Conjoint Analysis

Conduct Pricing

Research Effectively

What is Conjoint Analysis?

Conjoint analysis is a statistical technique used in market research todetermine how people value different features of a product or service.Also referred to as a trade-off analysis, conjoint is used determine whatcombinations of attributes is most influential on a respondents’ choice ordecision-making.

By analyzing how respondents make preferences based on a controlledset of potential products and services, the implicit valuations (utilities orparts-worth) of each attribute can be determined. The utilities or parts-worth values can then be used to simulate the estimated market share aswell as potential revenue and profits of new products or services.

Survey Analytics specializes in Choice-Based Conjoint (CBC). It is the mostpopular conjoint-related technique in use today. This is primarily becauseit is modeled after consumer behavior in real-life. Most purchases thatconsumers make are basically trade-off based.

If someone is planning a trip to Hawaii, will they book a garden view roomfor $125/night, a partial ocean view room for $175/night, or a full oceanview room with a balcony for $225/night? This will depend on the type ofperson, as well as how much they are willing and able to spend.

Why do I need Conjoint Analysis?

By using conjoint analysis in the initial product innovation phase, the daysof spending loads of money to create products and putting it directly in themarket are over. The use of conjoint analysis will offer data to helpdetermine the direction new products and services could potentially takebefore heavily investing company resources.

Conjoint analysis isn’t just for the idea phase. You can use it in all phases ofbringing a new product or service to market, or you can use it with existingproduct or services to determine estimated market share among yourcompetitors while discovering what things about certain productsinfluences a respondents’ choice or decision-making.

When specifically using choice-based conjoint, it quantifies the act ofwatching a person at the store trying to decide which kind of laundrydetergent to purchase or which toothpaste to buy. And based on theanswers given, one can then make a recommendation for new products orservices and at what price point to offer it to achieve gains in market share.

How do I conduct Choice-Based Conjoint?

The first thing you must do before creating a conjoint question in yoursurvey is to clearly define the features and attributes for your study. Ifyou cannot clearly define your features and attributes, or if your listappears to be extremely long, then you will need to do pre-conjointresearch to determine your list of features and attributes.

Features are different components that make up a product or service.Attributes, also known as levels, are varying elements within eachcomponent.

If using a Hawaiian vacation package as an example, your rooms, flights,activities, and car rental are features of a conjoint analysis question. Theattributes of a room are full ocean view, partial ocean view, and garden view,while activities attributes are snorkeling, swimming with turtles, or a boozecruise.

As a general rule of thumb, use no more than 5-7 features and 5-7attributes per feature. There may be exceptions to this rule, dependingon respondent size and how you want to use the data.

How do I conduct Choice-Based Conjoint?

Once that is done, you can add your conjoint instructions, features andlevels into the question. Next, you will want to set up your task counts andconcepts per task. After this, you may want to update prohibited pairs,add an n/a option, include fixed tasks, and select the best design option foryour study. Survey Analytics supports Random, D-Optimal (beneficial forsmall respondent groups), and Import design options for choice basedconjoint analysis.

How to analyze Choice-Based Conjoint

To analyze the conjoint data collected in Survey Analytics, go to theReports Tab, select "Choice Modeling" and then "Conjoint Analysis".There is an option to analyze the entire report or based on applieddata filters or segmentation.

What is Part-Worths?

Part-worths means level utilities for conjoint attributes. When multipleattributes come together to describe the total worth of the productconcept, the utility values for the separate parts of the product (assignedto the multiple attributes) are part-worths.

The final parts-worth are re-scaled so that the part-worths for anyattribute have a mean of zero, simply by subtracting the mean of the part-worths for all levels of each attribute. The higher the part-worth valueswithin the feature set, the more preferred it was among the responsegroup.

Example: Vacationers booking a trip to Hawaii prefer to book ocean viewrooms, then garden view rooms, then rooms with no view.

What is Relative Importance?

For each Attribute, the difference between the highest and the lowest Part-Worth is calculated. This value, divided by the total across all the attributes,is the relative importance. This percentage value will identify the featurethat most influences a respondent’s preference for a particular product orservice.

Example: When choosing a vacation package to Hawaii, room type was thefeature that most influenced a respondent’s preference among differentpackages presented.

In addition to the relative importance and parts-worth chart, SurveyAnalytics offers a market simulator tool, which will allow you to simulateother product options and view estimated market share, as well as variousdownload options for further analysis.

Relative Importance and Parts-Worth Table:

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