Tutorial: Choice Based Conjoint Analysis

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Transcription:

Tutorial: Choice Based Conjoint Analysis March 2017 Copyright: Number Analytics LLC

Introduction Conjoint analysis is a statistical analysis in marketing research to know how respondents value different attributes (characteristics or features) of products or services. The goal is to determine what combination of attributes is the most preferred to respondent choice decisions.

Introduction Design conjoint survey Distribute survey Analyze conjoint data Number Analytics generates a web link to the survey webpage so that respondents are asked to choose one of several options available. Once collected, you can run the analysis and get the individual partial worth at individual level. This tutorial shows how to design, distribute and analyze the choice based conjoint analysis

Conjoint Survey Outline Starting description > Demographics > Conjoint Questions > Analysis Analysis

Start a Choice Based Conjoint Survey Choice Based Conjoint generates online survey line and collect respondent choice data First you need to set attributes and levels for the product

Tile of the conjoint survey Starting description Ending description

Define the customer demographics you want to associate with their preference

Conjoint survey design 1. Set conjoint attributes for the product 2. Set the attribute levels

Conjoint survey questionnaire Attributes Levels

Limiting condition *Available only for advanced and premium plans Set conjoint constraints where unrealistic or infeasible attribute combinations should not be shown For example, Starbucks does not sell a coffee below $2, then we need to eliminate the option for $1.5

Design setting *Available only for advanced and premium plans The max number of respondents Set the number of co njoint choice alternati ves in the choice tabl e The number of CBC q uestions set how man y times the choice tabl es are shown per resp ondent The questionnaire display options Standard table without none option Promotion type display (without attribute n ames) Standard table with none option

# of choice alternatives # of CBC questions

Publish your conjoint survey Post the survey link to social media, website, facebook, or send email to respondents.

Data analysis Test the survey in a test mode Collect data with at least 3 respondents ( Run button turns to be active) Click Run button to see the analysis results

Publish the survey Before you post or send the link to the respondents, please publish the survey. Once you publish the survey, you can't change the survey. You can only change the survey until the survey is published. So test enough before you publish and post the survey to public. If you changed the survey, the data will be initialized and will be reset. Once you finalized the survey design, you need to publish button then you can t change it. Publish with responses if you want to keep the respondent data you already collected Publish without previous respons es if you want to collect the respondent data all over

Conjoint results Attribute importance metrics as a pie chart If there is a big variation across attribute levels given the attribute, the importance measure is higher Attribute mean utilities as column charts at aggregate level

Aggregate level importance summary Individual level importance score (total 100)

Attribute part-worth summary statistics

Interpret demographic effects on conjoint 25-34 years old customers like Mc Cafe more than Starbucks Male customers are more price sensitive Male customers likes Cappuccino than female customers

Market simulator Define competitive market conditions Set market size and profitability Choose the price variable Predict market share, revenue and profits

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