An overview of the Adoption Likelihood Factors Questionnaire (ALFQ), when to use it, and how it compares to other psychometric questionnaires.
The quantitative usability testing and UX research field is filled with psychometrics that measure the data beyond subjective qualities of users via qualitative means. In fact, our platform provides all the psychometrics that design and research teams could ever want, but we noticed the industry as a whole was missing a bit of nuance when it came to desirability and predictive success models.
The Adoption Likelihood Factors Questionnaire (ALFQ) was developed to predict the success of a product (both web and mobile-based) based on adoption likelihood. The ALFQ consists of 16 post-test survey prompts that calculate 4 crucial metrics to predict the success of fledgling products. These metrics are:
The 16 questions and the metrics they measure:
I felt very confident using this website/app. (Usability)
Learning to operate this website/app was easy for me. (Usability)
I would imagine that most people would learn to use this website/app very quickly. (Usability)
I found this website/app easy to use. (Usability)
I understand what this website/app is for. (Usefulness)
It was clear to me what this website/app can do for me. (Usefulness)
I would use this website/app to perform a task in my daily life. (Usefulness)
I found this website/app to be useful. (Usefulness)
The information provided by the website/app is believable. (Credibility)
I felt it was safe to interact with this website/app. (Credibility)
I would feel comfortable using this website/app’s services. (Credibility)
I believe this website/app is trustworthy. (Credibility)
I enjoyed using this website/app. (Desirability)
I would reuse this website/app in the future. (Desirability)
I would prefer to use this website/app over similar ones. (Desirability)
I will recommend this website/app to a friend or colleague. (Desirability)
Users mark their answers to the 16 items above on a 5-point Likert scale, with 5 meaning “Strongly agree” and 1 meaning “Strongly disagree.” The final result is an individual score for each of the 4 factors as well as a composite ALFQ score.
How does ALFQ differ from other psychometrics?
Put simply, ALFQ measures how likely designs by new business, teams, or companies will be successful (or adopted for use). We utilized this psychometric with our Blockstack partnership indie developers to gauge their products' accessibility to general audiences.
Here's a list of the other psychometrics on the Trymata platform and why ALFQ might be a better alternative depending on your situation.
The System Usability Scale is the most widespread measurement in UX and usability testing, and for good reason. SUS will give you the topline rating of your product’s usability, but lacks in determining the credibility and desirability of your design.
The Post-Study System Usability Questionnaire is great for testing the overall quality of information in addition to usability, but like the SUS, suffers from the same problems in demonstrating desirability.
Jeff Sauro’s Standardized User Experience Percentile Rank Questionnaire and our ALFQ are sister psychometrics in their intentionality. Both measure more than just usability, tapping into the heart of the user’s more abstract thoughts of a product such as trust and credibility.
One notable difference is the development stage: SUPR-Q is best utilized for established companies that users are familiar with, and whose designs have already been through rounds of SUS and/or PSSUQ testing. Meanwhile, ALFQ is built for UX and design teams on the opposite end of the spectrum who can’t rely on brand familiarity or previous design success.
The Survey Respondent Scale is the brainchild of a partnership between TryMyUI, MeasuringU, and QuestionPro to address the cognitive stress and fatigue of survey responses on testers. SRS is an extremely specialized metric that is meant more for marketing than usability.
When should I use ALFQ?
It might be most helpful to ask yourself, “where is my product and brand in the timeline of development and in the context of my industry?”
The ALFQ is the perfect psychometric tool for indicating both the ceiling (potential adoptability) and the floor (how immediately usable) of a product. It takes the best pieces of other psychometrics and composites them into a predictive model that teams can base their roadmap and design decisions on.
If you and your team are satisfied with your untested UX design, but also aren’t sure if usability is the only potential issue to uncover, running ALFQ is absolutely for you.
Here are some success stories from the Blockstack partnership program:
- Quantitative and Qualitative Testing
- The System Usability Scale
- SUPR-Q and usability testing
- User testing your mobile apps