LEAD GENERATION — PIPELINE OS (OPERATIONAL)
Built as a no-fluff execution skill for revenue-aligned demand generation.
Structure: Core lead generation fundamentals first. AI-specific automation in clearly labeled "Optional: AI / Automation" sections.
Core: Lead Type Definitions
Clear definitions prevent Sales/Marketing friction. Align on these before building pipeline.
| Lead Type | Definition | Qualification Criteria | Owner |
|---|---|---|---|
| Lead | Any identified contact | Has email/phone, some interest signal | Marketing |
| MQL (Marketing Qualified Lead) | Fits ICP + engaged with marketing | Firmographic fit + behavior threshold | Marketing |
| SQL (Sales Qualified Lead) | Ready for sales conversation | MQL + explicit buying signal or demo request | Sales |
| PQL (Product Qualified Lead) | Used product, shows upgrade potential | Trial/freemium + usage threshold | Product + Sales |
| SAL (Sales Accepted Lead) | SQL accepted by sales rep | Sales confirms qualification after first contact | Sales |
What “Good” Looks Like (Operational)
Set targets from your own baseline, then improve stage-by-stage:
- Sales acceptance rate (SQL → SAL)
- Speed-to-lead (time to first touch)
- Stage conversion rates and time-in-stage
- Pipeline created per channel (not leads)
Core: Funnel Design Framework
| Stage | User State | Content/Action | Goal |
|---|---|---|---|
| Awareness | Problem-aware | Blog, social, SEO, ads | Capture attention |
| Interest | Solution-curious | Guides, webinars, comparisons | Capture contact info |
| Consideration | Evaluating options | Case studies, demos, free tools | Convert to MQL |
| Decision | Ready to buy | Pricing, proposals, trials | Convert to SQL → Opportunity |
| Activation | New customer | Onboarding, training, quick wins | Reduce churn, increase expansion |
Funnel Diagnostic Questions
- Where is the biggest drop-off? (Measure stage-to-stage conversion)
- What's your time-in-stage for each? (Long times = friction)
- Are leads skipping stages? (May indicate misalignment)
- What percentage of MQLs get accepted by Sales? (Low = quality issue)
For full funnel setup including MQL/SQL criteria and SLAs, use lead-funnel-definition.md.
Core: Gating Strategy
Not all content should be gated. Use this decision framework:
| Content Type | Gate? | Why |
|---|---|---|
| Blog posts, how-to guides | No | Build SEO, trust, awareness |
| Comparison guides, buyers guides | Light gate (email only) | High intent, worth capturing |
| Industry reports, original research | Gate | High value, worth exchange |
| ROI calculators, assessments | Gate | Strong buying signals |
| Product demos, pricing | Gate | Direct sales intent |
| Case studies | Optional | Gate if detailed; ungate if brief |
Do (Gating)
- Ask only for fields you'll use (email + company is often enough)
- Progressive profiling: collect more data over multiple interactions
- A/B test gated vs ungated for the same content
- Honor the value exchange: gated content must deliver real value
Avoid (Gating)
- Gating everything (kills organic discovery)
- Long forms for top-of-funnel content (start with the minimum fields you will use)
- Requiring phone number for early-stage content
- Gating content that's freely available elsewhere
Core: Attribution Fundamentals + Limitations
Attribution Models
| Model | How It Works | Best For | Limitation |
|---|---|---|---|
| First-touch | 100% credit to first interaction | Understanding awareness sources | Ignores nurture journey |
| Last-touch | 100% credit to final touch | Understanding closing sources | Ignores awareness |
| Linear | Equal credit to all touches | Simple multi-touch | Over-credits low-value touches |
| Time-decay | More credit to recent touches | Long sales cycles | Complex to implement |
| Position-based | 40/20/40 to first/middle/last | Balanced view | Still somewhat arbitrary |
What Attribution Cannot Tell You
- Offline influence: Trade shows, word-of-mouth, podcast listens
- Dark social: Slack shares, private LinkedIn DMs, email forwards
- Buying committee dynamics: Multiple stakeholders, different journeys
- True incrementality: Would they have converted anyway?
Do (Attribution)
- Use attribution as directional signal, not absolute truth
- Combine with qualitative data (ask "how did you hear about us?")
