Usability research & AI evaluation
See where people struggle, understand why, and know what to improve.
32%
leave at the comparison step
3 / 5
people struggle to compare options
+14 pp
booking completion · percentage points
Led by Adnan Khan15+ years in UX and product design
From insight to improvement
This illustrative example shows how we examine what happened, why it matters, and what could make the experience better.
The customer’s requestFriday after 4 pm, ideally under $200. Show the options before booking.
“What day and time would you prefer?”
Repeats a question already answered.
“Friday at 4:30 fits your availability. The call-out fee is $180; the total repair cost is not yet known. Nothing is booked. Would you like to compare another service or request a quote?”
Proposed improvement · needs testing with real users.
Illustrative audit extract
This is a fictional conversation and a proposed evaluation plan. No automated test run, live analytics or participant research has been conducted for this example.
The customer must repeat a preference and work out why the recommendation fits. The exchange leaves them without a clear answer about cost or an explanation of how to compare alternatives.
Proposed priority: investigate before release. Check how frequently the pattern occurs across relevant tasks and how much it affects decisions. This excerpt does not establish an internal memory fault or show that an unauthorised booking occurred.
Ask representative customers to compare services, change one constraint and decide their next step. Observe repeated effort, hesitation, recovery and task completion. Ask them to explain the likely cost and booking status in their own words, and investigate why they trusted or questioned the recommendation.
Rerun the automated scenarios, then test whether people can compare options without restating unchanged preferences, distinguish a call-out fee from the total cost, and correctly explain what has or has not been booked. Use observed behaviour and participant feedback to refine the response and controls. Automated pass rates alone do not establish human usability.
What your team takes away
A shared view of the experience, findings grounded in evidence, and a plan your team can act on.
Connect the customer’s goal with the moments that need attention.
Illustrative journey · not a client result
“What day and time would you prefer?”
The assistant asks for availability already provided. Investigate how this affects effort and confidence.
Illustrative finding · impact needs research
Proposed improvements · ready to test
How we work
Research methods chosen for your question, with scope and costs agreed before the work begins.
Agree the journey, users and success criteria. Confirm scope, access and timing before we begin.
A shared research briefWalk through the experience, check realistic scenarios and observe representative users.
Evidence from real tasksReview the findings together. Prioritise changes and agree how to check the improvements.
A practical next stepJourney mapping and behavioural data help us find where to look. Walkthroughs, scenario checks and usability testing help us understand why.
For AI experiencesWe examine task success, context, explanations, uncertainty and control. Automated checks establish a baseline; real users reveal effort, understanding and trust.
For product teams launching or improving AI
Find where your AI feature creates confusion, unnecessary effort or misplaced confidence—and decide what to improve before wider rollout.
One journey · Five sessions · Two-week sprint
A kickoff, journey map and agreed criteria for one AI feature and one primary user group.
12 realistic scenarios, three attempts each, to examine context, explanations, uncertainty, control and recovery.
Up to 45 minutes with each participant, observing real tasks and investigating understanding, effort and trust.
Prioritised findings, up to three proposed interaction improvements and a 60-minute team walkthrough.
One recheck of up to six original scenarios on a revised version, requested within 30 days of the walkthrough.
Led by Adnan Khan, with 15+ years in UX and product design. Meet your evaluator
One working AI feature, one critical journey, one primary user group, one language (English) and one agreed desktop or mobile environment. Five remote moderated sessions cover up to two tasks in that journey. You identify and invite suitable users; we agree screening criteria and handle the research. This is qualitative research, not a population-level performance benchmark.
We confirm the test environment, reference information, participant consent and access before accepting the scope. Automated scenario execution depends on a successful access and feasibility check; the method is agreed in writing. Custom integrations, external recruitment, specialist domain reviews, implementation and ongoing monitoring are outside this package.
The initial 10-business-day sprint starts once scope, the first payment, access and participant bookings are ready. Delays or changes are discussed and dates revised together. Request the included recheck within 30 days of the findings walkthrough; we schedule it within five business days of receiving a stable revised version. It covers up to six original scenarios, three attempts each, and an updated findings note. Additional user sessions are separate.
To use the promise, reply to our engagement email within 14 calendar days of the findings walkthrough. You don’t have to implement recommendations, prove a financial loss, accept more work or give a testimonial. We initiate the full refund within five business days, including GST and any charges collected from you for this engagement, and waive the unpaid balance. You keep the delivered report; any unperformed follow-up work is cancelled. Costs you pay directly to third parties are not reimbursed.
We provide evidence and recommendations to inform your decision. The evaluation does not certify safety, compliance or launch readiness, or guarantee a commercial result. The scope and terms are confirmed before payment.
Book a 30-minute, obligation-free discovery call. We’ll confirm fit and scope before you commit or pay.
We can evaluate digital journeys, real-world touchpoints, and the hand-offs between them. The scope follows the customer’s task and can include a website, app, booking process, support channel, or AI-powered feature.
No. We can start with walkthroughs and usability testing, review the data you have, and help define or configure useful tracking. Data access, tools, privacy requirements, and any setup work are agreed as part of the scope.
Yes. The method depends on what is ready and what you need to learn. A prototype can help test comprehension and interaction. Questions about actual output quality, reliability, or response times require access to the working AI. Simulated responses are identified as such.
Deliverables are agreed before starting. They can include a journey map, documented walkthroughs, behavioural analysis, usability-test findings, and an AI experience assessment. The report brings the evidence, limitations, priorities, and recommended next steps together.
The introductory AI Experience Evaluation is A$2,500 including GST for our first three clients. It includes five moderated sessions with participants you supply and one targeted follow-up check. External recruitment, implementation and additional research are separate. Other evaluations receive a written scope and quote.
Connect insights across the tools you use.
PostHog
Amplitude
Stripe
GitHubStart with a conversation
Tell us where customers struggle. We’ll discuss the question, what you already know, and whether an evaluation would help.
Scope, fee and timing are agreed after the conversation.
