor (vanilla, chocolate, strawberry, or black raspberry)

  • price ($1.50, $2.00, $2.50, $3.00)

  • container (cone, cup)

  • freshness (homemade & fresh, factory-produced)

  • healthiness (reduced fat, regular)

Is there a preferred flavor, or do customers like a variety?  How much "extra" would someone be willing to pay more for a reduced-fat option?  Do kids really prefer cones? How much do consumers value a neighborhood shop using fresh local ingredients?

The scientific way to answer these questions is to test each of the 5 attributes in the context of the others.  To do that, we take each of these descriptors and create a series of "hypothetical" products, each with 5 attributes.  The software creates templates for 16 (or 18 - depending upon the number of variables) of these, and we portray the description of the proposed product visually, on a "card", as shown to the right.

"Cards" can describe the product using words only - but can also use logos, pictures, or even smells or sounds. In any case, respondents will be asked to read each of the 16 "cards", and then assign a ranking of some kind (using numbers 1-x, or using adjectives like favorable, unfavorable, ideal, etc.)

Perhaps Card #1 is a factory-produced low-fat cheap vanilla cone.  Maybe #2 is a homemade non-low-fat chocolate cup at a medium price point.  The process goes on with 16 mathematically designed cards that offer all the relevant combinations of choices.

Click for an online example of this actual conjoint analysis survey

Conjoint Results

Given the consumers' ratings of all 16 diverse combinations, the software package computes a mathematical regression to tell us how important each of the five factors is to the individual responding consumer, and to the group of responding consumers as a whole.

According to the results shown to the left (actual output from the online survey), we'd know that consumer X bases 47% of his decision on price, 23% on the flavor, 19% on the freshness, and is less concerned about the container or healthiness. We also learn get a relative ranking of the different flavors, as shown in the lower graph.

In addition, each consumer will be asked a number of informational questions to create a demographic profile, so that we can compare the results and analyze them based upon income, age, location, and other variables that may affect consumer behavior towards a particular product.

Maybe older customers who eat ice cream regularly are more concerned about healthiness.   Maybe younger consumers don't really care about the cone after all.  Perhaps those who work in a nearby office building and pass by for a snack really appreciate the homemade fresh ingredients.  All of these facts will be mathematically predicted using conjoint analysis.

The end result is a quantitative, robust analysis of what consumers really want, with each attribute evaluated in the context of the others, incorporating the trade-offs that ultimately project the greatest influence on consumer behavior.

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