Evidence-Based UX Audit for SaaS & AI Products by Arif khanEvidence-Based UX Audit for SaaS & AI Products by Arif khan
Evidence-Based UX Audit for SaaS & AI ProductsArif khan
Cover image for Evidence-Based UX Audit for SaaS & AI Products
I turn scattered, real user complaints into evidence-backed UX fixes — not redesigns based on guesswork or personal taste.
Most UX audits start from opinion: "this feels clunky," "this could be cleaner." Mine start from documented evidence — reviews, support-team replies, forum threads, and usage patterns that are already public and verifiable. I trace every design decision back to a specific, sourced problem, so the recommendations hold up when someone on your team asks "how do we know this is actually an issue?"
What you get: → A sourced problem audit — the friction points your users are already reporting publicly, with links to every source → A scoped design proposal — 2-4 focused UX improvements, built to fit your existing product (no unnecessary redesigns) → A written case-study document explaining the reasoning behind every recommendation, ready to share internally
Best fit for: SaaS products, AI tools, and app-builder platforms that already have public reviews (G2, Trustpilot, Reddit, app-store reviews) to work from.
See a full example of this process in my "Closing Lovable's Visibility Gap" project below.
FAQs

Starting at$2,999
Duration1 week
Tags
Figma
Figma Make
UX Audit
Product Designer
UX Researcher
Case Study
SaaS
Service provided by
Arif khan Baroda, India
31
Followers
Evidence-Based UX Audit for SaaS & AI ProductsArif khan
Starting at$2,999
Duration1 week
Tags
Figma
Figma Make
UX Audit
Product Designer
UX Researcher
Case Study
SaaS
Cover image for Evidence-Based UX Audit for SaaS & AI Products
I turn scattered, real user complaints into evidence-backed UX fixes — not redesigns based on guesswork or personal taste.
Most UX audits start from opinion: "this feels clunky," "this could be cleaner." Mine start from documented evidence — reviews, support-team replies, forum threads, and usage patterns that are already public and verifiable. I trace every design decision back to a specific, sourced problem, so the recommendations hold up when someone on your team asks "how do we know this is actually an issue?"
What you get: → A sourced problem audit — the friction points your users are already reporting publicly, with links to every source → A scoped design proposal — 2-4 focused UX improvements, built to fit your existing product (no unnecessary redesigns) → A written case-study document explaining the reasoning behind every recommendation, ready to share internally
Best fit for: SaaS products, AI tools, and app-builder platforms that already have public reviews (G2, Trustpilot, Reddit, app-store reviews) to work from.
See a full example of this process in my "Closing Lovable's Visibility Gap" project below.
FAQs

$2,999