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Want to see how NewtonX can help you?

We deliver both scale and specificity

Our technology reaches across 140+ industries to give you the scale of a panel combined with the depth of an expert network.

140+

industries

  • Cryptocurrency specialists advising on hedge fund projects 
  • Advertising professionals overseeing brand spend
  • Reddit users that visit Reddit for NSFW content
  • IT decision-makers evaluating cloud software services

Our conjoint analysis insights

Are you trying to decide which combination of features to include in your new product or service? Perhaps you’re prioritizing which features you should update on an existing product. You can remove any guesswork by basing your decisions on NewtonX conjoint analysis insights. 

By leveraging the NewtonX Knowledge Graph to custom recruit the best professionals to answer your questions, you get a clear understanding of which combination of attributes will be most valued by your different audience segments. This is the kind of competitive intelligence you need to increase your market share with strong product-market fit and the perfect price point. A conjoint study helps you avoid investing in product developments that aren’t valued by your clients. 

Your custom findings reveal those elusive nuances between the values of different stakeholders in your buyer teams. You can use this deeper understanding of your brand personas to increase the impact of all targeted communications. You might even uncover unexpected opportunities for new features, services or revenue streams. 

Insights from NewtonX conjoint analysis research are a reliable springboard from which to make strategic decisions across your organization. Your pricing, marketing, sales and product development strategies all benefit from knowing what your clients and prospects really value and are willing to pay for.

Strategy & Planning

  • Research strategy design
  • Screener design 
  • Interview guide questions
  • Survey questionnaire design: survey draft creation
  • Custom survey styling

Execution

  • Survey recruitment
  • Survey programming, coding, and hosting
  • Survey test (QA)
  • Survey fielding
  • Data consolidation & cleaning
  • Raw data extract

Data Analysis

  • Insight synthesis & analysis
  • RIM weighting (Random Iterative Method)
  • Crosstab analysis
  • Conjoint analysis

Reporting

  • Automated charting
  • Manual charting
  • Top-line reports
  • High-level report or presentation
  • Extended full report or presentation draft
  • Key insights
  • Hypothesis testing
  • White labeling

What is conjoint analysis

B2B buyer journey

Types of conjoint analysis

Conjoint analysis is a versatile market research methodology that allows businesses to understand consumer preferences and determine the key factors that drive their decision-making. It helps researchers gain insights into the trade-offs consumers make when choosing between different products or services. To cater to different research objectives and data collection approaches, various types of conjoint analysis have been developed. Each type offers unique advantages and is suitable for different research scenarios.

Choice-Based Conjoint Analysis

This type of conjoint analysis involves presenting respondents with multiple product profiles and asking them to choose their preferred option from each set. By analyzing these choices, researchers can determine the relative importance of different attributes and simulate market scenarios to understand consumer preferences and predict their decision-making. Choice-based conjoint analysis provides insights into preference shares and helps estimate market share.

Rating-Based Conjoint Analysis

In this approach, respondents rate or rank different levels of each attribute independently. Instead of making choices between profiles, respondents provide ratings or rankings based on their preferences for specific attribute levels. Rating-based conjoint analysis allows for a more granular analysis of individual attribute levels and their impact on overall preference.

Best-Worst Scaling Conjoint Analysis

This method involves presenting respondents with sets of profiles and asking them to indicate the best and worst options from each set. By focusing on the extreme choices, best-worst scaling conjoint analysis provides valuable information about the relative importance of different attributes and levels, making it useful for identifying key drivers of preference.

Adaptive Conjoint Analysis

Adaptive conjoint analysis is an interactive approach where respondents are presented with a series of choices based on their previous selections. The subsequent choices are adjusted based on the respondent’s previous preferences, allowing for a more efficient and personalized data collection process. This method helps to identify the most important attributes and levels quickly.

When to use conjoint analysis

market research online communities

Resources

Unlocking value with the laddering method

Discover the emotional motivation behind your prospects’ purchasing decisions using the laddering method.

Product-market fit research: How to do market size analysis

How to do market size analysis for product market fit.

Product development market research methods

Product development market research is the best way to ensure that a company brings their product to market or communicate new features successfully. Before investing time, energy and money behind a launch, product marketers look

Take it from the world’s leading companies.

NewtonX’s platform gives us continued confidence that we’re sourcing the highest quality data to drive critical business decisions.

Jason Talwar
Insights Executive with 15+ years of experience (Salesforce, Tableau, Microsoft)

I was really excited when we found NewtonX. Their Custom Recruiting has genuinely been a game changer for us in terms of data quality. Not only do I have much greater trust in the data, but the variation in the data means I can more easily provide actionable direction for our product and marketing teams without finding myself rationalizing away bad data.

Matt Harris
Senior Customer Research & Insights Manager, Checkout.com