# Blog

The Efficient Algorithm For Choice Model Experimental Designs
10 March 2019 | by Justin Yap

In this blog post, I describe the Efficient algorithm for generating choice model designs. This algorithm is used for generating choice model designs with partial profiles,

Data Visualization for Conjoint Analysis
10 March 2019 | 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,

Algorithms to Create your Choice Model Experimental Design
10 March 2019 | by Tim Bock

In a stated preference discrete choice experiment, respondents are asked a number of questions. Each question asks them to choose between a number of alternatives

How Good is your Choice Model Experimental Design?
27 February 2019 | by Jake Hoare

Today, you can produce a wide range of choice model experimental designs with numerous different algorithms. But with all this design diversity, how do you

12 Techniques for Increasing the Accuracy of Forecasts from Conjoint Analysis
27 February 2019 | by Tim Bock

Choice experiments, also known as choice-based conjoint (CBC), are widely used for predicting the performance of new products and changes to products’ designs and portfolios.

Experimental Design for Conjoint Analysis: Overview and Examples
27 February 2019 | by Tim Bock

This post introduces the key concepts in designing experiments for choice-based conjoint analysis (also known as choice modeling). I use a simple example to describe

What Sample Sizes do you Need for Conjoint Analysis?
27 February 2019 | by Tim Bock

Working out the sample size required for a choice-based conjoint study is a mixture of art and science. What makes it tricky is that the

Writing a Questionnaire for a Conjoint Analysis Study
27 February 2019 | by Tim Bock

The hard bit of designing a choice-based conjoint analysis (choice modeling) study is creating the experimental design. However, there are a few others parts of

Main Applications of Conjoint Analysis
27 February 2019 | by Tim Bock

Ready to dive further into conjoint analysis? In this post I describe the main applications of choice-based conjoint analysis (choice modeling; CBC). If you haven’t

Conjoint Analysis: The Basics
27 February 2019 | by Tim Bock

Choice-based conjoint analysis is a technique for quantifying how the attributes of products and services affect their performance. It is used to help decision makers

How to Identify Relevant Variables for Market Segmentation
05 February 2019 | by Tim Bock

This page lists the key frameworks and processes for identifying relevant variables to use when segmenting a market. The best way to identify relevant segmentation

How to Write “Golden Questions” for Market Segmentation
05 February 2019 | by Tim Bock

Golden questions are questions used to allocate people to segments. They are also known as self-selection questions. The main applications of golden questions are: As discovery

How to Work Out the Number of Segments For a Market Segmentation
05 February 2019 | by Tim Bock

When segmenting a market, a practical challenge is to work out the number of segments. There are eight approaches to choosing the number of segments:

How to Reuse Code Frames in Q
22 January 2019 | by Oliver Harrison

Coding open-ended and ‘other/specify’ responses can often be a tedious task for market researchers. In this post, I will instead show you how to reuse

How to Code Other/Specify Responses in Q
22 January 2019 | by Oliver Harrison

Coding open-ended responses can often be a tedious and time-consuming task for market researchers, especially when you include an ‘Other/specify’ option and then need to

How to Code an Open-Ended Question into a Single Response Question in Q
22 January 2019 | by Oliver Harrison

Coding open-ended responses can often be a tedious task for market researchers. In this post, I will show you how to easily code a single

How to Code Open-Ended Responses with Multiple Mentions in Q
22 January 2019 | by Oliver Harrison

Coding open-ended responses can often be a tedious task for market researchers. In this post, I will show you how to easily code multiple open-ended

How to Code an Open-Ended Question into a Multiple Response Question in Q
22 January 2019 | by Oliver Harrison

Coding open-ended responses can often be a tedious task for market researchers. In this post, I will show you how to easily code a single

How to Create a Box Plot in Q
21 January 2019 | by Chris Facer

Box plots are a tidy way to illustrate statistical properties of a set of numeric data. A box plot will typically show you the median

How to Relabel Rows and Columns of Tables using R in Q
21 January 2019 | by Matt Steele

Q enables you to flexibly mix data from different tables. The mixing process creates a new table as an R Output. Consider the example table

How to Do Principal Components Analysis in Q
16 January 2019 | by Chris Facer

Principal Components Analysis (PCA) is a technique for taking a large number of variables and creating a new, smaller set of variables. These aim to

How to Create a Banner in Q
07 January 2019 | by Daren Jackson

In constructing crosstabs, it can be helpful to see more than one question on an individual axis. Other instances may require labels to be “nested”,

How to Connect to a MySQL Database in Q
06 January 2019 | by Tim Ali

Having the ability to connect to a SQL database can provide greater opportunities for analyzing data sources. In this blog I will show you how