Conjoint Analysis Excel Template

Identify product attribute customer preferences, customer's willingness to pay, and product market share.

by Alberto Scappini
Business Analytics Manager, Professor Data Analytics, AuthorFollow 101

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Description
'Conjoint Analysis' is a surveying technique, and it is used to identify customer (and prospective customer) preferences. Those being interviewed are shown a range of products with a range of different attributes. They are then asked to rank the products. Using this ranking, the utility of each attribute and product is then calculated at the individual level. You can use the results to simulate market share variations with competitors, or to define the best combination of price and attributes.

You should leave enough time to design the analysis, starting with selecting the most important attributes and levels.

There are 3 different methods:

Decompositional methods

1. Different product versions are presented to the respondents
2. They're asked to rank them
3. By decomposing the observations, the utilities are calculated at the attribute level

Compositional methods

1. The levels of the attributes are rated by the attributes directly

Hybrid methods

1. In the first phase, compositional methods are used to present a small number of product versions in the second phase (useful when there is a large combination of levels and attributes.)

As well as the methods outlined above, many kinds of adaptive conjoint analysis are used to increase conjoint analysis efficiency, particularly when you have a large number of attributes.

In conjoint analysis, the price utility is calculated and the price is usually included as an attribute. But, this can create some problems:

-The price does not have a utility but is used in exchange for all of the attributes' utilities of the product

-The perception of the respondents, the number of levels, and the price ranges can all bias the answers

- You cannot know whether or not the respondent would actually buy the product at the price that has been presented because the intention to purchase is not included

Willingness to pay is calculated as the exchange rate between attribute utility and price utility. However, in order to avoid the aforementioned problems, a different approach should be considered. E.g. separating the analysis into 2 phases:

1. To define utilities, perform a classic conjoint analysis for non-price attributes
2. For full product profiles, ask for the purchase intention with varying prices to define the upper and lower boundaries between which the respondent would go ahead with purchasing the product.

This Best Practice includes
Conjoint Analysis Excel Template