Account Selection & Tiering skill
Builds and tiers a target account list: fit and intent scoring models, tier assignment, and TAM segmentation.
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SKILL.md · the author's own words# Account Selection & Tiering ## Overview Account selection is the hardest part of ABM. Pick wrong and you waste 6 months. Pick right and you 3x your close rate. This skill builds a weighted scoring model to tier your TAM into Strategic, Scale, and Programmatic accounts. ## Authoritative Foundations - **TOPO (now Gartner) — Account selection** — Score accounts on fit first, then layer intent and engagement to decide tier; fit without in… - **Winning by Design — ICP** — Define the ideal customer profile from closed-won customers who retain and expand, not from the largest log… - **ITSMA — Account-Based Marketing** — Tier-based ABM (1:1 / 1:few / 1:many); measure pipeline from target accounts, not lead volume. - **Lars Nilsson — Account-based sales development (ABSD)** — Select and sequence accounts by buying signals, not firmographics alone; the… ## When to Use - "Which accounts should we target?" - "Tier our target account list"
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Account Selection & Tiering
Overview
Account selection is the hardest part of ABM. Pick wrong and you waste 6 months. Pick right and you 3x your close rate. This skill builds a weighted scoring model to tier your TAM into Strategic, Scale, and Programmatic accounts.
Authoritative Foundations
- TOPO (now Gartner) — Account selection — Score accounts on fit first, then layer intent and engagement to decide tier; fit without intent is a nurture list, not a target list.
- Winning by Design — ICP — Define the ideal customer profile from closed-won customers who retain and expand, not from the largest logos.
- ITSMA — Account-Based Marketing — Tier-based ABM (1:1 / 1:few / 1:many); measure pipeline from target accounts, not lead volume.
- Lars Nilsson — Account-based sales development (ABSD) — Select and sequence accounts by buying signals, not firmographics alone; the account list is a living ranking, not an annual export.
When to Use
- "Which accounts should we target?"
- "Tier our target account list"
- "Build an account scoring model"
- "Prioritize our TAM for ABM"
Step-by-Step Process
Phase 1: Build Scoring Model
Weight each dimension (must total 100 points):
Firmographic Fit (35 pts):
- Industry match (0-10): Direct ICP industry = 10, adjacent = 5, outside = 2
- Employee count (0-10): In sweet spot = 10, near = 5, outside = 2
- Revenue range (0-10): In sweet spot = 10, near = 5, outside = 2
- Geography (0-5): Target region = 5, acceptable = 3, outside = 1
Technographic Fit (25 pts):
- Current tech stack (0-15): Complementary tools present = 15, some = 8, none = 2
- Integration potential (0-10): High integration value = 10, medium = 5, low = 2
Behavioral Signals (25 pts):
- Website visits (0-10): Frequent, multi-page = 10, some = 5, none = 2
- Content engagement (0-10): Downloads, webinar attendance, newsletter = score by recency
- Social engagement (0-5): LinkedIn follows, comments, shares
Intent & Trigger (15 pts):
- Hiring signals (0-5): Role related to your product = 5
- Funding event (0-5): Recent raise = 5
- Tech change (0-5): Evidence of switching or evaluating
Phase 2: Tier Assignment
- Tier 1 (>80): 5-15 accounts. Immediate sales + marketing investment.
- Tier 2 (60-79): 15-50 accounts. Scaled ABM plays.
- Tier 3 (40-59): 50-200 accounts. Programmatic nurture.
- Below 40: Not ABM. Generic inbound/outbound only.
Phase 3: Ongoing Refinement
- Idle whitespace pull (ABSD): filter high-fit prospects with zero prior business and zero open pipeline — that list is the targeted-outbound campaign queue (
references/lars-nilsson-absd.md) - Monthly: Re-score based on new signals
- Quarterly: Review tier assignments, promote/demote accounts
- After wins: Analyze what made winners score high — adjust weights
- After losses: Add disqualifying signals discovered in lost deals
Output Format
Scored account list with tier assignments, scoring model documentation, and a refinement calendar.
