AI Revenue Intelligence

Preamble (runs on skill start)

# Version check (silent if up to date)
python3 telemetry/version_check.py 2>/dev/null || true

# Telemetry opt-in (first run only, then remembers your choice)
python3 telemetry/telemetry_init.py 2>/dev/null || true

Privacy: This skill logs usage locally to ~/.ai-marketing-skills/analytics/. Remote telemetry is opt-in only. No code, file paths, or repo content is ever collected. See telemetry/README.md.

AI-powered revenue intelligence: sales call insight extraction, content-to-revenue attribution, and multi-source client reporting.

When to Use

• User wants to extract insights from Gong sales call transcripts
• User needs to identify objections, buying signals, or competitive mentions in calls
• User wants to prove content ROI by mapping content to closed deals
• User needs revenue attribution across first-touch and multi-touch models
• User wants to generate a unified client report from GA4 + HubSpot + Ahrefs + Gong
• User asks about content gaps in the buyer journey
• User needs anomaly detection across marketing metrics

Tools

Gong-to-Insight Pipeline (gong_insight_pipeline.py)

Extracts structured intelligence from sales call transcripts. Works with Gong API or plain transcript files.

# Analyze a single transcript file
python gong_insight_pipeline.py --file transcript.txt

# Analyze multiple transcript files
python gong_insight_pipeline.py --dir ./transcripts/

# Pull recent calls from Gong API (last 7 days)
python gong_insight_pipeline.py --gong --days 7

# Pull specific call by ID
python gong_insight_pipeline.py --gong --call-id abc123

# Output as JSON file
python gong_insight_pipeline.py --file transcript.txt --output insights.json

# Generate content topics from recurring objections
python gong_insight_pipeline.py --dir ./transcripts/ --content-topics

# Generate follow-up suggestions for outbound sequences
python gong_insight_pipeline.py --file transcript.txt --follow-ups

What it extracts:

• Objections (categorized: pricing, timing, competition, authority, need)
• Buying signals (budget confirmed, timeline mentioned, decision maker engaged, champion identified)
• Competitive mentions (who was mentioned, context: positive/negative/neutral)
• Pricing discussions (anchors, pushback, willingness indicators)
• Content topic suggestions from recurring objection patterns
• Personalized follow-up drafts based on call context