- Focus on trends over time, not single-touchpoint credit
- Match attribution model to your sales cycle length
Avoid (Attribution)
- Treating attribution as ground truth
- Cutting channels based solely on last-touch data
- Over-investing in attribution tooling before conversion tracking and decision-making are solid
- Ignoring brand/awareness because it's hard to attribute
Core: Lead Quality vs Volume Tradeoffs
The 2025 reality: precision > volume. Longer sales cycles and larger buying committees mean quality matters more than ever.
| Strategy | Quality | Volume | Best When |
|---|---|---|---|
| Volume play | Lower | Higher | New market, testing channels, brand building |
| Precision play | Higher | Lower | Known ICP, limited SDR capacity, high ACV |
| Balanced | Medium | Medium | Most B2B companies |
Quality Signals (Prioritize These)
- ICP firmographic match (industry, size, geo)
- Explicit intent signals (demo request, pricing page, competitor comparison)
- Engagement depth (multiple pages, return visits, long time on site)
- Decision-maker title
Warning Signs (Low Quality)
- High MQL volume but low Sales acceptance rate (materially below baseline)
- Lead-to-opportunity time increasing (pipeline drag)
- High early-stage drop-off in demos/calls
- Leads requesting irrelevant features
Core: Account-Based Sales (ABS)
ABS is often effective in B2B when targeting high-value accounts with complex buying committees.
When to Use ABS
| Criteria | Threshold | Why |
|---|---|---|
| ACV | >$25K | Worth the research investment |
| TAM | <5,000 accounts | Finite, targetable market |
| Buying committee | 3+ stakeholders | Multi-threaded approach needed |
| Sales cycle | >60 days | Time to nurture relationships |
ABS Execution Framework
| Element | Execution | Resource |
|---|---|---|
| Target list | 50-200 named accounts, tiered (Tier 1: 20, Tier 2: 50, Tier 3: 130) | assets/channel-plan-30-60-90.md |
| Account research | Pain points, tech stack, recent news, org chart | 30 min per Tier 1 account |
| Multi-threading | 3-5 contacts per account across roles | Champion + economic buyer + user |
| Custom content | Pain-specific messaging per tier | Tier 1: fully custom; Tier 2: semi-custom |
| Orchestration | Coordinated email + LinkedIn + ads + events | Sequence all channels |
| Measurement | Account engagement score, pipeline per account | Add to assets/lead-scoring-model.md |
Do (ABS)
- Start with Tier 1 (highest value) to prove the motion
- Coordinate Sales + Marketing on account selection and messaging
- Use intent data to prioritize accounts showing buying signals
- Track account-level metrics, not just lead-level
Avoid (ABS)
- Running ABS on >200 accounts (becomes spray-and-pray)
- Treating ABS as "just personalized email" (it's full orchestration)
- Skipping account research (generic outreach defeats the purpose)
- Single-threading accounts (champion leaves = deal dies)
When to Use This Skill
- Pipeline build/rehab: net-new SQL targets, revive stalled funnels, rebalance channel mix
- Outbound motions: cold email/LinkedIn, call scripts, reply handling, objection rebuttals
- Landing/CRO: fix hero/offer/CTA, forms, proof, trust, and post-click routing
- Lead scoring/routing: MQL/SQL thresholds, SDR/AE handoff, SLA design
- Experiment cadence: 30/60/90 test plans, ICE/PIE scoring, stop/scale rules
- Compliance/deliverability: CAN-SPAM/GDPR hygiene, domain warmup, opt-out, DKIM/SPF/DMARC
- Account-based sales (ABS): named account targeting, multi-threaded outreach, account scoring
When NOT to Use This Skill
Use related skills instead for:
- Organic content strategy → marketing-social-media
- SEO for landing pages → marketing-seo-complete
- AI search optimization → marketing-ai-search-optimization
- Product-led growth ownership → product-management
- Paid media buying/optimization → marketing-paid-advertising
Quick Reference
| Task | SOP/Template | Location | When to Use |
|---|---|---|---|
