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Kirkland, WA
USA

Caelus LLC is a company that specializes in researching, designing, and developing great user experiences.

We work primarily on software and hardware but also help in other types of research and design. Here are some of the methods and services we offer:


• Usability study kinds of services (lab studies, site visits, user modeling, etc.)
• Surveys of any size.
• Choice-based modeling/surveys.

• Agile UX/ backlog prioritization

• Software UI design
• UI development

• Training. We can train teams or individuals in areas such as customer site visits methods and strategies, UX research methods, and more.

 

Our research services

We have extensive experience with all of the 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. 

 

Traditional UX studies

 Usability lab evaluations and iterative usability lab evaluations

These are typically run in a usability lab setting. The goal is to uncover and produce insights into your user/customer behavior. The end result is that we will provide actionable and useful suggestions on how to improve your product. 

A typical study is run in three general phases

1) Preparation phase: gathering team input on what is to be tested. Putting together a set of research questions and a script for the study. Finding and recruiting participants for a lab study.

2) Running the study and analyzing the data: a usability specialist will expertly run participants, analyze the data, and write up the results in an actionable way.

3) Presenting or co-presenting the data first to key stakeholders, and then to your broader team once agreement is reached with the key stakeholders.  We do this in a way that reduces or prevents anyone from being embarrassed.  Our goal is to help people improve their products.

Most usability lab studies uses 8-12 participants and can take 3-5 weeks depending on the size and complexity.

Iterative usability lab evaluations use a similar process to conventional lab evaluation except they tend to have fewer participants per study.  For instance, we might run a series of three evaluations each at a different milestone with six to eight participants.

Paper prototype studies

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 on.  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.

There are many ways to run a paper prototype study, but the most common is to have the study facilitator sitting with the participant while the team looks on from another location.

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. 

Quantitative lab studies, benchmarking studies, and competitive analysis

Both of these types of studies are larger and more formal. They typically involve 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 us 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 product. 

Most benchmarking studies uses 20-40 participants and can take 4-8 weeks depending on the size and complexity.

All three types of usability studies (which are often closely related in terms of methodology) involve observation of your users as they interact with your product/design. We typically measure things like: time on task, success/failure rate, user opinion, and user preference.  Unlike less formal lab studies, we tend not interrupt/prompt participants in these kinds of studies as we are focused on measuring success/failure in the absence of external hints or help.

Medical device human factors engineering and testing

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

Backlog prioritization and choice-based research

We employ three basic forms of choice modeling: backlogprioritization (used in Agile), conjoint analysis, and maxdiff. 

Backlog prioritization isa useful method for helping agile teams in conducting continuous prioritizationand reprioritization of backlogs. Using our knowledge of choice based methods, wecreate a prioritized backlog that is measured using a sound empirical method. We are able to reduce or elimination the opinions of just a few vocal people byincluding the data/input from any combination of team members, managers,  customers, etc. Using this method, we effectively and efficiently enable teams tofocus 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 decision making.  For instance, you may have more than one potential set of features that comprise a product, yet you aren’t sure which ones 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.  

MaxdDiff is useful for taking a list of features and then determining form that list the stack rank and relative importance of each feature.  

Using this method we can tell you how much your customers/users want a feature and how much they don’t want that feature.  

Conjoint analysis is useful in determining which combination/attributes/features is most influential in customer choice or decision-making.   For instance, you may have more than one potential set of features that comprise a product yet aren’t sure which ones 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.