Quality Check
Before delivering, verify:
- All required sections are complete
- Output matches the user's stated need
- Named frameworks are cited for key recommendations
- No vague claims — every recommendation has a specific action
- Deliverable is ready for operational use, not just conceptual
Common Pitfalls
- Treating ABM as a marketing-only initiative. ABM requires tight sales alignment. Without BDRs assigned to specific accounts and shared account briefs, marketing produces content nobody uses. Fix: weekly ABM standups with marketing + BDRs + AEs.
- One-size-fits-all tiering. Applying the same playbook to Tier 1 and Tier 3 accounts. Fix: Tier 1 gets custom content and executive engagement; Tier 3 gets automated personalization.
- Measuring ABM on MQLs. ABM success is pipeline from target accounts, not lead volume. Fix: track coverage %, engagement depth, pipeline created, and win rate by tier.
Execution Artifacts
references/framework-notes.md— named frameworks, citation anchors, and operating assumptionstemplates/output-template.md— copy-paste deliverable structure for the userscripts/check-output.py— local checklist validator for required sections This skill includes lightweight artifacts the agent can load on demand: Use the artifacts when the user asks for an implementation-ready deliverable, a repeatable workflow, or a quality check rather than generic advice.
Implementation Depth
Use this section when the user asks for a finished asset, not a high-level explanation.
Diagnostic Questions
- What is the primary motion: founder-led, sales-led, product-led, partner-led, or lifecycle-led?
- Which ICP tier is the output for: small business, mid-market, enterprise, or mixed?
- What proof is available today: customer stories, usage data, third-party validation, screenshots, or none?
- What system will execute the work: CRM, sequencer, warehouse, support desk, product analytics, or manual workflow?
- What decision will the user make from this output: launch, prioritize, route, rewrite, score, coach, or measure?
Framework Application
Map the recommendation explicitly to the named frameworks in this skill:
- TOPO Account Selection: apply only the part that directly improves the requested deliverable.
- WbD ICP Framework: apply only the part that directly improves the requested deliverable.
- ITSMA — Account-Based Marketing: apply only the part that directly improves the requested deliverable.
- Lars Nilsson ABSD signal-based selection: apply only the part that directly improves the requested deliverable.
Deliverable Standard
A strong output from this skill includes:
- A crisp diagnosis of the current situation
- A recommended path with tradeoffs, not a generic list
- A concrete artifact the user can use immediately: table, script, checklist, scorecard, sequence, dashboard spec, or implementation plan
- A measurement plan with leading and lagging indicators
- Risks and edge cases called out before execution
Adaptation Rules
- For small business: reduce complexity, shorten time-to-value, and prioritize owner/operator clarity.
- For mid-market: include workflow ownership, handoffs, integrations, and enablement assets.
- For enterprise: include governance, risk, procurement, stakeholder mapping, and proof requirements.
Related Skills
- icp-scoring, abm-strategy, signal-scoring, lead-finding, list-building
| 1 | |
| 2 | name account-selection |
| 3 | description >- |
| 4 | Builds and tiers a target account list: fit and intent scoring models, tier |
| 5 | assignment, and TAM segmentation. Use when the user needs to decide which |
| 6 | accounts to target, score or tier an account list, or prioritize a TAM for ABM |
| 7 | or outbound. Triggers on: "account selection", "target account list", "tier |
| 8 | accounts", "prioritize accounts", "TAM segmentation". |
| 9 | license MIT |
| 10 | compatibility Claude Code, Codex, GitHub Copilot, Cursor, Gemini CLI, OpenCode, Goose, Hermes, Windsurf, Zed |
| 11 | metadata |