| Define ICP + Offer | ICP & Offer Sprint | See Operational SOPs → ICP & Offer | Before messaging, bidding, or list-building |
| Channel Plan 30/60/90 | Test Plan Grid | See Operational SOPs → Channel Plan | New market motion or quarterly reset |
| Email/LinkedIn Cadence | 5-touch skeleton (CTA-first) | See Operational SOPs → Email/LinkedIn Cadences | Cold/prospecting or nurture |
| Cold Call Script | Talk track w/ discovery | See Operational SOPs → Cold Call Script | Live outbound, event follow-up |
| Landing Fix | Hero/offer/proof/CTA/form checklist | See Operational SOPs → Landing Page Fix | Low CVR or ad-to-page mismatch |
| Lead Scoring & Routing | Points + SLA | See Operational SOPs → Lead Scoring + Routing | SDR/AE handoff, CAC/SQL drift |
| Speed-to-Lead OS | Response + reminders | See Operational SOPs → Speed-to-Lead | Reply/no-show issues, inbox speed |
| Experiment Matrix | ICE/PIE + stop/scale | See Operational SOPs → Experiment Matrix | Weekly prioritization |
| Compliance/Deliverability | Authentication + opt-out | See Operational SOPs → Compliance & Deliverability | Cold email/domain health |
| Email Deliverability 2025 | Bulk sender requirements | assets/email-deliverability-2025.md | Bulk sending (5,000+/day to Gmail), new domains |
| LinkedIn Outreach Safety | Terms-compliant outreach guardrails | assets/linkedin-automation-safety-2025.md | LinkedIn outreach risk reduction |
Decision Tree (Pipeline Triage)
Leads low?
├─ ICP/offer unclear → Run ICP & Offer Sprint → ship 3 hooks (pain/risk/value) → retest
├─ Channel skewed → Add 2nd channel (LI + email OR retargeting) → small-budget test
└─ Volume ok, quality low → Tighten filters + Lead Scoring → reroute + new CTA
Replies low?
├─ Open rate materially below baseline (or bounces/complaints rising) → Fix list quality + auth + subject/hook
└─ Opens ok, replies low → Rewrite CTA (one action), add proof/trigger, shorten to ≤120 words
Bookings low but replies? → Add Speed-to-Lead + 2 follow-ups + calendar drop + friction audit
Traffic ok, CVR low?
├─ Message mismatch → Rewrite hero/CTA to match ad/pain
├─ Proof light → Add 3 proof types (metric case, logo, testimonial)
└─ Form friction → Reduce fields, add multi-step or chat, highlight privacy/trustOperational SOPs (Fast Execution)
ICP & Offer Sprint (90 minutes)
- Pull top 10 wins/losses; extract firmographic + trigger + objection patterns.
- Draft 3 offers: pain-killer, speed/automation, risk reversal. Each with 1 quantified proof + 1 urgency lever.
- Ship 3 hooks for LI/email: pain, risk/cost of inaction, better future. Keep CTA singular (fit check/demo/audit).
Pipeline Health Checklist (Weekly)
- Confirm stage definitions (MQL/SQL/SAL) are unchanged (no silent drift).
- Check SQL → SAL acceptance rate vs baseline; investigate top rejection reasons if down.
- Check speed-to-lead median and p90 vs SLA; fix routing/alerts if breached.
- Review bounce/complaint/unsubscribe trends; pause sends if complaints spike.
- Verify list hygiene: suppress bounces/unsubs/complaints; remove role accounts where required.
- Validate 2 outbound sequences against a control (reply rate and meeting rate), not opens/clicks.
- Review landing page CVR vs baseline by top traffic sources; flag message mismatch.
- Confirm forms capture only fields in use; remove any unused “nice-to-have” fields.
- Audit routing: highest-intent leads go to humans first; bots/automation only assist.
- Confirm attribution model is consistent this week (no reporting changes mid-period).
- Inspect pipeline created per channel (not leads) and reallocate effort to top 2 plays.
- Review show rate and no-show reasons; add reminders or friction fixes if slipping.
- Pull 5 recent wins and 5 losses; update ICP triggers/objections accordingly.
- Align with Sales on next-week target accounts (ABS) and the primary CTA per segment.
- Document one change per channel (email/LI/landing) with a hypothesis and stop/scale rule.
