Funnel Intelligence Agent
A 4-agent pipeline: a Collector pulls per-channel funnel data, an Analyzer flags statistical bottlenecks, a Hypothesis Generator turns each into A/B tests, and a Report Builder assembles the roadmap.
About this case study
Problem: a single blended conversion funnel hides where campaigns actually break. A channel with weak signup conversion could have a mobile UX bug, a targeting problem, or nothing wrong at all — and telling those apart by eyeballing one dashboard stops working past two or three traffic sources. Approach: a 4-agent pipeline positioned as "a junior growth analyst who never sleeps." A Collector pulls funnel data per traffic channel, an Analyzer flags statistical bottlenecks (z-score vs. the cross-channel baseline for that step, not a fixed percentage threshold — channels genuinely behave differently), a Hypothesis Generator turns each bottleneck into 2-3 concrete A/B tests, and a Report Builder assembles the prioritized roadmap. Result: this demo runs against a synthetic SaaS funnel with two deliberately planted issues, so there's something real for the Analyzer to find. It correctly surfaces the compounding paid_social mobile-friction problem among the top bottlenecks and proposes matching, testable hypotheses — live, on the page.
Methodology Note
Funnel Intelligence Agent is the first built module of a broader growth-analytics architecture: today it diagnoses funnels, next in line are customer lifecycle and channel-level revenue attribution, on the same 4-agent pattern (Collector → Analyzer → Hypothesis Generator → Report Builder). Built and validated on a controlled synthetic scenario — I'll run the same thing on your real data on a call.
← See where this diagnostic approach came from: the SolidVisa case study
Example run
SyntheticSaaS Demo — 2026-06-20 to 2026-07-20
Funnel analysis for SyntheticSaaS Demo (2026-06-20 to 2026-07-20) across 7 traffic channels: 6 bottleneck(s) identified. Top issues: paid_social/landing_view (3.0% vs cross-channel baseline); paid_social/signup (15.2% vs cross-channel baseline). Generated 9 A/B hypotheses across 3 channel/step combination(s). Recommend starting with quick wins before strategic bets.
Funnel (aggregate across all channels)
Channel comparison
| Channel | Volume | Overall conversion | vs. avg |
|---|---|---|---|
| direct | 12,000 | 4.27% | ▲ 3.35% |
| referral | 8,000 | 1.23% | ▲ 0.31% |
| 15,000 | 0.36% | ▼ -0.56% | |
| organic_search | 40,000 | 0.29% | ▼ -0.62% |
| paid_search | 60,000 | 0.16% | ▼ -0.76% |
| organic_social | 25,000 | 0.08% | ▼ -0.84% |
| paid_social | 90,000 | 0.03% | ▼ -0.89% |
Top bottlenecks & A/B roadmap (6 total found, top 3 prioritized)
[paid_social] Drop-off at 'landing_view' is 7.0% (1.5 standard deviations above the cross-channel mean of 4.0% for this step).
Control: Current landing page with generic hero headline/imagery not directly tied to specific paid social ad creative/copy
Variant: Dynamic landing page hero that mirrors the exact value proposition, imagery, and offer language used in each paid social ad set
Primary: landing_view to next-step conversion rate · Guardrail: average session duration on landing page · n≈4,500/variant
Control: Current landing page layout with standard image-heavy hero section and multiple CTAs
Variant: Lightweight, fast-loading above-the-fold section with single clear CTA optimized for mobile paid social referral traffic
Primary: landing_view bounce rate · Guardrail: page load time (Core Web Vitals - LCP) · n≈5,000/variant
Control: Single generic landing page served to all paid social traffic regardless of ad audience segment
Variant: Segmented landing pages tailored to top 2-3 paid social audience/interest segments with matched copy and offer framing
Primary: landing_view to next-step conversion rate by segment · Guardrail: overall paid social CPA · n≈4,000/variant
[paid_social] Drop-off at 'signup' is 87.8% (1.7 standard deviations above the cross-channel mean of 72.6% for this step).
Control: Current signup form requires full name, email, password, and phone number before account creation
Variant: Reduced signup form to email + password only, with name/phone collected post-signup via progressive profiling
Primary: signup completion rate (paid_social segment) · Guardrail: downstream activation rate (% of signups completing first key action) · n≈2,500/variant
Control: Signup only via manual email/password form
Variant: Add 'Continue with Google/Facebook/Apple' one-click signup options above the manual form
Primary: signup completion rate (paid_social segment) · Guardrail: email deliverability/verification rate (to ensure SSO signups remain reachable) · n≈3,000/variant
Control: Generic signup page identical across all traffic sources
Variant: Signup page variant for paid_social traffic showing ad-matched headline, social proof badges, and reduced-step visual progress indicator
Primary: signup completion rate (paid_social segment) · Guardrail: overall signup page bounce rate · n≈2,800/variant
[paid_social] Drop-off at 'activation' is 49.9% (1.6 standard deviations above the cross-channel mean of 39.9% for this step).
Control: Users land on activation step and must self-discover how to complete setup with no contextual guidance
Variant: Add an interactive checklist/tooltip walkthrough that guides users through the single highest-value action immediately upon entry
Primary: activation completion rate · Guardrail: time-to-activation (should not increase median time) · n≈2,400/variant
Control: Activation step (e.g., signup completion, key setup task) is presented immediately after channel landing
Variant: Insert a lightweight value-preview or sample interaction before prompting the activation step, delaying the ask by one screen
Primary: activation completion rate · Guardrail: overall funnel completion rate (ensure no downstream cannibalization) · n≈2,600/variant
Control: Current activation step requires multiple fields/actions or clicks to complete
Variant: Strip activation to a single required field/action, deferring optional inputs to post-activation onboarding
Primary: activation completion rate · Guardrail: data quality/completeness of user profile post-activation · n≈2,200/variant
Quick wins
- Ad-to-Landing Message Match (paid_social / landing_view)
- Simplified Above-the-Fold Load for Mobile Paid Social Traffic (paid_social / landing_view)
- Simplify Signup Form Fields for Paid Social Traffic (paid_social / signup)
- Add Social Login (SSO) Option for Paid Social Traffic (paid_social / signup)
- Channel-Matched Signup Page Messaging & Trust Signals (paid_social / signup)
- Reduce Time-to-Value with Guided First Action (paid_social / activation)
- Delay Activation Ask Until Value Demonstrated (paid_social / activation)
- Simplify Activation Step Form/Action Complexity (paid_social / activation)
Strategic bets
- Audience-Specific Landing Page Variants (paid_social / landing_view)
Live access is available on request — I personally review each one.