Product & UX

Evaluates users' search experiences across intent expression, result relevance, and filter/sort usability to identify actionable improvements for product search, UX, and conversions.

Measures how easily shoppers find products, move through checkout, and trust your site with their payment details — with an AI follow-up that reconstructs the exact moment shoppers got stuck or almost abandoned their cart, rather than just a satisfaction score.

Measures how easily visitors find music, artists, tickets, or content on your website, where they hit friction, and what improvements matter most. Built for music platforms, label sites, and artist hubs, with an AI follow-up interview that reconstructs exactly where a visit broke down instead of relying on vague satisfaction scores.

The standard 10-item SUS questionnaire, scored 0–100 and benchmarkable against decades of published research — with correct alternating positive/negative wording preserved. An AI debrief interview follows the score, so you learn what to fix, not just where you stand.

Measures cross-device notification overload, delivery preferences, and control priorities to inform UX improvements in alert management and reduce user fatigue.

Assesses stakeholder usage patterns, anticipated disruption, and transition readiness before sunsetting a product feature. Designed for product and change-management teams planning deprecation with data-driven mitigation.

Measures how easily shoppers scan, pay, and recover from errors at self-service checkout kiosks, and prioritizes which fixes matter most. An AI follow-up interview reconstructs exactly what happened during a recent frustrating attempt instead of relying on vague complaints. Built for retail UX and store operations teams.

Captures a specific feature request in the requester's own words, gauges how urgent and impactful it would be, and benchmarks it against other candidate ideas using a best-worst trade-off exercise. Built for product teams triaging inbound requests, with an AI follow-up that reconstructs the exact workflow the feature would unblock and what the person does today without it.

Identifies specific design barriers, sensory preferences, and accessibility feature priorities for neurodivergent users. Designed for UX research teams seeking actionable insights to improve digital product inclusivity.

Measures users' comprehension of privacy-preserving analytics techniques, trust in identity protection, and preferences for consent controls and defaults. Designed for UX researchers and product teams evaluating analytics transparency features.

Measures how satisfied shoppers are with a retailer's website — from site speed and navigation to checkout and security trust — and where friction costs sales. Built for e-commerce and CX teams benchmarking site performance, with an AI follow-up that digs into the specific moment a shopper's last visit went right or wrong.

Measures how easily visitors navigate your site, how the visual design lands, and which design elements most need work — with an AI follow-up that reconstructs the exact moment a visitor got confused or stuck instead of just a satisfaction score. Built for product, UX, and marketing teams evaluating a live site or redesign.

Evaluates how people actually use an interior design planning tool or app — from room visualization to furniture shopping — and where they get stuck. Closed questions surface satisfaction and feature priorities; an AI follow-up interview digs into the specific moment the experience broke down, giving product teams a concrete story instead of a vague complaint.

Captures how people actually use your product or service, which features matter most, and where the experience breaks down — with an AI follow-up that digs into the specific moment a respondent got stuck or frustrated. Built for product, UX, and service design teams shaping a roadmap.

Measures whether visitors can find, understand, and trust the content on your website — covering findability, accuracy, completeness, and currency — for product, content, and UX teams auditing site content. An AI follow-up interview reconstructs what actually happened when a respondent hit a dead end, instead of relying on vague satisfaction ratings.

Diagnoses why users abandon forms, signups, and checkout flows. Captures the specific step, blockers, and recovery levers to reduce drop-off and improve conversion rates.

Measures perceived readability, eye strain, and comfort preferences for dark mode interfaces across devices and usage contexts. Designed for UX researchers evaluating dark theme implementations and accessibility.

Evaluates user perceptions of website cookie/consent banners across clarity, control, trust, and behavioral impact to guide GDPR/CCPA-compliant UX improvements.

Evaluates how effectively empty-state screens communicate value, guide first actions, and support onboarding for new or reset users. Use after a user's first session to identify friction points and optimize empty-state design.

Measures how intuitively users locate key tasks within a website's information architecture. Use this to validate navigation labels, identify findability gaps, and prioritize structural improvements.