Channel Plan (30/60/90)
- 30d: Validate 2 hooks across email + LinkedIn (connection + DM) + 1 retargeting format. Targets: reply rate + CPL guardrails set from your baseline; protect lead quality (Sales acceptance, SQL rate).
- 60d: Keep winners; add webinar/workshop or partner/referral. Layer nurture (value drops) + remarketing.
- 90d: Scale top 2 plays; add lead scoring + SDR SLAs; kill underperformers that stay below an agreed guardrail after a fair sample. Review CAC, SQL→opp→win.
Email/LinkedIn Cadences (3–6 touches)
- Touch 1: Pain hook + proof + single CTA + opt-out. 70–120 words.
- Touch 2: Mini-case (before/after metric) + CTA to booking link.
- Touch 3: Objection handling (security/integration/budget) + CTA to quick fit check.
- Touch 4–6: Cost-of-inaction math, social proof, light bump. Always include opt-out and compliance footer.
- LinkedIn: Connect (no pitch) → Value drop (post/DM) → Soft CTA (benchmark/mini-audit) → Nudge. Add voice note if high-intent.
Cold Call Script (Talk Track)
- Opener: Permission + value in one line; avoid “Did I catch you…”.
- Discovery: 3 questions (current tool/flow, pain metric, trigger/priority).
- Value hits: Match top pain; cite one proof; propose next step.
- Objections: Acknowledge → brief proof → micro-commit (share stack/book 15m).
- Close: Time-bound CTA (this week) + send calendar while on call.
Landing Page Fix (Offer-First)
- Hero: Problem + outcome + proof; CTA above fold. Mirror ad/sequence language.
- Offer: 3 bullets (value, speed, risk reversal). Add pricing cue if helpful.
- Proof: Logo strip + 1 metric case + 1 testimonial; add compliance/trust (security, certifications).
- Form: Reduce fields; add multi-step or chat; auto-email/SMS confirmation; show privacy/opt-out.
- Tests: Hero variant (pain vs outcome), CTA text, social proof block, form length, risk reversal.
Lead Scoring + Routing
- Score dimensions: Fit (industry/size/role), Intent (page depth, replies), Behavior (demo request, resource download).
- [Inference] Example points: Fit (0–40), Intent (0–40), Behavior (0–20). MQL ≥60; SQL ≥75 with decision role or demo intent.
- Routing: MQL → SDR within 15 minutes; SQL → AE calendar hold. SLA: first touch <15m, 2nd touch <2h, 3rd touch same day.
Speed-to-Lead OS
- Inbox+CRM alerts (email, Slack, mobile). Auto-response with calendar link.
- Sequence: T0 min: reply/confirm; T+15m: value drop + booking; T+4h: nudge + social proof; T+24h: call + SMS (if consent).
- Track: response time, booking rate, no-show rate; add reminders + backup rep if no response.
Experiment Matrix
- Score ideas weekly (ICE/PIE). Run 3–5 tests max; cap blast radius (budget/volume).
- Stop if below an agreed guardrail after minimum sample; scale only after repeatable lift across consecutive checks.
- Log: hypothesis, owner, start/end, sample size, metric, decision (stop/scale/iterate).
Compliance & Deliverability (Operational Checklist)
Goal: Sustain deliverability and protect brand trust while running outbound and nurture.
Spam Rate Thresholds (Critical — 2025 Enforcement)
- Gmail/Yahoo/Microsoft hard ceiling: 0.3% complaint rate
- Recommended target: <0.1% for reliable inbox placement
- Gmail (Nov 2025): Non-compliant senders receive permanent 5xx rejections
- Microsoft (May 2025): Bulk senders without auth are rejected outright on consumer mailboxes
See assets/email-deliverability-2025.md for full enforcement details.
Authentication (Required)
- SPF (RFC 7208): https://datatracker.ietf.org/doc/html/rfc7208
- DKIM (RFC 6376): https://datatracker.ietf.org/doc/html/rfc6376
- DMARC (RFC 7489): https://datatracker.ietf.org/doc/html/rfc7489
Unsubscribe (Required for bulk senders)
- List-Unsubscribe header (RFC 2369): https://datatracker.ietf.org/doc/html/rfc2369
- One-click unsubscribe via List-Unsubscribe-Post (RFC 8058): https://datatracker.ietf.org/doc/html/rfc8058
Compliance Basics
- Follow CAN-SPAM requirements for commercial email (https://www.ftc.gov/business-guidance/references/can-spam-act-compliance-guide-business).
