<!-- SPDX-License-Identifier: MIT -->
<!-- SPDX-FileCopyrightText: 2025-2026 Marcus Quinn -->

# Chapter 17: B2B Lead Generation, ABM, and Lead Scoring

B2B CRO: extended sales cycles, 6-10 decision-makers, $100K-$1M+ contracts. Buyers complete 57-70% of research independently (Gartner); only 17% of evaluation time with suppliers.

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## Part I: B2B Lead Generation

### Four Pillars

1. **Audience Precision** — Firmographic + psychographic + behavioral data. Measure ICP gap via conversion-to-opportunity rates, deal size, cycle length by source. Segment by stage, role, interests, signals.
2. **Content & Offer** — Map to journey: educational/strategic (early) → solution/comparison (mid) → ROI calculators/specs/references (late). Every offer must justify the data exchange. Test formats: PDF vs interactive, video vs written.
3. **Experience & Conversion** — Consumer-grade UX: personalization, mobile-first, fast load. Progressive profiling — every added field reduces completion.
4. **Attribution & Measurement** — Multi-touch attribution for extended cycles. Track: conversion-to-opportunity, cycle length, revenue by source.

### Lead Gen Scorecard

- **Audience:** ICP Match Rate, Target Account Penetration, Segment Conversion Variance, Cost Per Qualified Lead
- **Content:** Engagement Depth, Content-to-Lead CVR, Lead-to-Opportunity Rate by Source, Pipeline Attribution
- **Experience:** Landing Page CVR, Form Abandonment, Mobile CVR, Load Impact
- **Measurement:** Multi-Touch Coverage, Lead Quality Prediction Accuracy, Sales-Marketing Data Alignment

### Advanced Tactics

**Conversational Marketing:** Optimize intent recognition, response relevance, escalation, conversion completion. A/B test greetings, qualification sequences, response patterns.

**Interactive Content:** Value-first (insights before contact request). Progressive profiling. Personalized results. Shareability within accounts. Auto-route to nurture tracks.

**Intent Data:** First-party behavioral + third-party signals. Weight by topic relevance. Prioritize recent signals. Aggregate at account level. Integrate with sales for timely outreach.

**Landing Page:** Above fold: logos/certs, pain-point headline, value-prop subhead, social proof. Form: progressive fields, privacy assurance, value-focused CTA ("Get My Free Assessment" > "Submit"). Below fold: objection handling, features, testimonials, FAQ, trust indicators.

**Email:** Test subject lines (length, personalization, urgency, curiosity), preview text, button design/placement/copy. Optimize send times and cadence per segment. Trigger-based sending on prospect behaviors.

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## Part II: Account-Based Marketing (ABM)

ABM inverts the funnel: identify high-value accounts first, then orchestrate coordinated marketing + sales against them.

### ABM Optimization Framework

**1. Account Selection Scorecard (weighted):** Firmographic Fit 25% (size, industry, geography, structure) | Technographic Alignment 20% (stack compatibility, integration needs, maturity) | Behavioral Intent 25% (research activity, competitor engagement, buying signals) | Relationship Foundation 15% (existing connections, past engagement, referrals) | Strategic Value 15% (deal size potential, expansion opportunity, reference value).

**2. Stakeholder Engagement** (influence x attitude): High-influence champions → max investment (exec access, custom content, relationship dev). High-influence skeptics → targeted persuasion. Low-influence supporters → amplify internally. Low-influence blockers → neutralize without disproportionate spend. By role: Executives → thought leadership, peer networking | Technical evaluators → detailed docs, POC | End users → training, usability demos | Procurement → transparent pricing, flexible terms.

**3. Personalization Tiers:** Tier 1 (Strategic) — fully custom content, dedicated teams, exec programs, bespoke events. Tier 2 (High-Priority) — modular personalization, industry-specific content, role-based messaging. Tier 3 (Target) — dynamic content insertion, industry-aligned messaging, automated personalization.

**4. Channel-to-Stage:** Awareness → programmatic ads, social, publications, search. Engagement → email nurture, webinars, content syndication, website personalization. Consideration → sales outreach, demos, proposals, reference calls. Validation → exec meetings, site visits, POC trials, contract negotiation.

**5. Account-Centric Metrics:** Account Engagement Score (website + content + email + events + sales, weighted by seniority/recency). Stage progression: unaware → aware → engaged → opportunity → customer → expanded. Also: Engagement Heat Maps, Intent Trend Analysis, Competitive Presence Indicators, Relationship Depth Scoring, Opportunity Risk Indicators.

### ABM Tactics

**Programmatic ABM:** Dynamic creative with account names/industry refs. Sequential messaging. Auto-escalate ad intensity on engagement signals. Cross-channel sync.

**Direct Mail:** Trigger-based on engagement signals or stage advancement. Variable printing. Coordinated digital follow-up. QR codes / personalized URLs.

**Executive Engagement:** Peer-match by seniority, function, chemistry. Deliver genuine strategic value. Seamless handoff when opportunity signals emerge.

**Sales-Marketing Alignment:** Joint account planning, shared KPIs, coordinated playbooks. Weekly account reviews, monthly assessments, quarterly strategic planning.

