| name | cro-optimizer |
| description | CRO specialist that pulls live analytics data from Humblytics API, analyzes conversion funnels, identifies drop-off points, and generates prioritized A/B test hypotheses. Use when analyzing conversion rates, diagnosing funnel leaks, optimizing signup flows, or creating test roadmaps. Triggers: CRO, conversion rate, funnel analysis, drop-off, optimize conversions, test hypothesis. |
| metadata | {"version":"1.0.0","author":"Humblytics"} |
CRO Optimizer
Purpose
Analyze conversion funnels using live Humblytics analytics data, identify the highest-impact drop-off points, and generate prioritized A/B test hypotheses with expected revenue impact. This skill turns raw analytics into a ranked optimization roadmap.
When to Use
- Diagnosing why a funnel is underperforming
- Identifying the biggest conversion bottleneck across a user journey
- Generating a prioritized list of A/B test ideas
- Preparing a CRO sprint plan or quarterly optimization roadmap
- Analyzing page-level or step-level drop-off rates
- Comparing conversion performance across segments (device, source, geography)
Credentials
This skill reads a Humblytics API key from the environment. Never paste API keys directly into chat — they persist in transcripts and logs.
Setup (one time):
cp .env.example .env at the repo root and fill in HUMBLYTICS_API_KEY
source .env in your shell before running the agent (or use direnv, or add the exports to your shell profile)
- Get the key from Humblytics Dashboard > Settings > API
- The skill will ask for your Property ID (also in Dashboard > Settings > API)
If HUMBLYTICS_API_KEY is not in the environment, stop and point the user at .env.example — do not accept the key in chat.
Before You Start
- Confirm the property ID — Ask the user which Humblytics property to analyze
- Identify the funnel — Clarify which conversion flow to examine (e.g., homepage > pricing > signup > onboarding)
- Check for context — Look for existing project docs, AGENTS.md, or product briefs that describe the business model, target audience, and current conversion goals
- Establish the time range — Default to last 30 days; ask if the user wants a different window
- Confirm API access — Verify
HUMBLYTICS_API_KEY is available as an environment variable
Core Workflow
Step 1: Pull Funnel Data
Retrieve analytics data from the Humblytics API:
- Page views and sessions for each step in the funnel
- Event data for key conversion actions (signups, clicks, form submissions)
- Device and source breakdowns to identify segment-specific issues
- Heatmap summaries if available for high-traffic pages
Use the Humblytics API endpoints:
GET /properties/{propertyId}/analytics/pages — Page-level traffic
GET /properties/{propertyId}/analytics/funnel — Funnel step data
GET /properties/{propertyId}/analytics/events — Custom event tracking
GET /properties/{propertyId}/heatmaps — Click and scroll heatmap data
Step 2: Map the Funnel
Build a complete picture of the user journey:
Traffic Source → Landing Page → Key Action → Conversion → Retention
For each step, calculate:
- Volume: How many users reach this step
- Conversion rate: Percentage who proceed to the next step
- Drop-off rate: Percentage who abandon at this step
- Absolute drop-off: Raw number of users lost
Step 3: Identify the Biggest Leak
Apply the Largest Leak First principle:
- Calculate the absolute number of users lost at each step
- Rank steps by absolute drop-off (not percentage)
- The step losing the most users in absolute terms is your highest-priority optimization target
Why absolute over percentage: A 50% drop-off at a step with 100 visitors loses 50 people. A 10% drop-off at a step with 10,000 visitors loses 1,000 people. Fix the 1,000-person leak first.
Step 4: Diagnose Root Causes
For each high-drop-off step, investigate:
- Page load time — Slow pages kill conversions. Check if the step has performance issues.
- Mobile vs desktop — Is the drop-off concentrated on mobile? Layout/UX issue.
- Traffic source — Do certain acquisition channels show higher drop-off? Expectation mismatch.
- Scroll depth — Are users seeing the CTA? Check heatmap scroll data.
- Click patterns — Are users clicking non-interactive elements? Confusing UI.
- Form fields — For forms, which field has the highest abandonment rate?
Step 5: Generate Test Hypotheses
For each identified issue, create a hypothesis using the ICE framework:
Format:
IF we [change], THEN [metric] will [improve/increase/decrease]
BECAUSE [evidence from data]
Impact: [1-10] — How much will this move the needle?
Confidence: [1-10] — How sure are we this will work?
Ease: [1-10] — How quickly can we implement and test this?
ICE Score: [average of three]
Step 6: Prioritize and Recommend
Rank all hypotheses by ICE score and present:
- Top 3 Quick Wins — High ease, decent impact (ship this week)
- Top 3 High-Impact Tests — High impact, may require more effort (sprint backlog)
- Strategic Bets — Lower confidence but potentially transformative (quarterly roadmap)
For each recommendation, include:
- The specific page or funnel step
- What to change and why
- Expected impact on conversion rate
- Suggested test duration based on traffic volume
Analysis Frameworks
The RICE Prioritization (for larger teams)
- Reach: How many users per month does this affect?
- Impact: Expected lift (minimal / low / medium / high / massive)
- Confidence: Data quality supporting the hypothesis (low / medium / high)
- Effort: Engineering/design time (days)
Score = (Reach x Impact x Confidence) / Effort
Segment Analysis Checklist
Always break down conversion data by:
- Device type (mobile / desktop / tablet)
- Traffic source (organic / paid / direct / referral / social)
- Geography (if international)
- New vs returning visitors
- Entry page
Common Funnel Archetypes
| Funnel Type | Key Metrics | Common Leaks |
|---|
| SaaS Free Trial | Visit > Signup > Activate > Convert | Signup form friction, activation failure |
| E-commerce | PDP > Cart > Checkout > Purchase | Cart abandonment, checkout form |
| Lead Gen | Landing > Form > Thank You | Form length, trust signals |
| Content > Conversion | Blog > CTA > Signup | CTA visibility, relevance match |
Output Format
Present findings as:
- Funnel Overview — Visual step-by-step with volumes and rates
- Key Finding — The single biggest insight in one sentence
- Drop-off Analysis — Ranked list of leaks with absolute numbers
- Root Cause Diagnosis — What is causing each major leak
- Prioritized Test Roadmap — ICE-scored hypotheses ready for execution
- Expected Impact — If top 3 tests succeed, projected conversion lift
Related Skills
- ab-test-generator — Take the hypotheses from this skill and generate actual test configurations
- funnel-reporter — Pull comprehensive funnel reports with revenue data
- page-cro — Deep-dive into a specific page's conversion issues
- copywriting — Generate optimized copy for test variants