# Blog.

## Conjoint Analysis.

02 September 2020 | by Oliver Harrison

Introduction Conjoint Analysis: The Basics Main Applications of Conjoint Analysis Webinar: Introduction to Conjoint   Design Experimental Design for Conjoint Analysis: Overview and Examples Writing

Optimizing your Conjoint Analysis Simulator in Displayr
31 August 2020 | by Oliver Harrison

The choice simulator is one of the main objectives of choice-based conjoint analysis. This allows you to predict the effect of different scenarios on preference

Formatting Data for Running Conjoint in Displayr
21 August 2020 | by Oliver Harrison

There are many survey platforms that do not come with their own built-in choice-based conjoint question type. This then poses the question of how to

Using Choice-Based Conjoint in Pricing Research Studies
25 February 2020 | by Julia Sullivan

This one is a bit more complicated than the first five techniques weâ€™ve talked about, but the idea of this technique is to find peopleâ€™s

Using the Value Equivalence Line (VEL) with Conjoint Simulators
31 January 2020 | by Tim Bock

The value equivalence line is a useful concept for setting pricing strategies in markets where products vary in terms of their overall levels of benefits

Computing Willingness-To-Pay (WTP) in Displayr
31 January 2020 | by Tim Bock

This post explains the basics of computing willingness-to-pay (WTP) for product features in Displayr. Step 1: Estimate a choice model with a numeric price attribute

Creating Demand Curves Using Conjoint Studies
10 December 2019 | by Tim Bock

It shows how likely people are to make purchases at different price points. There are lots of different ways of estimating demand curves. In this

Reordering Attribute Levels in Conjoint Analysis Models in Displayr
29 July 2019 | by Tim Bock

Reordering attribute levels in a conjoint analysis model can make results easier to interpret. For example, setting a standard option as the baseline in your co...

How to Analyze Dual-Response ‘None of These’ Conjoint Models in Displayr
29 July 2019 | by Tim Bock

In practical terms, the sample size is reduced in proportion to the frequency with which the “None of these” option is chosen. A way to

How to Check a Choice-Based Conjoint Model
05 March 2019 | by Tim Bock

Conjoint analysis allows us to make predictions about the future. This post walks through the 7 stages involved in checking a choice model.

Comparing HB Root-likelihood (RLH) Between Displayr and Sawtooth
01 March 2019 | by Justin Yap

In this post, I compare the ways Displayr and Sawtooth implement the Hierarchical Bayes (HB). I used both an in-sample data and holdout data for testing.

Creating Online Conjoint Analysis Choice Simulators Using Displayr
28 February 2019 | by Tim Bock

Creating the simulator Create a choice model of the conjoint using hierarchical Bayes (HB), latent class analysis or Multinomial logit in Displayr (Insert > More

Adjusting Conjoint Analysis Simulators to Better Predict Market Share
28 February 2019 | by Tim Bock

This post describes four methods for adjusting choice simulators from conjoint studies so that they better fit market share: change the choice rule, modify availability,

Testing Whether an Attribute Should be Numeric or Categorical in Conjoint Analysis
27 February 2019 | by Tim Bock

Choosing whether to use a numeric or categorical variable in a Conjoint Analysis is a difficult decision to make. With Displayr, there is a straightfoward way t...

Understanding Logit Scaling
20 February 2019 | by Tim Bock

Example: choice-based conjoint analysis utilities Consider theÂ utilities plotÂ below, which quantifies the appeal of different aspects of home delivery. If you hover over the mouse plot

Numeric Attributes in Choice-Based Conjoint Analysis in Displayr
14 February 2019 | by Tim Bock

Step 1: Set up and estimate the choice model treating all the variables as categorical Start by setting up the choice model keeping all the

Numeric versus Categorical Price Attributes in Conjoint Analysis
13 February 2019 | by Tim Bock

The difference between a numeric and categorical price attribute The chart below illustrates the the implications of treating price as being categorical versus numeric. When

Checking Convergence When Using Hierarchical Bayes for Conjoint Analysis
06 February 2019 | by Justin Yap

Please readÂ How to Use Hierarchical Bayes for Choice Modeling in Displayr prior to reading this post. There are a number of diagnostic tools that you

Performing Conjoint Analysis Calculations with HB Draws (Iterations)
11 December 2018 | by Tim Bock

Analyses of the data from conjoint analysis should take into account the uncertainty that we have about the estimates of people's utilities.

