Cro Audit

CRO Audit

Find the points on a page or flow where visitors lose clarity, trust, interest, or momentum.

Inspect The Page

Use the provided URL, screenshot, copy, or code. If the surface is live, inspect desktop and mobile when possible.

Capture:

• Visitor source and intent.
• Main promise above the fold.
• CTA text, count, and location.
• Form or checkout effort.
• Proof and trust elements.
• Objections addressed or ignored.
• Visual hierarchy and reading order.
• Mobile readability and tap targets.
• Load or rendering issues that affect the decision.

Analyze Friction

Classify each issue:

• Message friction: reader cannot tell what it is, who it is for, or why it matters.
• Trust friction: claim is bigger than proof.
• Choice friction: too many actions or unclear next step.
• Effort friction: form, onboarding, or checkout asks too much too early.
• Timing friction: the ask appears before the reader has enough confidence.
• Mismatch friction: page does not match the traffic promise.
• Technical friction: speed, layout, accessibility, broken states.

Follow The Visitor Decision

Map the page as a decision path:

• Seeing: does the visitor immediately know what this is?
• Believing: does the promise match their intent and feel specific?
• Trusting: is the proof strong enough for the ask?
• Acting: is the next step obvious, low-friction, and appropriately timed?

For each fix, note whether it is reversible. Prefer reversible copy, layout, and proof changes before deep product or pricing changes unless the evidence is strong.

Recommend Changes

Prioritize by likely impact and effort. Include concrete replacement copy or layout changes when useful.

Avoid pretending all pages need the same pattern. A pricing page, waitlist, checkout, and enterprise demo page have different jobs.

Output

Page friction read:
[one paragraph]

Conversion path:
Visitor intent -> Page promise -> Proof -> Action

Hesitation sequence:
Seeing -> Believing -> Trusting -> Acting

Friction log:
| Step | Problem | Evidence | Fix | Reversible | Impact | Effort |

Highest-leverage changes:
1. [change]
2. [change]
3. [change]

Copy replacements:
- Current: [text]
  Replace with: [text]

Test next:
- [experiment or measurement]

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Infinite-Labs-AI
• Source: Infinite-Labs-AI/infinite-skills
• License: MIT
• Homepage: https://infinite.fast/agents/

Install and usage instructions live in the source repository linked above.