DIY Experimental Design
With Conjointly, you can upload your own experimental design from the JMP Discrete Choice designer. Conjointly will handle data collection and, if you require, fielding to panel respondents. Once data have been collected, you will be able to download a .csv output for analysis in JMP. However, Conjointly will not automatically produce a report for this type of experiment.
Experimental design files need to comply with the JMP standard. Here are a couple of examples:
- Example 1 (alternatives are not labelled, with multiple blocks/surveys)
- Example 2 (with labelled alternatives, only one block/survey)
Once the file is selected, you will need to choose the type of the "None of the above" option (because it is not specified in the design file):
- Forced choice (i.e., no opt-out option),
- Standard "None of the above" option (part of the choice set), or
- Two-stage response (a confirmation question after the choice set).
Next, the file is uploaded and validated. You will then be able to format the study, tweak the names of attributes and levels, and specify other settings that are available to conjoint experiments on the platform.
Export of collected data is available in the JMP "stacked" format (see example exported file). Please note:
- Each row in these exports corresponds to an alternative. For example, for each respondent that replies to a study with eight questions per block/survey and two alternatives in each question, there will be 16 rows. If a respondent selects a particular alternative, the "Choice Indicator" column for that alternative row will contain "1".
- "None of the above" alternatives are omitted from the file: if a respondent chooses "None of the above", the rows that correspond to the question will contain all zeros in the "Choice Indicator" column.
- Respondent-level information (for example, location, answers to additional questions, and GET variables) are repeated on each row for each respondent.
Partial-profile designs are also supported (see example design file). In order to specify such a design, you need to insert "NULL" in the place of level names for the hidden attribute in specific choice sets.
Explore automated research methods
Fully-functional online survey tool with various question types, logic, randomisation, and reporting for unlimited number of responses and surveys.
Feature and claim selection and measuring willingness to pay for features for a single product.
MaxDiff (aka Maximum Difference Scaling or Best–Worst Scaling) is a statistical technique that creates a robust ranking of different items, such as product features.
Efficiently test up to 300 product claims on customer appeal, fit with brand, and diagnostic questions of your choice.
Pricing, feature and claim selection in markets where product characteristics vary across brands, SKUs, or price tiers.
Identify winning product variants from up to 300 different ideas (e.g., designs, materials, bundle options) on customer appeal, fit with brand, and diagnostic questions of your choice.
Test pricing of new and existing consumer goods in a competitive context using elasticity charts, revenue, and profitability projections.
Determine price elasticity for a single product and identify revenue-maximising price level.
The Price Sensitivity Meter helps determine psychologically acceptable range of prices for a single product and approximately estimate price elasticity.
Perform focussed comparisons between two items to determine which performs better.
Ask respondents to evaluate product concepts and digital assets one-by-one to get a read of their preferences and perceptions with various question types.
Test the effectiveness of your digital advertisements in an online environment
Efficiently evaluate potential business names to identify the best one to represent your brand
Efficiently test potential images to identify the best one for your ads
Efficiently test ad copy to identify the best one for your campaign
Efficiently test potential brand names to identify the best one to represent your business
Efficiently test potential domain names to identify the perfect new home for your brand
Efficiently test print ads to identify the best one for your campaign
Efficiently test out-of-home ads to identify the best one for your campaign
Efficiently test potential product names to identify the best one to reflect your brand
Efficiently test potential business card designs to identify the best one for your business
Efficiently test potential logos to identify the best one for your ads
Efficiently test packages to identify the best one for your product
Efficiently test product concepts to identify the best one for your business
Efficiently test graphic designs to identify the best one for your brand
Conduct automated TURF analysis on results of any Conjointly experiment (or an outside dataset) using this user-friendly TURF analysis tool.
Allowing advanced choice modellers to upload their own experimental designs and perform data collection on Conjointly.
Ensure product-market fit and maximise your user acquisition and expansion, by differentiating software features according to your users' needs.