12 Techniques for Increasing the Accuracy of Forecasts from Conjoint Analysis
11 December 2018 | by Tim Bock

There are many ways you can increase the chance that the forecasts from your choice model are accurate. In this post, we take you through 12 of them.

Experimental Design for Conjoint Analysis: Overview and Examples
05 December 2018 | by Tim Bock

This post introduces the key concepts in designing experiments for choice-based conjoint analysis (also known as choice modeling or CBC).

Data Visualization for Conjoint Analysis
04 December 2018 | by Tim Bock

While choice-based conjoint analysis represents one of the more sophisticated techniques used in market research, presentation of its results commonly consists only of a simulator,

Using Substitution Maps to Understand Preferences in Conjoint Analysis
04 December 2018 | by Tim Bock

The main output from conjoint analysis is typically a choice simulator. However, substitution maps better show the underlying preferences.

Using Indifference Curves to Understand Tradeoffs in Conjoint Analysis
04 December 2018 | by Tim Bock

Indifference curves are a way of showing relative preferences for quantities of two things (e.g., preferences for price versus delivery times for fast food). This

Sample Size for Conjoint Analysis
04 December 2018 | by Tim Bock

Working out the sample size required for a choice-based conjoint study is a mixture of art and science. The required sample size depends on many factors.

Writing a Questionnaire for a Conjoint Analysis Study
14 November 2018 | by Tim Bock

This post gives you ten top tips for writing your questionnaire for your choice modeling study. It's a must read for all those conducting choice-based conjoint....

Main Applications of Conjoint Analysis
14 November 2018 | by Tim Bock

Want to know when and why you would do choice modeling? Discover all about the main applications of choice modeling and choice-based conjoint here!

Conjoint Analysis: The Basics
14 November 2018 | by Tim Bock

Choice modeling can be tricky. Luckily we've covered the basics so you can learn everything choice modeling and choice-based conjoint analysis.

Comparing Choice Models and Creating Ensembles in Displayr
08 October 2018 | by Jake Hoare

Alternative-specific choice model designs are used where alternatives are described by different qualities, rather than all attributes being the same.

How to do Choice Modeling in Displayr
06 October 2018 | by Justin Yap

You can use either hierarchical Bayes or latent class analysis to do choice modelling in Displayr, making it easy to create your designs.

How to Use Simulated Data to Check Choice Model Experimental Designs Using Displayr
18 September 2018 | by Justin Yap

Running a survey can be time-consuming and costly. Check your choice model experiment design using simulated data to save yourself the expense.

The Efficient Algorithm for Choice Model Experimental Designs
12 September 2018 | by Justin Yap

The Efficient algorithm is a special case of the more general Partial Profiles algorithm. It results in faster computation times.

The Partial Profiles Algorithm for Experimental Designs
12 September 2018 | by Justin Yap

In partial profiles designs, a specified number of attributes are held constant in each question. This reduces the cognitive effort for respondents.

How to Compute D-Error for a Choice Experiment Using Displayr
10 September 2018 | by Justin Yap

D-error is way of summarizing how good or bad a design is at extracting information in a choice model. Find out how to compute it in Displayr.

How to Compute D-Error for a Sawtooth Software CBC Experiment
05 September 2018 | by Justin Yap

D-error summarizes how good a design is at extracting information in a choice experiment. Find out how to compute it fo a Sawtooth Software CBC Experiment.

How to Create Alternative-Specific Choice Model Designs in Displayr
16 August 2018 | by Jake Hoare

Alternative-specific choice model designs are used where alternatives are described by different qualities, rather than all attributes being the same.

The Accuracy of Hierarchical Bayes When the Data Contains Segments
26 July 2018 | by Tim Bock

In this post I explore the implications of using hierarchical Bayes versus using latent class analyis for data which contains segments.

How to Use Hierarchical Bayes for Choice Modeling in Displayr
24 July 2018 | by Mathew McLean

Using Hierarchical Bayes for Choice Modeling doesn't have to be difficult. I'll show you how to do it easily in Displayr.

How Good is your Choice Model Experimental Design?
20 July 2018 | by Jake Hoare

Assessing design quality in terms of balance can involve hundreds of numbers. What if I showed you a way to use a few key metrics to summarize your design quali...