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Uxia 用户画像与受众定位|简诗 AI

围绕“Uxia 用户画像与受众定位”提供具体执行方法,涵盖用户需求、方案设计、优先级和验证迭代。

person作者: user_fccf428bhubcommunity

Uxia Platform Help

Uxia (uxia.app) is an AI / synthetic-tester usability-testing tool — the synthetic counterpart to the real-human usability tools (Userbrain, UXtweak). Instead of recruiting people, Uxia runs AI "testers" (LLM agents modeled on demographic + behavioral profiles + any uploaded persona docs) that explore your design, prototype, or live URL, "think aloud," and surface UX friction in ~5 min → transcripts, heatmaps, SUS / SUPR-Q usability scores, accessibility checks, and actionable reports across five test types: AI User Test, AI Live Test (paste a live URL), AI User Research, Accessibility Test, and a Human Test (real humans — enterprise/custom-plan only).

Two things to say almost every time (both are Step 4 imperatives):

  • Synthetic ≠ real ≠ demand. AI testers are great for early iteration (stress-test flows 20× a sprint) but don't replace real humans (the founder says so), and a smooth run does not prove anyone will pay — validate the final version with real testers (/sales-userbrain, /sales-uxtweak) and take a build-or-not go/no-go to a real behavior test (/sales-idea-validation).
  • No public REST API — only a marketed-but-undocumented MCP link (Claude/ChatGPT/Gemini; no docs/ endpoints/schemas). Any "pipe results into my CRM/warehouse/Slack" ask is manual export or the MCP link — discover MCP tools at runtime, don't invent endpoints; for a documented pipeline route to /sales-userintuition (or /sales-syntheticusers / /sales-ditto).

Step 1 — Gather context

If references/learnings.md exists, read it first for accumulated platform knowledge.

Ask only what you can't infer:

  1. What do you want from Uxia?
    • A) Set up a test — a test type (AI User Test / Live Test / User Research / Accessibility), tasks, Figma prototype or live URL
    • B) Configure testers — define an audience (demographics/tech literacy), upload persona docs, set tester count
    • C) Read results — transcripts, heatmaps, SUS/SUPR-Q scores, the report
    • D) Judge validity — how realistic the synthetic testers are, whether they replace real users
    • E) Get data out / automate — export a report or wire up the MCP link (no REST API)
    • F) Choose — Uxia (synthetic) vs Userbrain/UXtweak (real humans) vs Synthetic Users/Ditto (synthetic interviews)
  2. Are you testing something you've already built/designed, or still deciding whether to build? The second is an idea-validation question, not a usability question — flag it in Step 2.

Skip-ahead: if the user's prompt already names the task and their question is specific, go to Step 3.

Step 2 — Route or answer directly

| If the user's question is about… | Route to | |---|---| | Real-human think-aloud usability testing (Uxia's testers are synthetic) | /sales-userbrain {question} | | Card sorting / tree testing / first-click IA tests, or the broad usability suite | /sales-uxtweak {question} | | Comparing usability/research/validator tools across the market, or the validate-before-building method | /sales-idea-validation {question} | | Synthetic interviews/surveys against AI personas (a different job from usability testing) | /sales-syntheticusers or /sales-ditto {question} | | An API / webhook-native research or interview pipeline (Uxia has no public API) | /sales-userintuition {question} | | Running a real behavior demand test (smoke-test page, waitlist, pre-sale) | /sales-idea-validation or /sales-funnel {question} |

When routing, give the exact command: "This is a {domain} question — run: /sales-userbrain {original question}"

Otherwise, answer Uxia-specific questions using Step 3.

Step 3 — Uxia platform reference

Read references/platform-guide.md for the full reference — the capability/automation-surface table (five test types, each UI-only / MCP-only), the synthetic-tester data model, best-effort pricing and plan gates (free-trial credits, the flat-monthly-vs-credit ambiguity, the enterprise-gated Human Test + SSO/SCIM), the SUS/SUPR-Q frameworks, the Figma/Jira/Notion/Linear integrations, and the no-API / MCP data-out playbook. Uxia has no public REST API, so references/uxia-api-reference.md documents the (undocumented) MCP surface and integrations, not endpoints.

Answer using only the relevant section — don't dump the full reference.

Step 4 — Actionable guidance

You no longer need the platform guide — focus on the user's specific situation.

