GC
Range optimisation
Features and claims

Generic Conjoint

Feature and claim selection and measuring willingness to pay for features for a single product.

Example Conjoint Report on Ice-cream

Example conjoint analysis report for preferences in ice-cream cones.
GC
Range optimisation
Features and claims

Generic Conjoint

Feature and claim selection and measuring willingness to pay for features for a single product.

This is a simple conjoint analysis report for a Generic Conjoint test on ice-cream. You can also take this survey yourself. We tested three features:

  • Flavour (Fudge, Vanilla, Strawberry, and Mango)
  • Size (from 120g to 200g)
  • Price (from $1.95 to $3.50)

We collected over 1,500 good quality responses in this test (even though this report would be robust enough with a hundred complete answers). It turns out that variation of price was a more important driver of people’s decision-making than differences in both flavour and size of the cone combined:

Relative importance by attribute using generic conjoint

Unsurprisingly, people preferred larger and cheaper cones. Fudge and vanilla were the two top flavours:

Relative value by conjoint level (level partworth utilities)

But when we look at confidence intervals, we notice that we are much less certain about average preferences for flavours than for size or price:

Relative value by conjoint level (level partworth utilities) with confidence intervals

It is probably because if we simulate preference shares for four concepts with varied flavours but fixed price and size, we observe that the distribution of people who pick different options is not extremely skewed towards one flavour:

Conjoint preference share simulation with different flavours

But when we do simulation analysis with different price points, we clearly see that more people prefer to pay a lower price. Even though some still stick with a higher price, probably due to price-quality inference.

Conjoint preference share simulation with different price points

Another useful output of the study is marginal willingness to pay, which shows the equivalent amount of money for upgrade from the less preferred to the more preferred features:

Marginal willingness to pay from conjoint analysis

If you want to pick the topmost preferred combination of product features, you can take a look at the following ranking as well:

Ranked list of product concepts from conjoint analysis

It looks like a large dollop of modestly-priced Frosty Vanilla is the winner today.


Published on 2 October 2019.

Read these articles next:

What is Conjoint Analysis?

What is Conjoint Analysis?

Guides 19 April 2017

Conjoint analysis is one of the most widely-used & powerful quantitative methods in market research. Discover how it works & where to use it by clicking here. View article

Classification of conjoint analysis

Classification of conjoint analysis

Guides 14 April 2017

We are often asked what types of conjoint analysis exist and which ones we offer on Conjoint.ly. Here is an opinionated classification of conjoint analysis that helps you understand what some experts are talking about. View article

Avoid common mistakes with practical tips for setting up conjoint studies

Avoid common mistakes with practical tips for setting up conjoint studies

Guides 29 December 2016

Conjoint.ly team shares experience of setting up thousands of conjoint experiments for pricing, feature selection, and range optimisation. View article