Learn How to Do a Conjoint Analysis Project In 1 hour

•Started in 2002 in Seattle, WA•#172 on Inc. 500 Fastest Growing Private Companies•#12 on Puget Sound Journal's Top 100 in Washington •Over 6K+ clients and growing!•QuestionPro, SurveyAnalytics, IdeaScale, MicroPoll      Esther LaVielle – Chief Education Director

  

Who is Survey Analytics?

Andrew Jeavons has been active in the survey and market research business for over 25 years around the world. He has worked in Europe, the USA and APAC. He currently lives in Cincinnati, Ohio, USA.

After studying neuropsychology at Birkbeck College in London UK, he then worked in the medical statistics department of the Institute of Neurology in London UK.

Andrew worked as a software developer for Quantime. He was one of the founders of the software company E-Tabs, and a founder of a software consulting company now called Cobalt Sky. His areas of interest include statistics, text analytics and visualization, neuropsychology, writing and speaking.

In the last ten years he has worked for survey software companies in a marketing, sales and strategic development capacity. He has also written numerous articles for ESOMAR publications and a range of international conferences.

He is currently Western area convenor for the New MR 2010 conference (www.newmr.org)

Who is Andrew Jeavons?

 AGENDA: 1.What is Conjoint, Why you need to use it, Core Concepts

2. How to Put together a Conjoint Analysis QuestionWizard based interface to create Conjoint Tasks based on simply entering 

 Features (Attributes) and Levels for each of the features.

3.  Adding Conjoint Design ParametersTweak your design but choosing the number of tasks, number of profiles per task as well as "Not-

Applicable" option. 

4. Preview Survey

5. Review Utility Calculation & Relative Importance  

6. Market Segmentation ToolFilter the data based on criteria and then run Relative Importance calculations

 7. Best Practice & Tips / Q&A

 

 Why Choose Survey Analytics 

  over 

 Sawtooth Software?

  Flexible monthly pricing available  Most User-friendly Conjoint Tool   Specialized in Discrete Choice Conjoint Analysis  Offer Robust Survey/Reporting Capabilities  Dedicated Account Manager during length of license

What is Conjoint Analysis ?

Conjoint analysis is a method developed over the past 50 years by market researchers and statisticians to predict the kinds of decisions consumers will make about products by using questions in a survey.

The central idea is that for any purchase decision consumers evaluate or “trade off” the different characteristics of a product and decide what is more important to them. For instance , it may be that the container size is the most important factor, or it may be environmental friendliness of the product and the price. Obviously for different products there are a whole range of possible characteristics or “attributes” that consumers may take into account.

Conjoint analysis is away of presenting a set of possible products to consumers via a survey and ask them to make a choice about which one they would pick. A set of attribute for a product (perhaps color, size, price) are chosen and then a set of “levels” of the attributes are selects. For instance we could have 3 colors of a product, red, green and blue, then maybe 3 sizes, 4, 8 and 12 oz, then 3 prices, $10, $20 and $30 . This would give 3 x 3 x 3 possible product combinations.

A set of alternative “products” based on the attributes you have defined are presented to respondents who make choices as to which product they would purchase in real life. It is important to note that there are a lot of variations of conjoint techniques. SA uses a conjoint technique which we feel best simulates the purchase process of consumers.

Why use Conjoint Analysis ?

Conjoint analysis is used to help evaluation new products, or variations of products, against an existing range of products or a marketplace.

It is very expensive to develop a new product and then put it out into the marketplace with no guarantee of success.

Conjoint analysis allows market researchers to simulate the decisions consumers would make in the market place.

This means a company can get an idea about how a new product with be received in the marketplace much more easily than if they had to really develop and market the product. It is also used to see what effect changes in price of existing products may have on the sales of the product.

With Survey Analytics conjoint analysis system you can get feedback on new products or variations of an existing product very quickly and at a low cost.

1) Attributes/Feature: Define the attributes of the products for your market. These are the properties of your product.

Seattle Tourism Study: vs. Hours, Time of Day, Tour Type

2) Levels: The different properties of the attributes. Define at least two levels for each of the attributes. 

Seattle Tourism Study: Hours - 3 levels

Time of day - 4 levelsTour Type: 5 levels

3) Utility or Part Worth functions: These are what are produced by the conjoint analysis. These can then be used to determine how important an attribute is to the purchase or choice process and in “market simulations”.

4) Relative importance: how important an attribute is in the purchasing/choice decision ?

 

Core Concepts

 (1)Survey Analytics uses Multinomial Logistic Regression for part worth calculations. Used in calculating utility values for each level  (2) Survey Analytics use an Orthogonal Profile Generation Any set of attributes will have a minimal set of profiles that can be generated to form a balanced design.  Have greater confidence in the results you receive!

Analysis

Set up a Discrete Choice Conjoint Analysis Study:Add Instructions and Features

                                                             Set up a Discrete Choice                                                              Conjoint Analysis Study:

Set Attributes /features for each Level

                                                             Set up a Discrete Choice                                                              Conjoint Analysis Study:

Prohibited Pairs- You can create as many "Pairs" as you want and the Engine will never display two levels that have been marked as "Prohibited" in the same concept (as\ a product) for the user to choose 

                                                             Set up a Discrete Choice                                                              Conjoint Analysis Study:

Set Concept Simulator- This can be used to determine what choices will be presented to the respondents when your survey is actually deployed.

