Conjoint Analysis for Predicting Consumers Choice Behavior

Conjoint Analysis for Predicting Consumers Choice Behavior

The conjoint analysis technique helps businesses identify which attribute/s are associated with their products or services their customer’s value the most. These days, your niche products are available in multiple features, but it is hard to find out the features your target consumers find most significant. So, when you are launching a new product line conduct conjoint analysis to understand better what appeals to your customers.

For example, a laptop manufacturer desired to find out, how much customers value their product’s sound and picture quality or do customers value the price more than its picture quality. Using conjoint analysis will help them to place the value of every feature to find out what the majority of their customers prefer.

Below are ten essential conjoint analysis examples to follow or apply in your organization.

  1. Design new products.
  2. Product optimization to remove the less crucial feature, thus reducing manufacturing cost without impacting sales and revenue.
  3. Develop service suites and pricing packages targeted towards specific customer groups.
  4. Create line extension.
  5. Develop a market simulator that exhibits preference levels among the buyers.
  6. Replace the traditional concept test with effective conjoint analysis.
  7. Estimate market size.
  8. Project profitability.
  9. Perform price sensitivity analysis.
  10. Identify competitor’s weaknesses.

Conjoint analysis strength is its capacity to develop a market simulation paradigm, which predicts customer behavior in case of product modifications. Businesses can even predict customer’s inclination on other items which they plan to introduce in the future.

How to conduct conjoint analysis?

There are several things to consider while performing conjoint analysis.

  • First, determine the features you need to examine and find out ideal respondents for the survey. Even define how to perform the survey – online, by email, or by telephone.
  • A ranking or value is placed on every possible attribute.
  • The chosen respondents are asked about which feature combination they prefer in the survey. Several combinations including different possibilities are offered in the questionnaire. Respondents are requested to rank every combination they think is the best.
  • The completed survey is then collected and analyzed to find out the most optimal feature combination suitable to their needs.

For properly evaluating the conjoint analysis data, an array of software and services are employed. Conjoint analysis software is designed to write the questionnaire, arrange feature combinations as well as perform statistical analysis on collected data before presenting the result in a chart or graph form for better understanding.

A detailed example of conjoint analysis 

When consumers decide to choose a restaurant, the features they consider are distance, atmosphere, menu, and cost. Consumers subconsciously weigh these elements before choosing one that suits their needs. Tassty restaurant is close to their residence and the cost is cheap and has a sub-par atmosphere. While Ridge River restaurant is far away, more expensive, and has an outstanding atmosphere.

If the customer chose Ridge River then the atmosphere element carried more weight than the other two. Knowing this information helps to determine how to design a new restaurant layout, which location to choose, and prices to charge.