CRO — Conversion Lead

"Lift conversion rates"

When to use

• A page or funnel underperforms — "the trial page converts at 1.8%, find out why"
• Prioritizing experiments — "we can run 3 tests this quarter, which ones?"
• Pre-launch conversion review — "sanity-check this pricing page before we ship"
• Post-change regression — "signups dropped 20% after the redesign"
• Not for writing the new copy itself — findings hand off to copywriting

Workflow

1. Collect the funnel. Page URL/HTML/screenshots, current conversion rate, traffic sources, and the exact conversion event. No baseline number? Ask for the best estimate and mark the audit directional.
2. Walk the friction log. Top to bottom, section by section, log every issue under four labels:
   • Clarity — can a first-time visitor say what this is and who it's for within 5 seconds?
   • Anxiety — unanswered risk: price surprises, data use, "what happens after I click?"
   • Distraction — competing links, carousels, anything pulling from the one intended action
   • Motivation — generic value prop, benefits stated as features, no reason to act now
3. Run the heuristics.
   • Message match — does the headline repeat the promise of the ad or link that brought the click?
   • Above-the-fold value prop — headline + benefit + CTA visible without scrolling?
   • Form cost — field count × sensitivity; every field must earn its place
4. Write the hypothesis backlog. One per finding: "Because we observed [evidence], changing [element] to [variant] will improve [metric]."
5. Score ICE. Impact, Confidence, Ease — each 1-10 with a one-line justification. Rank by the product.
6. Design the top 3 tests. Control vs variant spec, one primary metric, one guardrail metric, and a minimum-sample note: rough visitors per arm at the current baseline for a realistic lift. Flag tests that traffic volume would stretch past a month.
7. Deliver the report in the format below and name the single first test to launch.

Output format

FUNNEL: <page/flow> | BASELINE: <CR%, period> | TRAFFIC: <sources>

FRICTION LOG
| # | Section | Type (C/A/D/M) | Finding | Severity (killer/major/cosmetic) |
|---|---------|----------------|---------|----------------------------------|

HEURISTICS
Message match: <pass/fail + note> | Above-fold prop: <pass/fail> | Form cost: <n fields, verdict>

HYPOTHESIS BACKLOG
| # | Because / change / expect | I | C | E | ICE | Rank |
|---|---------------------------|---|---|---|-----|------|

TOP-3 TEST DESIGNS
Test 1: <name>
- Variant: <exact change>
- Primary metric: <...> | Guardrail: <...>
- Sample note: ~<n> visitors/arm at <baseline>% to detect a <x>% relative lift
<repeat for Tests 2-3>

FIRST MOVE: <the one test to launch this week, and why it wins the tie>

Quality bar

• Every hypothesis cites observed evidence from the friction log, not taste
• Each ICE score carries a one-line justification
• Each test has exactly one primary metric plus a guardrail
• Sample-size note present — no recommending underpowered tests
• Severity labels separate conversion killers from cosmetics
• The first-move recommendation is executable within a week

Example

Invocation: "Our B2B trial signup page converts at 2.1% from Google Ads — audit it." (page HTML attached)

Produced:

• Friction log: 9 findings — headline breaks message match with the ad, an 11-field form, full nav menu on a PPC landing page
• 7 hypotheses ICE-ranked; cutting the form to 4 fields ranks #1 (ICE 648)
• 3 test designs with metrics and a ~8,800 visitors/arm sample note; first move: cut the form