  • Say the caveat: synthetic testers are an AI opinion, not real behavior, and not demand. Whatever the user asks, make explicit that Uxia's testers are AI, not real people — great for early-stage iteration (find friction, test flows many times cheaply) but not a replacement for real humans (they lack genuine intuition/emotion/randomness), and a clean synthetic run does not prove anyone will pay. Recommend the pattern the founder describes: iterate with synthetic testers, then validate the final version with real testers (/sales-userbrain, /sales-uxtweak). If the real question is build-or-not, take the go/no-go from a real behavior test via /sales-idea-validation.
  • Flag the automation reality: no public REST API, MCP marketed but undocumented. When automation or export comes up, state plainly there is no public REST API and no webhooks — the only programmatic surface is a marketed MCP link (ChatGPT/Claude/Gemini) with no published docs, endpoints, or schemas. Tell the user to discover the MCP tools at runtime and not to invent endpoints; "sync to HubSpot/Snowflake/Slack" is a manual export otherwise. For a documented pipeline, route to /sales-userintuition (real-human, REST API + webhooks + MCP) or /sales-syntheticusers / /sales-ditto (synthetic studies with a real API).
  • Read the SUS/SUPR-Q scores as directional, not absolute. Uxia scores designs with the standard System Usability Scale (SUS) and SUPR-Q frameworks — useful for ranking variants against each other, but because the raters are AI, treat the absolute number as directional and trust relative comparisons (variant A vs B) over a single score. Pair the score with the qualitative transcripts and heatmaps — the why the testers struggled — which is the more actionable output.
  • Fix shallow feedback with better tasks, not more testers. If the AI testers "narrate the screen" or say "looks easy," that's a task-design problem — write goal-based scenario tasks with no hints ("You want to cancel your subscription — do it"), add open follow-up questions, and define a specific audience (demographics + uploaded persona docs) so a "novice" behaves differently from an "expert." A handful of testers per audience surfaces most friction; more mostly repeat it.
  • Present all pricing as best-effort and point to uxia.app. Pricing is inconsistent across sources — the site shows a Free trial (~50 credits, 1 audience, ~5 testers/test) plus a Custom/Enterprise tier (unlimited, audience enrichment, Human Test, SSO/SCIM), while third-party listings describe a flat monthly Basic/Pro model ("unlimited tests, no 6-figure contracts"). Say the number is best-effort, note the Human Test and enterprise security are custom-plan-only, and point to uxia.app/pricing to confirm.

If you discover a gotcha or tip not in references/learnings.md, append it there with today's date.

Gotchas

Best-effort from research (2026-07) — pricing, plan gates, the five test types, SUS/SUPR-Q scoring, and the (undocumented) MCP/integration surface move; verify at uxia.app.

  • Synthetic ≠ real ≠ demand. Uxia's testers are AI, not humans. Use them for fast early iteration, but they don't replace real users (the founder agrees) and a clean run is not proof anyone will buy — validate the final design with real testers (/sales-userbrain//sales-uxtweak) and take a build-or-not go/no-go to a real behavior test (/sales-idea-validation).
  • It's "not just an LLM," but it's still an LLM under the hood. Uxia layers personas, task simulation, consistency rules, and aggregation on an LLM — better than raw ChatGPT, but still can be confidently wrong and skews agreeable/generic.
  • No public REST API; MCP is marketed but undocumented. The only automation surface is an MCP link to Claude/ChatGPT/Gemini with no published endpoints/schemas — don't invent them; discover at runtime. Everything else is manual export. Route a documented pipeline to /sales-userintuition.
  • The Human Test is enterprise-only (as are audience enrichment, SSO/SCIM) — the free/self-serve tier is synthetic testers only.
  • Pricing is ambiguous — marketing says "flat pricing, unlimited tests"; the site shows a credit-limited free trial + Custom. Treat every figure as best-effort and confirm at uxia.app/pricing.
  • SUS/SUPR-Q from AI raters is directional. The scores use real usability frameworks but the raters are synthetic — read them as a relative signal between variants, backed by the transcripts/heatmaps, not an absolute usability verdict.

Related skills

  • /sales-userbrain — The real-human video-first usability peer — the pick to validate a final design with actual testers after iterating with Uxia's synthetic ones. Install: npx skills add sales-skills/sales --skill sales-userbrain -a claude-code
  • /sales-uxtweak — The real-human usability + information-architecture suite (card sort, tree test, first-click) — route here for IA methods Uxia doesn't do, or to test with real users. Install: npx skills add sales-skills/sales --skill sales-uxtweak -a claude-code
  • /sales-syntheticusers — The synthetic-research peer (AI-moderated interviews/surveys vs personas, with a real REST API) — a different job from Uxia's task-based usability testing. Its synthetic message/creative-tester sibling is /sales-evelance (AI personas score copy/creative/product on 12 psychology metrics) — reach for Evelance when the question is "does my message land", Uxia when it's "is my design usable". Install: npx skills add sales-skills/sales --skill sales-syntheticusers -a claude-code
  • /sales-idea-validation — The tool-agnostic validate-before-building method + the full research/usability/validator tool landscape (use this to decide build-or-not; a passing synthetic usability test is not demand). Install: npx skills add sales-skills/sales --skill sales-idea-validation -a claude-code
  • /sales-userintuition — The API/webhook/MCP-native real-human interview peer — the pick when you need a documented, programmatic research pipeline Uxia can't offer. Install: npx skills add sales-skills/sales --skill sales-userintuition -a claude-code
  • /sales-funnel — Build the smoke-test / fake-door landing page that turns a design hypothesis into a real demand test. Install: npx skills add sales-skills/sales --skill sales-funnel -a claude-code
  • /sales-do — Not sure which skill to use? The router matches any sales objective to the right skill. Install: npx skills add sales-skills/sales --skill sales-do -a claude-code

Examples

Example 1: "Are these AI testers real enough to trust — do they replace real user testing?"

