Quantitative Research Training Workshops

URI provides quantitative research training workshops to client research teams.

These interactive workshops are developed and run by our experts who are all highly experienced with quantitative research methods and advanced analyses. Designed for both quantitative research novices who are looking to begin developing their knowledge, as well as for those with more quant experience, they can be a refresher or provide additional depth of knowledge. Half-day or full-day workshops include case studies to provide real-world examples of the outcomes and benefits of these analyses as well as Q&A to ensure full understanding of the material. Request more information.

URI offers several quantitative research workshops, including:

  • Foundational Quantitative Research Methods
  • Maximum Differences Analysis (MaxDiff)
  • Segmentation Analysis
  • Kano Analysis
  • Conjoint Analysis

Foundational Quantitative Research Methods Workshop

This workshop covers essential information which anyone getting started in quantitative research needs to know: data types, sampling methods, estimation (margin of error and confidence intervals, p-values, standard deviation, Z-Scores), data distribution, fundamentals of statistics (estimation and hypothesis testing), experimental design and inferential statistics (chi-square, ANOVA, t-tests, regressions, etc.), as well other foundational quantitative methods and concepts to provide the basis needed to move on to more advanced quantitative research methods.

Maximum Differences Analysis (MaxDiff) Workshop

In this workshop, we provide an in-depth understanding of the MaxDiff methodology, its purpose, when it is used (and when it shouldn’t), and why it is often a superior approach to simple rating or ranking of attributes. MaxDiff is a fundamental “go-to” method in the research community and is used to understand which features are most important to product users. Business applications include product development, branding and message testing, and customer satisfaction initiatives.

Segmentation Analysis Workshop

This workshop covers what segmentation analysis is, what it is used for, and the different types of segmentation that can be employed depending on the business need. With segmentation analysis, decision makers can gain a detailed picture of their customers/users and how different sub-audiences differ in terms of things like pain points, key purchase/appeal drivers, appeal of branding elements, and how products/services/technologies are used, along with many other applications. With this type of detailed audience information, decision makers can develop products and marketing campaigns that are optimized for their various user segments.  

Kano Analysis Workshop

In this workshop we dive into a very useful type of capability/feature set analysis. This analysis is based on the concept that capability/feature fulfillment does not always have a linear relationship to customer satisfaction. It is a quantitative method that models capabilities/features to help prioritize the importance of each capability/feature based on their ability to drive user satisfaction if included and well-executed, or dissatisfaction if excluded or poorly executed. The key value for decision makers derived using the Kano method include: 1) Set priorities for product development; 2) Gain greater insight into the how capabilities/features function in driving customer satisfaction; 3) Identify differences between capabilities/features between user audiences, and; 4) Help to differentiate products from competitors.  

Conjoint Analysis Workshop

This workshop covers one of the most valuable types of research methods for making product development and go-to-market decisions. Conjoint analysis is a type of choice analysis (others include TURF analysis and MaxDiff analysis), in which respondents make choices regarding product features and other components of the product. Differing from other choice modeling methods in which choices are made about individual features and offerings, with conjoint analysis respondents make choices from a set of offerings, versus individual features, that would match what the company could feasibly develop and deliver. The feature sets can also be ones which would potentially differentiate them from competitors, which can then inform decisions regarding product offer sets that position products against competitor offerings. Using conjoint analysis, decision makers see exactly which offer sets will have the best chance of success in the marketplace. 

To schedule a Quantitative Research Training Workshop

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