| 12 | version "1.1.0" |
| 13 | author LeadMagic |
| 14 | category abm |
| 15 | tags [abm, account-selection, scoring, tiering, target-accounts] |
| 16 | frameworks |
| 17 | - "TOPO (now Gartner) — Account selection" |
| 18 | - "Winning by Design — ICP" |
| 19 | - "ITSMA — Account-Based Marketing" |
| 20 | - "Lars Nilsson — Account-based sales development (ABSD)" |
| 21 | |
| 22 | |
| 23 | # Account Selection & Tiering |
| 24 | |
| 25 | ## Overview |
| 26 | Account selection is the hardest part of ABM. Pick wrong and you waste 6 months. |
| 27 | Pick right and you 3x your close rate. This skill builds a weighted scoring model |
| 28 | to tier your TAM into Strategic, Scale, and Programmatic accounts. |
| 29 | |
| 30 | ## Authoritative Foundations |
| 31 | **TOPO (now Gartner) — Account selection** — Score accounts on fit first, then layer intent and engagement to decide tier; fit without intent is a nurture list, not a target list. |
| 32 | **Winning by Design — ICP** — Define the ideal customer profile from closed-won customers who retain and expand, not from the largest logos. |
| 33 | **ITSMA — Account-Based Marketing** — Tier-based ABM (1:1 / 1:few / 1:many); measure pipeline from target accounts, not lead volume. |
| 34 | **Lars Nilsson — Account-based sales development (ABSD)** — Select and sequence accounts by buying signals, not firmographics alone; the account list is a living ranking, not an annual export. |
| 35 | |
| 36 | ## When to Use |
| 37 | "Which accounts should we target?" |
| 38 | "Tier our target account list" |
| 39 | "Build an account scoring model" |
| 40 | "Prioritize our TAM for ABM" |
| 41 | |
| 42 | ## Step-by-Step Process |
| 43 | |
| 44 | ### Phase 1: Build Scoring Model |
| 45 | Weight each dimension (must total 100 points): |
| 46 | |
| 47 | **Firmographic Fit (35 pts):** |
| 48 | Industry match (0-10): Direct ICP industry = 10, adjacent = 5, outside = 2 |
| 49 | Employee count (0-10): In sweet spot = 10, near = 5, outside = 2 |
| 50 | Revenue range (0-10): In sweet spot = 10, near = 5, outside = 2 |
| 51 | Geography (0-5): Target region = 5, acceptable = 3, outside = 1 |
| 52 | |
| 53 | **Technographic Fit (25 pts):** |
| 54 | Current tech stack (0-15): Complementary tools present = 15, some = 8, none = 2 |
| 55 | Integration potential (0-10): High integration value = 10, medium = 5, low = 2 |
| 56 | |
| 57 | **Behavioral Signals (25 pts):** |
| 58 | Website visits (0-10): Frequent, multi-page = 10, some = 5, none = 2 |
| 59 | Content engagement (0-10): Downloads, webinar attendance, newsletter = score by recency |
| 60 | Social engagement (0-5): LinkedIn follows, comments, shares |
| 61 | |
| 62 | **Intent & Trigger (15 pts):** |
| 63 | Hiring signals (0-5): Role related to your product = 5 |
| 64 | Funding event (0-5): Recent raise = 5 |
| 65 | Tech change (0-5): Evidence of switching or evaluating |
| 66 | |
| 67 | ### Phase 2: Tier Assignment |
| 68 | **Tier 1 (>80):** 5-15 accounts. Immediate sales + marketing investment. |
| 69 | **Tier 2 (60-79):** 15-50 accounts. Scaled ABM plays. |
| 70 | **Tier 3 (40-59):** 50-200 accounts. Programmatic nurture. |
| 71 | **Below 40:** Not ABM. Generic inbound/outbound only. |
| 72 | |
| 73 | ### Phase 3: Ongoing Refinement |
| 74 | Idle whitespace pull (ABSD): filter high-fit prospects with zero prior business and zero open pipeline — that list is the targeted-outbound campaign queue (`references/lars-nilsson-absd.md`) |
| 75 | Monthly: Re-score based on new signals |
| 76 | Quarterly: Review tier assignments, promote/demote accounts |
| 77 | After wins: Analyze what made winners score high — adjust weights |
| 78 | After losses: Add disqualifying signals discovered in lost deals |
| 79 | |
| 80 | ## Output Format |
| 81 | Scored account list with tier assignments, scoring model documentation, and a |
| 82 | refinement calendar. |
| 83 | |
| 84 | |
| 85 | |
| 86 | ## Quality Check |
| 87 | |
| 88 | Before delivering, verify: |
