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.

Scope Boundary (Important)

This skill covers pipeline creation up to qualification and meeting booking (Lead/MQL/SQL/PQL definitions, routing, SLAs, and conversion). It does not cover late-stage closing work such as proposals, negotiation, procurement, contract redlines, or expansion.

If the user is asking for end-to-end sales execution (discovery-to-close), route to startup-sales-execution.

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

• Discovery-to-close sales execution (proposals, negotiation, procurement) → startup-sales-execution

• Onboarding, retention, renewals, expansion → startup-customer-success

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/trust

Operational 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

• Strategy & targeting: ICP & buyer personas (references/icp-buyer-personas.md ), ABM account-based marketing (references/abm-account-based.md )

• Scoring & nurture: Lead scoring models (references/lead-scoring-models.md ), lead nurturing workflows (references/lead-nurturing-workflows.md )

• Acquisition channels: Outbound sequences (references/outbound-sequences.md ), webinar & event funnels (references/webinar-event-funnels.md ), lead magnets & gating (references/lead-magnets-gating.md )

• Partnerships & signals: Referral & partner programs (references/referral-partner-programs.md ), intent data & buying signals (references/intent-data-buying-signals.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