Target Account Selector

Account Selection & Tiering

by LeadMagic · MIT license · ★ 62 on GitHub

Builds and tiers a target account list: fit and intent scoring models, tier assignment, and TAM segmentation. Use when the user needs to decide which accounts to target, score or tier an account list, or prioritize a TAM for ABM or…

---
name: account-selection
description: >-
  Builds and tiers a target account list: fit and intent scoring models, tier
  assignment, and TAM segmentation. Use when the user needs to decide which
  accounts to target, score or tier an account list, or prioritize a TAM for ABM
  or outbound. Triggers on: "account selection", "target account list", "tier
  accounts", "prioritize accounts", "TAM segmentation".
license: MIT
compatibility: Claude Code, Codex, GitHub Copilot, Cursor, Gemini CLI, OpenCode, Goose, Hermes, Windsurf, Zed
metadata:
  version: "1.1.0"
  author: LeadMagic
  category: abm
  tags: [abm, account-selection, scoring, tiering, target-accounts]
  frameworks:
    - "TOPO (now Gartner) — Account selection"
    - "Winning by Design — ICP"

Overview

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

Manual install (npx, ZIP)

Claude Codenpx skills add LeadMagic/gtm-skills --skill account-selection -g -a claude-code

Claude Code (degit)npx degit LeadMagic/gtm-skills/skills/abm/account-selection#main ~/.claude/skills/account-selection

Claude.ai / desktopZip the folder and upload it under Settings → Capabilities → Skills.

Codex, Cursor, other agentsPoint them at SKILL.md. The other files are plain text.

Connects with Agent Alley MCP · agentalley.io/mcp

Files included

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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.

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 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

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.

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	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.
98	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.
99	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.
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	1. What is the primary motion: founder-led, sales-led, product-led, partner-led, or lifecycle-led?
116	2. Which ICP tier is the output for: small business, mid-market, enterprise, or mixed?
117	3. What proof is available today: customer stories, usage data, third-party validation, screenshots, or none?
118	4. What system will execute the work: CRM, sequencer, warehouse, support desk, product analytics, or manual workflow?
119	5. 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