Cro Optimizer: Install, Source and Security | FunnelSlayer

Cro Optimizer

Published by humblytics in ai-marketing-skills

No known issues11 installs

What this skill does

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.

Add Cro Optimizer to your agent

Review the source and files first. When you are ready, copy the prompt instruction or use the CLI command supported by your environment.

Install with a prompt

Paste this into a compatible coding agent:

add this skill "cro-optimizer" from https://github.com/humblytics/ai-marketing-skills

Install with the CLI

Run this command in a controlled environment after reviewing the repository:

npx skills add https://github.com/humblytics/ai-marketing-skills --skill cro-optimizer

Skill instructions

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):

  1. cp .env.example .env at the repo root and fill in HUMBLYTICS_API_KEY
  2. source .env in your shell before running the agent (or use direnv, or add the exports to your shell profile)
  3. Get the key from Humblytics Dashboard > Settings > API
  4. 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

  1. Confirm the property ID — Ask the user which Humblytics property to analyze
  2. Identify the funnel — Clarify which conversion flow to examine (e.g., homepage > pricing > signup > onboarding)
  3. Check for context — Look for existing project docs, AGENTS.md, or product briefs that describe the business model, target audience, and current conversion goals
  4. Establish the time range — Default to last 30 days; ask if the user wants a different window
  5. 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:

  1. Calculate the absolute number of users lost at each step
  2. Rank steps by absolute drop-off (not percentage)
  3. 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:

  1. Top 3 Quick Wins — High ease, decent impact (ship this week)
  2. Top 3 High-Impact Tests — High impact, may require more effort (sprint backlog)
  3. 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 TypeKey MetricsCommon Leaks
SaaS Free TrialVisit > Signup > Activate > ConvertSignup form friction, activation failure
E-commercePDP > Cart > Checkout > PurchaseCart abandonment, checkout form
Lead GenLanding > Form > Thank YouForm length, trust signals
Content > ConversionBlog > CTA > SignupCTA visibility, relevance match

Output Format

Present findings as:

  1. Funnel Overview — Visual step-by-step with volumes and rates
  2. Key Finding — The single biggest insight in one sentence
  3. Drop-off Analysis — Ranked list of leaks with absolute numbers
  4. Root Cause Diagnosis — What is causing each major leak
  5. Prioritized Test Roadmap — ICE-scored hypotheses ready for execution
  6. 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

Files included

  • SKILL.md

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