| 89 | [ ] All required sections are complete |
| 90 | [ ] Output matches the user's stated need |
| 91 | [ ] Named frameworks are cited for key recommendations |
| 92 | [ ] No vague claims — every recommendation has a specific action |
| 93 | [ ] Deliverable is ready for operational use, not just conceptual |
| 94 | |
| 95 | ## Common Pitfalls |
| 96 | |
| 97 | **Treating ABM as a marketing-only initiative.** ABM requires tight sales alignment. Without BDRs assigned to specific accounts and shared account briefs, marketing produces content nobody uses. Fix: weekly ABM standups with marketing + BDRs + AEs. |
| 98 | **One-size-fits-all tiering.** Applying the same playbook to Tier 1 and Tier 3 accounts. Fix: Tier 1 gets custom content and executive engagement; Tier 3 gets automated personalization. |
| 99 | **Measuring ABM on MQLs.** ABM success is pipeline from target accounts, not lead volume. Fix: track coverage %, engagement depth, pipeline created, and win rate by tier. |
| 100 | |
| 101 | ## Execution Artifacts |
| 102 | |
| 103 | `references/framework-notes.md` — named frameworks, citation anchors, and operating assumptions |
| 104 | `templates/output-template.md` — copy-paste deliverable structure for the user |
| 105 | `scripts/check-output.py` — local checklist validator for required sections |
| 106 | This skill includes lightweight artifacts the agent can load on demand: |
| 107 | Use the artifacts when the user asks for an implementation-ready deliverable, a repeatable workflow, or a quality check rather than generic advice. |
| 108 | |
| 109 | ## Implementation Depth |
| 110 | |
| 111 | Use this section when the user asks for a finished asset, not a high-level explanation. |
| 112 | |
| 113 | ### Diagnostic Questions |
| 114 | |
| 115 | What is the primary motion: founder-led, sales-led, product-led, partner-led, or lifecycle-led? |
| 116 | Which ICP tier is the output for: small business, mid-market, enterprise, or mixed? |
| 117 | What proof is available today: customer stories, usage data, third-party validation, screenshots, or none? |
| 118 | What system will execute the work: CRM, sequencer, warehouse, support desk, product analytics, or manual workflow? |
| 119 | What decision will the user make from this output: launch, prioritize, route, rewrite, score, coach, or measure? |
| 120 | |
| 121 | ### Framework Application |
| 122 | |
| 123 | Map the recommendation explicitly to the named frameworks in this skill: |
| 124 | |
| 125 | TOPO Account Selection: apply only the part that directly improves the requested deliverable. |
| 126 | WbD ICP Framework: apply only the part that directly improves the requested deliverable. |
| 127 | ITSMA — Account-Based Marketing: apply only the part that directly improves the requested deliverable. |
| 128 | Lars Nilsson ABSD signal-based selection: apply only the part that directly improves the requested deliverable. |
| 129 | |
| 130 | ### Deliverable Standard |
| 131 | |
| 132 | A strong output from this skill includes: |
| 133 | |
| 134 | A crisp diagnosis of the current situation |
| 135 | A recommended path with tradeoffs, not a generic list |
| 136 | A concrete artifact the user can use immediately: table, script, checklist, scorecard, sequence, dashboard spec, or implementation plan |
| 137 | A measurement plan with leading and lagging indicators |
| 138 | Risks and edge cases called out before execution |
| 139 | |
| 140 | ### Adaptation Rules |
| 141 | |
| 142 | For small business: reduce complexity, shorten time-to-value, and prioritize owner/operator clarity. |
| 143 | For mid-market: include workflow ownership, handoffs, integrations, and enablement assets. |
| 144 | For enterprise: include governance, risk, procurement, stakeholder mapping, and proof requirements. |
| 145 | |
| 146 | |
| 147 | ## Related Skills |
| 148 | icp-scoring, abm-strategy, signal-scoring, lead-finding, list-building |
| 149 |
Discussion
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