Research Services

We have extensive experience with the numerous user experience (UX) research methods described on our site. Our principal researcher has personally run well over 100 usability studies in his career. We are glad to perform any size UX design or evaluation project in the US, Canada, and internationally.

Explore some of the research methods we offer below. Whether you are just starting to think about conducting research or you are in the midst of a complex project, we can help! Start the conversation here:
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  • We conduct research with your customers to uncover and produce insights into your user/customer behavior and provide data-driven actionable and useful suggestions on how to improve your product or service. Research can be performed in a usability lab, remotely via Microsoft Teams or Zoom, or face-to-face in a variety of settings.

    We work with your team to understand your needs and customer questions, and then design and create the research methods and materials. We will run the study, analyze the results, write the report, and present the findings to all your key stakeholders.

    Most user research studies require 5 to 12 participants and can take from 3-5 weeks to complete based upon the complexity of the study and the requirements of the participants.

    We also conduct rapid iterative user research studies over a period of several weeks, using increasingly detailed prototypes that evolve based upon the research findings. For example, we might run a series of three evaluations each at a different milestone with six to eight participants.

  • Paper prototype studies involve the use of low fidelity prototypes. They provide your design team an opportunity to focus your participants' attention on early design and navigation concepts.

    We find that working with paper prototypes early in the design phase is very helpful in producing solid, and useful designs later. These kinds of studies will save you a lot of money in the long-term if run early enough in the design and development process.

    Most paper prototype studies use 4-8 participants per study and usually take 1-2 weeks depending on the size and complexity. These are best run iteratively since once of the biggest advantages of paper prototyping is to make rapid changes. Many teams opt to run a series of two or three paper studies where each study is spaced a week or two apart from the previous study.

  • These studies are larger and more formal, typically involving measurement of a complete or near-complete product or design. The purpose of quantitative and benchmarking studies is to compare two more or more designs and/or to establish a level of usability and design desirability by which future product versions can be evaluated. These methods are also useful when a company wants to compare its products with a competitor’s product.

    Most benchmarking studies use 20-40 participants and can take 4-8 weeks depending on the size and complexity. We typically measure attributes such as time on task, success/failure rate, user opinion, and user preference.

  • We are trained in human factors psychology/engineering and can help you with all phases of your human factors or usability work. We are well versed in the methods outlined by the FDA.

  • We employ three basic forms of choice modeling: backlog prioritization (used in Agile), conjoint analysis, and MaxDiff.

    Backlog prioritization is a useful method for helping agile teams in conducting continuous prioritization and reprioritization of backlogs. Using our knowledge of choice-based methods, we create a prioritized backlog that is measured using a sound empirical method. We can reduce or eliminate the opinions of just a few vocal people by including the input from a combination of team members, managers, customers, etc. Using this method, we effectively and efficiently enable teams to focus on what is important to customers and to the innovation process.

    Conjoint analysis is useful in determining which combination of attributes/features are most influential in customer choice or purchase decision making. For instance, you may have more than one potential set of features that comprise a product, yet you aren’t sure which feaures your customers will most prefer. We present your customers/users with a set of proposed features, products, or services, and then analyze how they make preferences between these products. We can then determine the optimal or preferred feature combinations for your product offering.

    MaxDiff is useful for taking a list of features and then determining the stack rank and relative importance of each feature. This method tells you how much your customers/users want a feature and how much they don’t want that feature.