**Tech Stack:** Data (account platforms, intent providers, CDPs) → Orchestration (marketing automation, sales engagement, ABM platforms) → Engagement (ads, email, direct mail, events) → Intelligence (analytics, attribution, AI). AI: propensity scoring, engagement optimization, churn prediction, next-best-action, conversation intelligence.

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## Part III: Lead Scoring

### Data Foundation

- **Firmographic:** Company size, revenue, industry, geography, structure
- **Demographic:** Title, seniority, function, tenure, background
- **Technographic:** Current stack, integration needs, infrastructure maturity
- **Behavioral:** Website, content, email, events, sales conversations
- **Intent:** Third-party research, comparison sites, competitor engagement
- **Relationship:** Referral sources, connections, past interactions, account history

### Model Architecture

| Model | Complexity | Transparency | Predictive Power | Best For |
|-------|-----------|-------------|-----------------|----------|
| Rule-Based | Low | High | Moderate | Simple processes, small data |
| Multi-Dimensional | Medium | High | Good | Complex journeys, multiple segments (separates fit vs engagement) |
| Predictive ML | High | Low-Medium | Excellent | Large data, sophisticated ops |
| Hybrid | High | Medium | Excellent | Accuracy + explainability |

### Thresholds & Routing

**MQL** → nurture | **SAL** → sales development | **SQL** → immediate AE engagement | **Exceptions** → high-value accounts or referrals.

Route: high-fit/low-engagement → targeted awareness | high-engagement/moderate-fit → qualification calls | highest scores → immediate senior sales.

### Advanced Scoring

**Behavioral Patterns:** Research-to-Evaluation (educational → solution content 7d → demo request 14d). Stakeholder Expansion (end user → technical evaluator → exec sponsor). Competitive Evaluation (comparison content + pricing visits + reference cases, compressed timeframe).

**Negative Scoring & Decay:** Fit deterioration (job change, unsuitable acquisition, tech decision against platform). Engagement quality (careers page, support-seeking, competitor events). Decay: reduce scores after 30 days inactivity.

**Account-Level Scoring:** Aggregate individual scores + breadth multiplier (unique contacts) + depth weighting (seniority/influence) + account fit baseline + intent multiplier.

**Predictive ML:** Data prep → feature engineering → training + tuning → holdout validation → deployment → drift monitoring.

### Scoring Governance

**Committee:** Marketing ops, sales ops, sales leadership, analytics. Weekly → monthly → quarterly cadence.

**Audit:** Score distribution | Conversion correlation | Sales feedback | Model drift

**Docs:** Model logic + weights | Data sources + update frequencies | Threshold definitions + actions | Change history | User guides.

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## Part IV: Integration

Key workflows with unified data infrastructure:

- **Lead-to-Account:** Inbound leads → evaluate account context → route to ABM if target account; trigger multi-threading if colleagues already engaged
- **Scoring-Driven ABM:** High scores from non-target accounts → account research + potential ABM enrollment; declining engagement → proactive intervention
- **Sales Handoff:** Transfer full context (engagement history, content, scores, talking points); continue support with account-based ads, content portals, triggered nurture
- **Unified Measurement:** Attribute revenue to all touchpoints; reveal which tactic combinations drive results for different prospect types

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## Part V: Case Studies

**Case 1 — Enterprise Software Lead Gen:** 5K MQLs/mo, 12% → opportunity, sales ignoring leads. Fix: redefined ICP, mid/bottom-funnel content, progressive qualification, fit+behavior scoring, marketing-sales SLAs. Result: lead volume -40%, opportunity CVR 12%→28%, cost per opportunity -60%, sales acceptance 30%→75%.

**Case 2 — ABM Program Launch:** Pilot (50 accounts): 3x visits, 5x engagement, only 8 opportunities. Root cause: size-over-fit selection, known-contacts-only engagement, no sales coordination. Fix: intent data in selection, stakeholder mapping, ABM specialists in sales pods, tiered personalization, weekly joint reviews. Result: pipeline per account 4x, sales cycle -30%, win rates +15pp.

**Case 3 — Lead Scoring Redesign:** Rule-based model misaligned — demo requests (20pts) converted 45% vs similar-scored leads at 5%. Fix: analyzed 2yr data, multi-dimensional model (fit + engagement + intent), negative scoring, 30-day decay. Result: top-quartile lead-to-opportunity 18%→34%, sales acceptance 45%→78%, marketing-sourced revenue 25%→42% (18mo).

**Case 4 — Integrated Optimization:** Siloed demand gen, ABM, sales ops. Fix: unified team, common data platform, cross-functional workflows (high scores trigger ABM enrollment, ABM engagement adjusts scores). Result: pipeline +45% (no additional spend), marketing ROI +60%, CAC -35%, deal value +20%.

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## Part VI: Future Trends

- **AI:** Generative AI enables personalization at scale; NLP extracts sentiment/buying signals; predictive analytics anticipates buying cycles from external signals (economic indicators, company announcements)
- **Privacy:** Cookie erosion + regulation → earn data via value exchange (communities, proprietary research, exclusive events, valuable tools)
- **Human-AI Partnership:** AI handles routine optimization; humans focus on strategic account planning, complex stakeholder navigation, creative development, relationship building
