qualify-accounts

name

qualify-accounts

description

Qualify and score target accounts using ICP scoring matrices, ABM tier assignment, intent data layering, and lookalike building. Use when user asks about "qualify accounts", "score accounts", "ABM tiers", "account-based marketing", "intent data", "lookalike accounts", "prioritize accounts", "tier 1 accounts", "account scoring". Do NOT use for initial ICP definition (use define-icp) or finding contacts at accounts (use find-contacts).

Qualify Accounts — Sub-Skill

You help users score, qualify, and prioritize target accounts using ABM tier frameworks and intent data. Always read the reference file before responding.

Reference

Read {SKILL_BASE}/resources/sales-navigator-guide.md — sections: ICP Scoring, Scoring Matrix, ABM List Building, Intent Data Layering, Lookalike Building. Read {SKILL_BASE}/resources/templates/qualification-workflow.md — ColdIQ tier system (Company/Contact tiers), weighted ICP scoring, Clay AI qualification prompts, real DevOps scoring examples, source comparison matrix, and "good list" column template.

ABM Tier Structure

Tier	Accounts	Approach	Resources
Tier 1 (1:1)	10-50	Fully custom, multi-threaded	Maximum — custom content, executive outreach, direct mail
Tier 2 (1:Few)	50-200	Segment-based personalization	Medium — industry/persona templates, targeted ads
Tier 3 (1:Many)	200-1,000	Programmatic, automated	Low — automated sequences, broad messaging

Account Scoring Process

1. Apply ICP scoring matrix (100-point system from define-icp)
2. Layer intent data to adjust scores dynamically
3. Assign ABM tier based on final score
4. Map contacts per account (Economic Buyer, Champion, Technical Evaluator, End User, Blocker, Coach)

Intent Data Layers

Layer	Sources	Signal Strength
First-party	Website visits, pricing page views, content downloads, webinar attendance	Strongest
Second-party	G2 Buyer Intent, TrustRadius, Capterra reviews/comparisons	Strong
Third-party	Bombora, 6sense, ZoomInfo Intent, TechTarget	Moderate
LinkedIn-native	Buyer Intent signals, ad engagement, page followers	Moderate

Scoring adjustment: Add 10-20 points for strong first-party intent. Add 5-10 for second/third-party. An account scoring 65 (Tier C) with strong first-party intent jumps to 75-85 (Tier B).

Lookalike Building

1. Export top 10-20 customers (by revenue, LTV, or NPS)
2. Analyze common attributes: industry, size, geography, tech stack, growth stage
3. Build lookalike search in Sales Navigator matching those attributes
4. Use "Similar Companies" feature on company pages
5. External tools: Ocean.io, Clearbit, Apollo.io, Clay

Contact Mapping Per Account

Role	Typical Titles	Purpose
Economic Buyer	CEO, CFO, VP	Final budget approval
Champion	Director, Head of	Internal advocate
Technical Evaluator	Manager, Architect	Technical fit assessment
End User	Analyst, Specialist	Daily product user
Blocker	Legal, Compliance	Can slow or stop deal
Coach	Any level	Provides insider information

Examples

Example 1: "I have 500 companies, how do I prioritize them?" -> Apply ICP scoring matrix across all 500. Sort by score. Top 10-50 (Tier A, 90+ pts) = Tier 1 ABM with custom outreach. Next 50-150 (Tier B, 70-89) = Tier 2 with segment-based sequences. Remaining (Tier C, 50-69) = Tier 3 automated. Below 50 = exclude. Layer intent data from G2/Bombora to re-rank.

Example 2: "How do I build a lookalike list from my best customers?" -> Export top 20 customers by ARR. Identify patterns: e.g., all are SaaS, 100-500 employees, US-based, using HubSpot, Series A-C funded. Build Sales Nav search matching these attributes. Use Ocean.io for automated lookalike expansion. Score new accounts against the same matrix.

Example 3: "We want to do ABM for enterprise accounts" -> Select 20-30 Tier 1 accounts scoring 90+. Map 5-6 contacts per account (buying committee). Layer first-party intent (website visits) + third-party (Bombora topics). Create custom landing pages per account. Multi-channel: LinkedIn + email + direct mail + ads.