How to Analyze the Conjoint Analysis Feature on the Pollfish Platform

We covered the critical question of what is conjoint analysis, explaining its utility, especially in the product development and customer development space. A previous article has also discussed how to build a Conjoint Analysis survey on the Pollfsh online survey platform.  

With those insights in mind, it’s crucial to learn how to analyze the Conjoint Analysis feature, which is choice-based on the Polfish platform. You can do so by familiarizing yourself with its different data visualizations, which adequately provide data for decision making. 

This article expounds on how to analyze a conjoint analysis feature on the Pollfish market research platform. 

Generating Insights from the Conjoint Analysis in Your Dashboard

You can easily generate the insights you’ll need to understand your conjoint analysis in the Pollfish dashboard. To access this feature, simply visit your survey results page and remain on the Conjoint Analysis block. No visualizations will appear until you have collected four responses.

In the Conjoint Analysis block, you will see three graphs: the Attribute importance chart, the Level Utilities chart and the Distribution of Level Preferences chart and a Ranked list of product alternatives as preferred by customers. 

Check out this preview of the results page:
https://www.loom.com/share/745f0240ef1c4b879c6e9bc5db6db3a7  

The Attribute Relative Importance Graph 

This graph displays the influence an attribute has when the respondent selects their preferred alternative. The higher the percentage, the more influential it is in the decision-making process of the potential consumers.

Assuming a survey with 3 attributes tested and None of the above options enabled, the Brand is the most influential attribute relative to the Colour and Price which is the least influential attribute (as displayed below).

This chart shows how strongly the variations of attributes affect customers’ choice, but only for the levels that you chose in the design.

Level Utilities 

This allows you to dive deeper to understand what specific levels within an attribute drive customers’ choice. Each graph displays the measurement of preference for the levels of an attribute. Level utilities are calculated based on the average preference scores for each level. The higher the percentage, the higher the influence of the level at the customer’s decision to select a product alternative.

Distribution of Level Preferences Graph 

This visualization displays the measurement of the probability that a level would be selected over another, if all other attributes were held constant. The higher the percentage a level has, the higher it was preferred within the levels of the attribute by respondents.

Willingness to pay

Willingness to pay is the maximum price a customer is willing to pay for a product or service (ie. how much users are ready to pay for an upgrade from level A to level B, in addition to the price they are already paying now).

Each attribute has its own chart, where values represent monetary values. By using the chart and selecting a different baseline level, you can compare how much respondents are willing to pay for an upgrade or a downgrade to another level.

Willingness to pay is a chart available only for Conjoint surveys containing an attribute of Price type.

In the example below, the baseline level for “Perfume” attribute is set to “Floral”. From the graph, we can understand that users are willing to pay $2.05 more for “Lavender”, whereas for the “Green Citrus” they are willing to pay $0.77 less than for “Floral”.

You can change the baseline level for the specific attribute to “Ocean” to compare how this performs against the other levels, by clicking on the relevant bar. This will convert “Ocean” to the baseline level, where we can see that users are willing to pay more only for the “Free of perfume”, whereas for all other levels of “Perfume” they are willing to pay less than they would for “Floral”.

Ranked List of Product Alternatives 

This table displays how the product alternatives are ranked, based on the level utilities. The first ones are the most preferred among the respondents. 

You can apply the results of the Conjoint Analysis feature through filters. Just use the filters with the selected demographic criteria and to the rest of the demographics gathered. 

The information in the graphs gets recalculated to provide insights only for the filtered audience, as long as there are at least four remaining responses. Post-stratification is not available on the Conjoint Analysis feature.