Demo Performance Monitor

This drill creates an always-on monitoring system for the discovery-based demo pipeline. It tracks the full funnel from discovery call through demo to deal outcome, detects when conversion rates degrade, and surfaces which demo structures and pain-to-feature mappings produce the best outcomes.

Input

• PostHog events flowing from the demo-prep-automation drill (demo_prep_generated, demo_completed)
• Attio deal records with BANT scores and demo outcomes
• Fireflies transcripts for demo calls
• At least 2 weeks of baseline demo data (minimum 10 demos)

Steps

1. Define the demo conversion funnel

Using posthog-custom-events, ensure these events are captured:

| Event | Trigger | Key Properties | |-------|---------|----------------| | discovery_call_completed | Discovery call transcript processed | deal_id, bant_composite, pains_identified | | demo_prep_generated | Demo prep doc created | deal_id, pains_mapped, features_shown | | demo_scheduled | Cal.com booking confirmed | deal_id, days_since_discovery, attendee_count | | demo_completed | Demo call ended and logged | deal_id, outcome, pains_addressed, questions_asked, duration_minutes | | recap_video_sent | Loom recap shared | deal_id, video_length_seconds | | recap_video_viewed | Prospect watched recap | deal_id, watch_percentage, cta_clicked | | next_step_committed | Prospect agreed to next meeting | deal_id, next_step_type | | proposal_requested | Prospect requested pricing/proposal | deal_id, deal_value | | deal_closed_won | Deal closed | deal_id, deal_value, days_in_pipeline |

2. Build the funnel in PostHog

Using posthog-funnels, create a saved funnel:

discovery_call_completed -> demo_scheduled -> demo_completed -> next_step_committed -> proposal_requested -> deal_closed_won

Break down by:

• bant_composite buckets (0-40, 40-70, 70-100) -- which BANT scores predict demo success
• pains_addressed count -- does covering more pains increase conversion
• outcome -- which demo outcomes lead to closed deals
• days_since_discovery -- does demo timing affect conversion

Save as: "Discovery-Based Demo — Full Funnel"

3. Build the demo effectiveness dashboard

Using posthog-dashboards, create a dashboard with these panels:

1. Funnel conversion rates: discovery -> demo -> next step -> proposal -> closed won
2. Demo-to-nextstep trend: weekly line chart of conversion rate
3. Pain coverage vs outcome: scatter plot of pains_addressed vs next_step_committed rate
4. BANT score vs demo success: bar chart showing conversion by BANT bucket
5. Recap video engagement: average watch percentage and correlation with next step
6. Time-to-demo: histogram of days between discovery and demo, overlaid with conversion rate
7. Demo duration vs outcome: are longer demos better or worse
8. Weekly demo volume: count of demos completed per week

4. Build n8n monitoring workflows

Using n8n-scheduling, create a daily cron workflow:

1. Query PostHog for the last 7 days of funnel data
2. Compute key conversion rates:
   • Discovery-to-demo rate
   • Demo-to-nextstep rate
   • Demo-to-proposal rate
   • Overall discovery-to-closed-won rate
3. Compare to baseline using posthog-anomaly-detection logic:
   • Normal: within +/- 15% of 4-week rolling average
   • Warning: 15-30% below average for 3+ consecutive days
   • Critical: >30% below average for 2+ consecutive days
4. For Warning/Critical: send Slack alert with degradation details and probable cause

Using n8n-triggers, create event-triggered workflows:

• On demo_completed where outcome = "no_interest": flag for demo quality review
• On recap_video_viewed where watch_percentage > 80% and no next_step_committed within 48 hours: trigger follow-up reminder

5. Build the pain-to-feature effectiveness report

Create a weekly n8n workflow that:

1. Pulls all demo_completed events from the last 30 days
2. Groups by features shown and pains addressed
3. Calculates conversion rate for each pain-to-feature combination
4. Identifies:
   • Top 3 pain-feature combos that predict closed deals (prioritize showing these)
   • Bottom 3 pain-feature combos that never convert (stop leading with these)
   • Features shown but never connected to a pain (remove from demos)
5. Generates a ranking report and stores it in Attio as a campaign note

6. Track demo quality signals from transcripts

After each demo, use Fireflies transcript + Claude to extract quality signals:

• Did the rep connect features back to specific pains mentioned in discovery ("You said X, this solves X")
• How many questions did the prospect ask (engagement signal)
• Did the prospect verbally commit to a next step
• Were there objections, and how were they handled

Score each demo 1-5 on: pain coverage, feature relevance, engagement, and close attempt. Correlate demo quality scores with deal outcomes over time.

Output

• Real-time demo conversion funnel with breakdown by BANT score, pain coverage, and timing
• Daily automated monitoring with anomaly alerts
• Weekly pain-to-feature effectiveness ranking
• Demo quality scoring from transcript analysis
• Historical trend tracking for demo-to-deal conversion

Triggers

• Daily monitoring: runs every day at 9 AM via n8n cron
• Weekly effectiveness report: runs every Monday at 8 AM via n8n cron
• Event-triggered: fires on every demo_completed event for quality scoring