Click on the Simulate ConceptChoices button.

                                                             Set up a Discrete Choice                                                              Conjoint Analysis Study:

Prohibited Pairs- Determine Levels not to be paired together

Example: Weird Seattle tour can’t be 4-6 hours 

Note: too many prohibitions arenot recommended - may skew results.

                                                             Set up a Discrete Choice                                                              Conjoint Analysis Study:

Preview Using the Preview Option

 Conjoint Analysis:Reviewing the Results

 

 Results from Conjoint Study

 

Relative Importance of attributesas a Pie chart.

 Results from Conjoint Study

 

The tour type is clearlythe most important attribute.

Chocolate isever popular !

Weird is good !

 Results from Conjoint Study

 

The tour type is best liked.Weird works.

 Results from Conjoint Study

 

Relative Importance of attributesas a Pie chart.

 Results from Conjoint Study

 

Media tools just winCombination best

 Results from Conjoint Study

 

Most liked profile.

 

Market Segmentation SimulatorUsing existing Data from Conjoint Analysis

Market Segmentation SimulatorGives you the ability to "predict" the market share of new products and concepts that may not exist today.

Ability to measure the "Gain" or "Loss" in market share based on changes to existing products in the given market.

Important steps in Conjoint Simulation:

1- Identifying and describing the different products or concepts that you want to investigate. We call these "Profiles".

Example one of the profiles could be: Tour Type: Weird, Hours: 1-2 , Time of Day: Evening

2- Find out all the existing products that are available in that market segment and simulate the market share of the products to establish a baseline.

3-Try out new services and ideas and see how the market share shifts based on new products and configurations.

 

Let's look how to set up a Simulator!

Setting Up Simulator:

1) Click on Online tools >>Name Simulator Profile>>change profiles

   2)Click                                             to see results . . . . .

 Results: Simulator Output Defined The market simulator uses utility values to project the probability of choice and hence the market share

 Now that we know how to use this . .

  What can we askand find out with the Market Segmentation Simulator?

Market Segmentation Simulator

In our second example we have a 20%/80% split of market share when we just vary the DVD or DVD with Podcast feature. What happens if we change the guide to family guide from separate adult and children’s guides ?

Answer: The market share for the Family guide with DVD option goes down to 10% from 20%

Market Segmentation Simulator

In our first example what happens if have a tour of 1-2 hours as opposed to 4-6 hours in the afternoon for “Weird Seattle” ?

Answer: We find that the 1-2 hour tour would attract about 75% of the market share.

Market Segmentation Simulator

Using our second example, what happens if we take the most preferred profile and change the family exercise calendar from 60 days to 30 days ? What effect does the 90 day calendar have ?

Answer:  We get a 60% market share for the 60 day calendar vs 40% for the 30 day calendar. A 90 day calendar vs a 60 day calendar has 30% market share for the 90 day calendar and 70% for the 60 day calendar.

60 days 60%30 days 40%

60 days 70%90 days 30%

Best Practices

        

Tips for Successful Conjoint Analysis Studies

You must use qualitative research first!What are the top attributes? What range? What language?  

   A focus group or surveys with open-ended questions will help define your top attributes needed for your study  

   

Best Practices & Tips

You need some numbers to get good statistics 

   

Best Practices & Tips

Sample size is a question that comes up very frequently. Richard Johnson , one of the inventors of conjoint analysis, has presented the following rule of thumb for sample size in choice based conjoint:

(nta/C) > 500

Where n = the number of respondents, t= the number of tasks, a=the number of alternatives per task , C= the largest number of level for any one attribute.

So if you have 50 respondents, 3 tasks per respondent, 2 alternatives per task and the maximum number of levels on an attribute is 3 you get:

(50 x 3 x 2 x 3) = 900

The general opinion now seems to be that 500 may be too small a number, 1000 is a better value.

Generally speaking sample sizes tend to be around 200 – 1200 respondents, admittedly a wide range. It does seem that the value of 300 comes up most often for a single group of subjects.

Keep the options clear and simple as possible

No more than 10-12 trade-off exercises (5-7 standard)No more than 5-6 attributesKeep the ranges simple You can ask more intimate questions of current customers than potential customers, but don’t let that stop you from trying!

Follow general good online survey techniques Test your surveyMake it clear responses keep strictly confidentialKeep survey results to 15-20 minutesProvide incentives 

        

Best Practices & Tips

Pricing for SurveyAnalytics Conjoint Analysis

SurveyAnalytics offers pricing on a monthly or yearly basisUnlimited Conjoint Projects + Dedicated Account Manager + additional Survey & Analytics Tools

Cost per Month: $500/Mo per user  limited time discount

Yearly License : $6,000/yr per user

Billed via credit card only

Conclusion and Question & Answer Session

Esther LaVielleSurveyAnalytics http://www.surveyanalytics.comesther.rmah@surveyanalytics.com

Andrew Jeavonsapj@andrewjeavons.com