Guides and how-tos

Comparison of types of conjoint analysis

Posted on 2 March 2017

Conjoint.ly offers two types of conjoint analysis: generic conjoint and brand-specific.

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How to get participants for your study

Posted on 12 February 2017

This guide shows you the range of options we offer to get responses for your experiments.

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How to interpret marginal willingness to pay (MWTP)

Posted on 13 January 2017

Generally, in economics, marginal willingness to pay (MWTP) forms the basis of price, which is defined as the maximum price someone would pay for an extra good or service. It is also known as marginal rate of substitution of something for money.

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How to interpret partworth utilities

Posted on 30 December 2016, updated on 19 March 2017

Partworth utilities (also know as attribute importance scores and level values) are numerical scores that measure how much each attribute and level influenced the customer’s decision to make that choice. Because attribute and level partworths are interrelated, in this post we will look at them using the same example of tissue paper. Suppose the company wants to find out customers’ preferences for tissue paper to re-assess its product range, as a pathway to growth. The charts below show some common attributes of the company’s (and competitors’) tissue paper:

  • Texture: weave-like or simple
  • Ply: 3 ply or 2 ply
  • Scent and colour: “recycled unscented”, “white unscented”, or “white scented”
  • Price per 100 sheets: 30¢, 55¢, or 70¢
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How to specify attributes and levels in conjoint analysis

Posted on 29 December 2016

Attributes are ‘dimensions’ of your product (such as price, colour, shape, size, brand, location). Include the attributes that you believe are most important to your customers when they make buying decisions, as well as any attribute whose importance you would like to check. For example, if you know that customers are driven by price and size, and want to investigate whether colour is important, include all three attributes (price, size, and colour). Try not to include more than five attributes because it might confuse your respondents.

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Top ten tips for great conjoint analysis

Posted on 28 December 2016

Conjoint analysis is a very powerful tool for market research. Here are Conjoint.ly’s best practice tips for setting up your analysis to yield useful results.

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CBC Excel simulator with Conjoint.ly

Posted on 17 November 2016

For each conjoint study on Conjoint.ly, one of the outputs we provide is an Excel profitability model (also known as CBC simulator). By letting you simulate the market environment, it lets you estimate the profitability of your new product development (NPD). These calculations are based on a simple model:

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