User says: "Uxia gives me feedback in 5 minutes from AI testers. Can I just use this instead of recruiting real users?" Skill does: Explains Uxia's testers are synthetic (LLM agents on demographic/behavioral profiles), not people — useful for fast early iteration but not a replacement for real humans (they lack real intuition/emotion/randomness, skew agreeable), and a smooth synthetic run is not proof anyone will pay. Recommends the founder's pattern — iterate with synthetic testers, then validate the final version with real testers (/sales-userbrain, /sales-uxtweak) — and, if the question is build-or-not, taking the go/no-go from a real behavior test via /sales-idea-validation. Result: The user keeps Uxia for cheap iteration but plans a real-human validation round before shipping.

Example 2: "How do I get every finished Uxia test into our data warehouse / Slack automatically?" (developer/automation)

User says: "I want each completed test's transcript and report to flow into Snowflake and post a summary to Slack." Skill does: States plainly Uxia has no public REST API and no webhooks — the only programmatic surface is a marketed MCP link to Claude/ChatGPT/Gemini with no published endpoints or schemas, so you must discover the MCP tools at runtime and not invent endpoints; absent MCP access, data-out is manual export of the report/transcript to run your own ETL. If a documented live pipeline is required, routes to /sales-userintuition (REST API + HMAC webhooks + MCP) or /sales-syntheticusers / /sales-ditto (synthetic studies with a real API), noting those are interview/survey studies, not Uxia's task-based usability tests. Result: The user stops hunting for a REST API that doesn't exist and either uses the MCP link or a manual export routine.

Example 3: "What does the free plan give me, and how does Uxia score my design?"

User says: "I'm a solo maker. What can I do on Uxia's free tier, and what's this SUS/SUPR-Q number it shows?" Skill does: Gives best-effort free-tier limits (a credit-limited free trial — ~50 credits, 1 audience, ~5 testers/test — with the Human Test, audience enrichment, and SSO/SCIM gated to Custom/Enterprise), flags that pricing is inconsistent (flat-monthly marketing vs on-site credits) and points to uxia.app/pricing. Explains the scores use the standard SUS and SUPR-Q frameworks but, because the raters are AI, to read them as a relative signal between design variants (backed by the transcripts and heatmaps), not an absolute usability verdict. Result: The maker runs a free-trial test, compares two variants by relative SUS, and reads the transcripts for the why.

Troubleshooting

"The AI testers just narrate the screen / say it's easy — no real insight"

Symptom: Synthetic testers describe the page or say "looks easy to use," with nothing actionable. Cause: Vague, leading, or hint-laden tasks, or an undefined audience, so the AI has nothing real to do. Solution: Write goal-based scenario tasks with no hints ("You want to return an item you bought last week — do it"), add open follow-up questions ("what did you expect?", "what was confusing?"), and define a specific audience (demographics + tech literacy + uploaded persona docs) so a "novice" behaves differently from an "expert." Read the transcripts/heatmaps for the why, and remember even a clean result proves the design works in simulation, not that anyone will pay.

"I can't find Uxia's API to automate this"

Symptom: The user is looking for REST endpoints, webhooks, or a Zapier app and can't find them. Cause: Uxia has no public REST API and no webhooks — the only automation surface is a marketed but undocumented MCP connection to Claude/ChatGPT/Gemini (no published endpoints/schemas). Solution: Don't invent endpoints — if you have MCP access, discover the tools at runtime; otherwise data-out is manual export of the report/transcript. For a documented, API-native pipeline, use /sales-userintuition or /sales-syntheticusers / /sales-ditto (synthetic studies with a real API).

"Can I test with real humans, and why is my score different from a real test?"

Symptom: The user wants real-human testing on Uxia, or distrusts the AI SUS/SUPR-Q number. Cause: Uxia's default testers are synthetic; the Human Test is gated to the Custom/Enterprise plan, and AI raters produce a directional, not absolute, usability score. Solution: On self-serve, expect synthetic testers only — for real humans upgrade to the enterprise Human Test or run a real-human tool (/sales-userbrain, /sales-uxtweak). Treat the AI SUS/SUPR-Q as a relative signal between variants (trust A-vs-B ranking over the absolute number), backed by transcripts.

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