Funnel Analytics
Objective
Identify exactly where Hedge Edge is losing potential revenue in the user journey and quantify the dollar impact of fixing each bottleneck. The funnel is not a static diagram it is a living, measured system where every stage has a conversion rate, a benchmark, a trend, and a recommended action. The goal is to make funnel optimization the primary growth lever by turning qualitative hunches into quantitative priorities.
When to Use This Skill
- •Weekly funnel review: Standard weekly analysis of full-funnel conversion rates and WoW changes
- •Campaign launch: When Marketing Agent launches a new campaign and needs baseline + tracking setup
- •Conversion drop detected: When KPI Dashboards flag a conversion rate anomaly at any funnel stage
- •Channel comparison: When evaluating which acquisition channel (YouTube, Discord, paid, IB) has the best funnel performance
- •Landing page changes: When Developer Agent or Content Creator Agent pushes landing page updates and needs impact measurement
- •Growth planning: When Business Strategist Agent needs funnel data to model growth scenarios
- •New funnel stage added: When a new touchpoint is introduced (e.g., webinar funnel, MT4 launch)
Input Specification
Required Inputs
| Field | Source | Description |
|---|---|---|
| date_range | Request parameter | Analysis period with comparison period |
| ga4_traffic_data | GA4 API | Sessions, users, source/medium, landing pages, UTM parameters, conversion events |
| ercel_page_data | Vercel Analytics | Page views, unique visitors, bounce rate by page, referrer data |
| supabase_signups | Supabase uth.users | Signup events with created_at, source, utm_source, utm_medium, utm_campaign |
| supabase_trials | Supabase subscriptions | Trial start events with user_id, plan, started_at |
| creem_conversions | Creem.io API | Trial-to-paid conversions, plan selections, payment timestamps |
| creem_retention | Creem.io API | Renewal events, cancellation events, upgrade/downgrade events |
Optional Inputs
| Field | Source | Description |
|---|---|---|
| discord_signups | Discord Bot + Supabase join | Users who joined Discord before/after signup (community influence measurement) |
| email_events | n8n/email platform | Email sends, opens, clicks by campaign (for email funnel stages) |
| ib_activations | Google Sheets CRM | IB broker activation events mapped to user journey |
| support_tickets | Supabase/Google Sheets | Support interactions mapped to funnel stage (pre-sale vs. post-sale) |
| segment_filter | Request parameter | Filter by channel, plan, prop firm, geography, device |
Step-by-Step Process
Step 1: Define the Funnel Stages
Map the Hedge Edge funnel with measurable events at each transition:
` CONTENT (Awareness) Event: Video view, blog visit, social impression Metric: Impressions, watch time, profile visits Source: YouTube Analytics, social platforms
ATTENTION (Interest) Event: Click to landing page, ad click, email open Metric: CTR, CPC, engagement rate, open rate Source: GA4, Vercel, email platform
CAPTURE (Lead) Event: Landing page signup, lead magnet download, Discord join Metric: Lead capture rate, leads per channel Source: Vercel + Supabase (signup event)
SALES (Conversion) Event: Trial start, trial-to-paid, plan selection Metric: Trial start rate, close rate, avg plan value Source: Supabase + Creem.io
DELIVERY (Activation) Event: First hedge executed, MT5 EA connected, 3+ accounts added Metric: Time-to-first-value, activation rate, support tickets Source: Supabase usage logs
RETENTION (Loyalty) Event: 30-day renewal, 60-day renewal, upgrade, referral sent Metric: 30/60/90-day retention, NRR, referral rate Source: Creem.io + Supabase
EXPANSION (Advocacy) Event: Referral conversion, IB activation, plan upgrade, review posted Metric: Viral coefficient, IB activation rate, expansion revenue Source: Supabase + Google Sheets CRM `
