Account Selection & Tiering skill

Builds and tiers a target account list: fit and intent scoring models, tier assignment, and TAM segmentation.

by LeadMagic·MIT license·★ 62 Stars on the repo·GitHub ↗

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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

  1. 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.
  2. 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.
  3. 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 assumptions
  • templates/output-template.md — copy-paste deliverable structure for the user
  • scripts/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
  1. What is the primary motion: founder-led, sales-led, product-led, partner-led, or lifecycle-led?
  2. Which ICP tier is the output for: small business, mid-market, enterprise, or mixed?
  3. What proof is available today: customer stories, usage data, third-party validation, screenshots, or none?
  4. What system will execute the work: CRM, sequencer, warehouse, support desk, product analytics, or manual workflow?
  5. 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.
  • icp-scoring, abm-strategy, signal-scoring, lead-finding, list-building
1---
2name: account-selection
3description: >-
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".
9license: MIT
10compatibility: Claude Code, Codex, GitHub Copilot, Cursor, Gemini CLI, OpenCode, Goose, Hermes, Windsurf, Zed
11metadata:
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
26Account selection is the hardest part of ABM. Pick wrong and you waste 6 months.
27Pick right and you 3x your close rate. This skill builds a weighted scoring model
28to 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
45Weight 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
81Scored account list with tier assignments, scoring model documentation, and a
82refinement calendar.
83 
84 
85 
86## Quality Check
87 
88Before 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 
971. **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.
982. **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.
993. **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
106This skill includes lightweight artifacts the agent can load on demand:
107Use 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 
111Use this section when the user asks for a finished asset, not a high-level explanation.
112 
113### Diagnostic Questions
114 
1151. What is the primary motion: founder-led, sales-led, product-led, partner-led, or lifecycle-led?
1162. Which ICP tier is the output for: small business, mid-market, enterprise, or mixed?
1173. What proof is available today: customer stories, usage data, third-party validation, screenshots, or none?
1184. What system will execute the work: CRM, sequencer, warehouse, support desk, product analytics, or manual workflow?
1195. What decision will the user make from this output: launch, prioritize, route, rewrite, score, coach, or measure?
120 
121### Framework Application
122 
123Map 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 
132A 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 

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