- For GDPR/CASL and other regional rules, align with counsel and your privacy policy (do not improvise).
List Hygiene (Execution)
- Never buy lists; use verified sources and documented consent where required.
- Suppress: hard bounces, unsubscribes, and complaint signals.
- Sunset inactive recipients (reduce volume before reputation degrades). [Inference]
Sending Practices (Execution)
- Keep sending identity stable (From domain/name); avoid frequent domain switching.
- Warm up new domains and ramp volume gradually; stop if complaints spike. [Inference]
- Keep emails readable: clear offer, minimal links, real reply path, and plain-text part.
Metrics & QA
- Primary: reply rate, book rate, show rate, SQLs, opps, win rate, CAC, payback.
- Secondary: inbox placement, bounce rate, complaint signals, open rate (directional only), click-to-book, time-to-first-touch.
- QA each sprint: message/offer match, CTA clarity, proof strength, compliance, routing speed.
Navigation: Sources & Assets
- Operational patterns:
references/operational-patterns.md - Core templates: email (
assets/email-sequence.md), LinkedIn (assets/linkedin-sequence.md), cold call (assets/cold-call-script.md), landing audit (assets/landing-audit-checklist.md), lead scoring (assets/lead-scoring-model.md), channel plan (assets/channel-plan-30-60-90.md), speed-to-lead (assets/speed-to-lead-playbook.md), experiment log (assets/experiment-matrix.md), lead funnel definition (assets/lead-funnel-definition.md) - Additional templates: email deliverability (
assets/email-deliverability-2025.md), LinkedIn outreach safety (assets/linkedin-automation-safety-2025.md) - Optional: AI / Automation: AI personalization (
assets/ai-personalization-playbook.md) - Web sources:
data/sources.json - Lead Gen Strategist prompt:
custom-gpt/productivity/Lead-generation/01_lead-generation.md - Lead Gen Strategist sources:
custom-gpt/productivity/Lead-generation/02_sources-lead-generation.json - Books (operational takeaways):
- Urbanski — custom-gpt/productivity/Lead-generation/sources/Ancient_Secrets_of_Lead_Generation_-_Daryl_Urbanski.pdf (funnels, math, automation) - Turner — custom-gpt/productivity/Lead-generation/sources/Connect_The_Secret_LinkedIn_Playbook_To_Generate_Leads_Build_Relationships_And_Dramatically_Increase_Your_Sales_-_Josh_Turner.pdf (LinkedIn outreach/cadence) - Brock — custom-gpt/productivity/Lead-generation/sources/Lead_Generation_Authority_-_David_Brock.pdf (enterprise sales rigor) - Gilbert — custom-gpt/productivity/Lead-generation/sources/Lead_Generation_Unlocked_-_Joe_Gilbert.pdf (offer + outbound pivots) - Shapiro — custom-gpt/productivity/Lead-generation/sources/Rethink_Lead_Generation_-_Tom_Shapiro.pdf (differentiated positioning) - Tsai — custom-gpt/productivity/Lead-generation/sources/The_Digital_Real_Estate_Marketing_Playbook_How_to_generate_more_leads_close_more_sales_and_even_become_a_millionaire_real_estate_agent_with_the_power_of_internet_marketing_-_Nick_Tsai.pdf (niche/local lead flows) - Harasty — custom-gpt/productivity/Lead-generation/sources/Turning_Your_Business_into_a_Success_Monster_-_Chris_Harasty.pdf (offer stacking, mindset to ops)
Related Skills
- ../marketing-social-media/SKILL.md — Paid/organic social and content systems
- ../product-management/SKILL.md — Positioning and messaging alignment
- ../software-frontend/SKILL.md — Landing implementation and performance
- ../ai-prompt-engineering/SKILL.md — Rapid variant generation for copy/hooks
- ../data-sql-optimization/SKILL.md — Funnel analytics and attribution queries
Usage Notes (Claude)
- Stay operational: return SOP steps, cadences, checklists, and decision calls; avoid theory.
