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What Is Account Scoring in ABM?

Account scoring ranks companies by Fit, Intent, and Engagement so Marketing, Sales, and RevOps can focus on buying groups most likely to create and expand revenue. It’s a governed capability—not a one-off model.

Activate ABM Account Scoring Map Signals with The Loop™

Account scoring calculates an Account Qualification Score (AQS) by blending three signal sets—Fit (ICP firmographics/technographics), Intent (in-market research and topic surges), and Engagement (first-party behavior across web, email, ads, events, and sales touches). Teams apply weights, thresholds, recency/decay, and negative rules to produce Marketing Qualified Accounts (MQAs), trigger next-best actions, and route with SLAs—measured by pipeline per 100 MQAs, win rate, cycle time, ACV, and expansion.

Core Elements of a Reliable AQS

Fit (ICP) — Industry, size, region, tech stack, compliance needs, look-alike customers.
Intent — Topic surges, competitor comparisons, 3rd-party research, peer content consumption.
Engagement — High-value pages, pricing/tools, demo/consult requests, events, replies, SDR outcomes.
Buying Group Coverage — Roles represented, sequence of actions by persona, consensus signals.
Recency & Decay — Weight fresh actions; decay stale behavior to reduce false MQAs.
Negative Signals — Career page visits, EDU domains, competitor job seekers, unqualified regions.
Governance — Shared taxonomy, versioned rules, audit trail, and quarterly reviews with Sales.
Data Hygiene — De-duplication, domain matching, unifying leads→contacts→accounts.

The ABM Account Scoring Playbook

Use this sequence to design, deploy, and govern account scoring across Marketing, Sales, and RevOps.

Define → Model → Instrument → Activate → Route → Measure → Govern

  • Define ICP & motions: Segments, exclusions, buying groups; align to products and territories.
  • Model Fit–Intent–Engagement: Weights, MQA threshold, recency windows, decay, negative rules.
  • Instrument identity & events: Domain matching, UTMs, standardized forms, intent topics, sales outcomes.
  • Activate plays: Personalization, ABM ads, SDR cadences; next-best actions by high-intent topic.
  • Route with SLAs: Ownership rules, MQA alerts, acceptance criteria, recycle logic for stalled accounts.
  • Measure outcomes: Pipeline per 100 MQAs, meeting rate, win rate, cycle time, ACV/ARR.
  • Govern & tune: Backtests, cohort analysis, and versioned release notes—quarterly with Sales.

Account Scoring Capability Maturity Matrix

Capability From (Ad Hoc) To (Operationalized) Owner Primary KPI
ICP Definition Generic personas Segmented ICP with exclusions and look-alikes Product Marketing % MQAs in ICP
Data Foundation Leads not linked to accounts Unified lead→contact→account with high domain match rate RevOps Match Rate, Duplicate Rate
Scoring Model Single lead score Fit–Intent–Engagement AQS with decay & negatives Marketing Ops Pipeline per 100 MQAs
Routing & SLAs Manual assignment Automated territory routing, acceptance, recycle logic Sales Ops Speed-to-First-Touch
Activation One-size campaigns Plays by segment & intent topic; ABM ads + SDR cadences Demand Gen/SDR Meetings per MQA
Governance Untracked tweaks Versioned models, backtests, release notes RevOps Council Win Rate, Cycle Time

Client Snapshot: MQAs that Create Pipeline

After unifying identity and launching a Fit–Intent–Engagement model with recycle rules, a B2B SaaS team increased pipeline per 100 MQAs and shortened sales cycles. Explore results: Comcast Business · Broadridge

Start by mapping signals to journeys with The Loop™, then activate ABM programs that use AQS to trigger next-best actions across channels.

Frequently Asked Questions about Account Scoring

How is account scoring different from lead scoring?
Lead scoring evaluates individuals; account scoring aggregates buyer-group activity and fit at the company level. In ABM, the account is the unit of value, so routing and SLAs center on the account.
How do we choose weights for Fit, Intent, and Engagement?
Start with hypothesis weights (e.g., 40/35/25), backtest on historical opportunities, and adjust quarterly. Add decay so recent actions count more than old ones.
What causes false positives?
Student traffic, competitor job seekers, vendor research, and bots. Use negative rules (career pages, EDU domains), frequency caps, and anomaly filters.
Where should scores live—MAP or CRM?
Expose scores in both. Identity resolution, routing, and SLAs are RevOps functions; publish model versions and fields to all systems.
How do we measure success?
Track pipeline per 100 MQAs, meeting rate, win rate, cycle time, ACV, and ARR/expansion versus baseline and holdouts.

Operationalize Account Scoring

Map Fit–Intent–Engagement to next-best actions, route with SLAs, and measure what matters: pipeline, win rate, and expansion.

Activate ABM Account Scoring Map Signals with The Loop™
Explore More
Lead Management Account-Based Marketing Customer Journey Map (The Loop™) What is Account Scoring in ABM?

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