Step 2: Data Collection & Event Mapping
- •Pull GA4 session data with UTM parameters to attribute traffic to channels
- •Pull Vercel Analytics for landing page behavior (pageviews, scroll depth, CTA clicks)
- •Query Supabase for signup events, matching utm_source to GA4 sessions where possible
- •Pull Creem.io for trial starts, conversions, and renewals
- •Query Supabase usage logs for activation events (first hedge, EA connection, account additions)
- •Map each user to their funnel journey: assign timestamps for each stage transition
- •Handle multi-session attribution: if a user visits 3 times before signing up, capture all touchpoints
Step 3: Conversion Rate Calculation
For each stage transition, calculate:
- •Absolute conversion rate: Users who completed stage N+1 / Users who entered stage N
- •Cumulative conversion rate: Users at stage N / Total users at top of funnel
- •Time-to-convert: Median and P90 time between stages (e.g., signup to trial start: median 0.5 days, P90 3 days)
- •Drop-off count: Absolute number of users lost at each stage
- •Revenue impact of drop-off: Lost users average LTV of converted users = revenue left on table
Example calculation for Hedge Edge: ` Landing Page Visitors: 10,000/mo Signups: 800 (8.0% capture rate) Trial Starts: 560 (70% of signups) Trial-to-Paid: 168 (30% close rate) 30-Day Retained: 135 (80% retention) 90-Day Retained: 101 (60% of original paid) IB Activated: 42 (25% of paid users)
Revenue per converted user: ARPU 8 mo avg tenure = LTV
- •IB value: 25% /mo IB commission 8 mo = IB LTV contribution Blended LTV: ~
Revenue impact of +1% signup rate improvement: 100 additional signups 70% trial 30% convert LTV = ,862/year `
Step 4: Channel-Specific Funnel Analysis
Build separate funnels for each acquisition channel:
- •YouTube Organic: Video view Profile visit Landing page click Signup Trial Paid
- •Key metric: Content-to-signup rate, video-assisted conversion rate
- •Discord Community: Discord join Engagement (5+ messages) Landing page visit Signup Trial Paid
- •Key metric: Community-influenced conversion rate, time-in-community before conversion
- •Paid Ads: Ad impression Click Landing page Signup Trial Paid
- •Key metric: CAC (fully loaded), ROAS, payback period
- •IB Partner Referral: Partner link click Broker signup Hedge Edge signup Trial Paid
- •Key metric: Partner-attributed revenue, co-registration rate
- •Organic Search: Search impression Click Landing page Signup Trial Paid
- •Key metric: Keyword conversion rates, SEO ROI
- •Email: Email received Opened Clicked Landing page Signup/Trial/Upgrade
- •Key metric: Email-attributed conversions, nurture sequence effectiveness
- •Word of Mouth/Referral: Referral link shared Click Signup Trial Paid
- •Key metric: Viral coefficient, referral conversion premium vs. organic
Step 5: Drop-Off Analysis & Bottleneck Identification
- •Rank all stage transitions by drop-off rate (worst conversion % first)
- •For the top 3 bottlenecks, investigate:
- •Who drops off: Segment by channel, device, plan interest, geography
- •When they drop off: Time-based patterns (day of week, time of day, days since previous stage)
- •Where they drop off: Specific pages, form fields, onboarding steps
- •Behavioral signals: What did drop-offs do differently than converters? (e.g., watched demo video vs. didn't, joined Discord vs. didn't)
- •Calculate the revenue impact of improving each bottleneck by 10%, 25%, 50%
- •Rank bottlenecks by: Revenue Impact Confidence of Improvement Implementation Ease
Step 6: Funnel Velocity Analysis
- •Calculate time-to-convert at each stage (median, P25, P75, P90)
- •Identify slow stages where users stall (e.g., signup-to-trial >3 days = risk of drop-off)
- •Correlate speed with conversion: do faster-moving users have higher LTV?