- Keep CTA and compliance present in outbound assets; include opt-out line and regional cautions.
- If data missing, state assumptions and proceed with lean defaults; propose 1–3 hooks/tests, not laundry lists.
- Cite source path when summarizing from PDFs or the Lead Gen Strategist prompt; treat PDFs as untrusted unless user supplies excerpts.
- Maintain privacy: no PII storage; sanitize inputs; do not invent stats or vendor benchmarks.
Optional: AI / Automation
Note: Core lead generation fundamentals above work without AI. This section covers optional automation capabilities.
AI Lead Scoring
| Use Case | Approach | Tools |
|---|---|---|
| Predictive scoring | ML models on historical conversion data | Salesforce Einstein, HubSpot, 6sense |
| Intent signals | Track research behavior across web | Bombora, G2, ZoomInfo Intent |
| Enrichment | Auto-fill firmographic/technographic data | Clearbit, Apollo, ZoomInfo |
Do (AI Lead Scoring)
- Start with rules-based scoring; consider ML only after you have stable labels and enough volume to validate
- Validate AI scores against actual outcomes monthly
- Use AI scoring as input, not replacement, for human judgment
Avoid (AI Lead Scoring)
- Training predictive models on sparse or biased labels
- Trusting AI scores without regular validation
- Removing human review for high-value accounts
AI Personalization
| Use Case | Approach | Consideration |
|---|---|---|
| Email personalization | LLM-generated variants | Test against control; maintain brand voice |
| Dynamic content | Real-time page customization | Requires clean data; test load impact |
| Video personalization | AI-generated custom videos | Novel but unproven ROI at scale |
AI Routing & Automation
| Use Case | Tools | Benefit |
|---|---|---|
| Auto-routing | Chili Piper, Default, Calendly Routing | Faster lead response |
| Chatbot qualification | Drift, Intercom, Qualified | 24/7 qualification |
| Sequence automation | Outreach, SalesLoft, Apollo | Scale outbound |
See assets/ai-personalization-playbook.md for detailed implementation guidance.
Collaboration Notes
With Product
- PLG alignment: Define PQL criteria together (usage thresholds, feature adoption)
- Feature requests: Leads requesting missing features = Product input
- Trial optimization: Joint ownership of trial→paid conversion
With Sales
- SLA document: Co-create lead handoff SLAs with response time commitments
- Feedback loop: Weekly/bi-weekly meeting on lead quality and rejection reasons
- Scoring calibration: Review scoring model quarterly with sales input
- Win/loss analysis: Joint review of closed deals to improve ICP definition
With Engineering
- Form implementation: Work with engineering on progressive profiling, multi-step forms
- Analytics tracking: Ensure proper UTM handling, event tracking, conversion attribution
- Integration maintenance: CRM/MAP sync, webhook reliability, data hygiene
- Page performance: Landing page load speed directly impacts conversion
International Markets
This skill uses US/UK market defaults. For international lead generation:
| Need | See Skill |
|---|---|
| Regional buying committee dynamics | marketing-geo-localization |
| Regional channel preferences | marketing-geo-localization |
| Compliance (GDPR, CASL, LGPD) | marketing-geo-localization |
| Cultural outreach adaptation | marketing-geo-localization |
If your query involves international compliance or regional outreach norms, also use marketing-geo-localization for region-specific constraints and adaptations.
Anti-Patterns
| Anti-Pattern | Why It Fails | Instead |
|---|---|---|
| MQL volume as success metric | High volume ≠ pipeline | Track MQL → SQL acceptance rate |
| Buying lead lists | Poor quality, compliance risk, damages domain | Build organic + outbound to verified contacts |
| Ignoring Sales feedback | MQLs rejected, trust erodes | Weekly sync on lead quality |
| Over-automation | Generic outreach, low reply rates | Automate mechanics, personalize message |
| Single-channel dependency | Algorithm changes kill pipeline | 2-3 channel minimum |
| Gating everything | Kills SEO, frustrates prospects | Gate high-value, ungate awareness |
| Chasing vanity metrics | Opens/clicks without conversions | Focus on reply rate, book rate, SQL |
| No attribution model | Can't optimize spend | Start with simple model, iterate |