# AI Sales Playbook — Value-Based Pricing & Deal Upselling ## Preamble (runs on skill start) ```bash # 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`. --- Framework for value-based pricing that moves deals from $10K/mo → $40-100K/mo. Pre-call briefings, tiered package generation, post-call analysis, and a pattern library for training sales teams on proven pricing techniques. ## When to Use Use this skill when: - Preparing for a sales call and need competitive data to anchor on value - Building tiered pricing proposals for prospects at different deal sizes - Analyzing sales call transcripts to score against the value-based pricing framework - Training sales reps on proven pricing patterns and objection handling - Upselling existing deals by identifying missed value levers ## Tools ### Pre-Call Preparation | Script | Purpose | Key Command | |--------|---------|-------------| | `value_pricing_briefing.py` | Generate pre-call briefing with competitive data, value calcs, and conversation hooks | `python3 value_pricing_briefing.py --domain acme.com --competitors "comp1.com,comp2.com"` | | `value_pricing_packager.py` | Generate tiered S/M/L + performance pricing packages | `python3 value_pricing_packager.py --target-monthly 80000 --services "seo,cro,content,paid"` | ### Post-Call Analysis | Script | Purpose | Key Command | |--------|---------|-------------| | `call_analyzer.py` | Score a call transcript against the value-based pricing framework | `python3 call_analyzer.py --transcript call.txt` | | `pricing_pattern_library.py` | Reference library of 10 proven pricing patterns + training mode | `python3 pricing_pattern_library.py --list` | ## Configuration All scripts use environment variables for API keys: ### Optional Environment Variables - `AHREFS_API_KEY` — Ahrefs API key (Briefing Generator, optional — uses stubs without it) - `SEMRUSH_API_KEY` — SEMrush API key (Briefing Generator, optional — uses stubs without it) - `ANTHROPIC_API_KEY` — Anthropic API key (Call Analyzer, Pattern Library scenario mode) - `OPENAI_API_KEY` — OpenAI API key (alternative to Anthropic for LLM features) Scripts work without API keys using built-in stubs and sample data for testing. ## Key Concepts ### The Value-Based Pricing Framework 1. **Lead with data, not your pitch** — Show the prospect their competitive gaps before discussing services 2. **Anchor high** — Present the premium tier first so the target tier feels reasonable 3. **Tie price to value** — Every dollar of investment maps to projected ROI 4. **Use competitive triggers** — Competitor rankings activate urgency without being pushy 5. **Present tiered options** — 3-4 tiers with clear tradeoffs, always including a performance option ### Pricing Framework Score (0-100) The call analyzer scores calls against these criteria: - Showed data before pitching (20 pts) - Presented tiered options (20 pts) - Anchored high first (15 pts) - Tied price to value/ROI (15 pts) - Used competitive triggers (15 pts) - Got prospect to state their own pain (15 pts) ## Dependencies - Python 3.9+ - `requests` (for API integrations) - No other external dependencies