- •Identify "fast path" users (signup to paid in <24 hours) and analyze what they have in common
- •Set velocity benchmarks and flag users who are falling behind (trigger nurture automation)
Step 7: Output Generation
- •Build funnel visualization with conversion rates at each stage (Sankey-style data for rendering)
- •Write stage-by-stage data to Google Sheets with conditional formatting
- •Generate Notion report with:
- •Funnel diagram with current rates and MoM changes
- •Top 3 bottlenecks with revenue impact quantification
- •Channel comparison table
- •Velocity analysis with benchmark compliance
- •Recommended actions with ICE scores
- •If a conversion rate drops >15% WoW, trigger n8n alert
Output Specification
Funnel Report Structure
`
Funnel Analytics Report [Date Range]
Executive Summary
- •Total funnel throughput: [X] visitors [Y] paid users ([Z]% end-to-end)
- •MoM change in end-to-end conversion: [+/- %]
- •Biggest bottleneck: [Stage] at [X]% conversion (target: [Y]%)
- •Estimated revenue impact of fixing top bottleneck: $[amount]/month
Stage-by-Stage Breakdown
| Stage | Volume | Conversion Rate | WoW Δ | MoM Δ | Target | Status |
|---|---|---|---|---|---|---|
| Landing Page Visitors | 10,000 | +5% | +12% | |||
| Signups | 800 | 8.0% | -0.5% | +1.2% | 8% | |
| Trial Starts | 560 | 70.0% | +2% | +5% | 65% | |
| Trial-to-Paid | 168 | 30.0% | -3% | -1% | 35% | |
| 30-Day Retained | 135 | 80.4% | +1% | 0% | 80% | |
| IB Activated | 42 | 25.0% | +4% | +8% | 30% |
Channel Comparison
| Channel | Visitors | End-to-End CVR | CAC | LTV | CAC:LTV | Payback |
|---|---|---|---|---|---|---|
| YouTube Organic | 4,200 | 2.1% | 1:55 | 0.4 mo | ||
| Discord | 1,800 | 3.5% | 1:170 | 0.2 mo | ||
| Paid (Google) | 2,500 | 1.2% | 1:9 | 3.2 mo | ||
| Organic Search | 1,200 | 1.8% | 1:80 | 0.5 mo | ||
| Referral | 300 | 5.2% | 0 mo |
Bottleneck Analysis
Bottleneck 1: Trial-to-Paid (30% vs. 35% target)
- •Revenue at stake: $[X]/month
- •Root cause hypothesis: [analysis]
- •Segment most affected: [detail]
- •Recommended action: [specific action]
- •ICE Score: [Impact Confidence Ease]
Funnel Velocity
| Transition | Median Time | P90 Time | Benchmark | Status |
|---|---|---|---|---|
| Visit Signup | 2.3 sessions | 7 sessions | 3 sessions | |
| Signup Trial | 0.5 days | 3.2 days | 1 day | |
| Trial Paid | 6.8 days | 13 days | 7 days |
Recommended Actions (ICE-ranked)
- •[Action] Impact: [H/M/L], Confidence: [H/M/L], Ease: [H/M/L] Score: [X/30]
- •... `
API & Platform Requirements
| Platform | Endpoint/Method | Auth | Purpose |
|---|---|---|---|
| GA4 | Data API v1 | ||
| unReport | GA4_MEASUREMENT_ID + GA4_API_SECRET | Traffic source, UTM attribution, session data | |
| Vercel Analytics | /v1/analytics | VERCEL_ANALYTICS_TOKEN | Landing page behavior, CTA click tracking |
| Supabase | /rest/v1/users, /rest/v1/events | SUPABASE_URL + SUPABASE_KEY | Signup events, activation events, usage logs |
| Creem.io | /v1/subscriptions, /v1/events | CREEM_API_KEY | Trial, conversion, renewal, churn events |
| Google Sheets | Sheets API v4 | GOOGLE_SHEETS_API_KEY + service account | Dashboard output, CRM data for IB funnel |
| Notion | /v1/pages | NOTION_API_KEY | Report storage and distribution |
| Discord Bot | /guilds/{id}/members, /channels/{id}/messages | DISCORD_BOT_TOKEN | Community engagement funnel data |
| n8n | POST to N8N_WEBHOOK_URL | Webhook URL | Alert triggers for conversion anomalies |
Quality Checks
- • Full funnel coverage: Every defined stage has a measured conversion rate with sample size shown
- • Attribution integrity: >90% of signups have a tracked source (UTM or referrer). Unattributed <10%.
- • No double-counting: Each user counted once per stage, even with multiple sessions
- • Conversion windows: Time windows are defined and consistent (e.g., 14-day trial window, 30-day attribution window)
- • Statistical validity: Conversion rate changes flagged only when sample size >100 and change is >2 percentage points or statistically significant at p<0.05
- • Channel isolation: Channel-specific funnels do not overlap (multi-touch handled in Attribution Modeling skill, not here)
- • Revenue impact calculated: Every bottleneck has a dollar-value impact estimate, not just a percentage
- • Velocity benchmarks set: Each stage transition has a target time-to-convert with actual vs. target comparison
- • Comparison context: Every metric shows WoW and MoM change plus target benchmark
- • Actionable output: Report includes at least 3 ICE-scored recommended actions tied to specific funnel stages