Account-based marketing has grown up.
It’s not just “target a list of accounts and run campaigns.” The teams winning today are coordinating signals, conversations, and value across the full buying group. When it works, it feels less like marketing and more like a connected buying experience that moves deals forward.
That shift matters because it changes what you measure.
Most ABM dashboards show activity. The best ones show momentum, progression, and revenue outcomes. This article gives you a clean KPI roadmap you can share with RevOps to build an ABM measurement system that actually helps the business make better decisions.
In most orgs, ABM metrics break down for one of three reasons:
They track activity, not progress.
Clicks and impressions do not tell you whether target accounts are truly advancing from signals and engagement to qualification and conversations.
They measure individuals, not buying groups.
Gartner notes that attribution uses individual-level data and is often confined to digital channels, creating inherent limits on what it can credibly measure.
ABM is an account motion. In B2B, decisions are made by committees.
They cannot roll up data to the account level reliably.
This is especially common in Salesforce if Leads are not matched to Accounts (more on that below).
So the goal is not “more metrics.”
The goal is a system that answers four questions, in order:
Are we set up to win the right accounts?
Are those accounts becoming sales-ready?
Are opportunities moving efficiently through the pipeline?
Are we winning, retaining, and expanding profitably?
Think of this like a revenue assembly line. Each layer supports the next.
🎯 Coverage is your foundation (data + reach + buying group visibility)
🏁 Readiness is your leading indicator (signals + engagement across roles)
📊 Throughput is your conversion engine (stage movement/progression + cycle time)
🚀 Yield is your revenue quality (wins + deal size + retention + expansion)
This structure also maps cleanly to how ABM metrics are commonly grouped across the industry:
Engagement goals → 🏁 Readiness
Penetration goals → 📊 Throughput
Retention and share goals → 🚀 Yield
What’s often missing is 🎯 Coverage, which is why many ABM programs feel “busy” but still unpredictable.
Coverage answers:
Do we have the right accounts, the right people in the buying group mapped, and enough reach to influence a buying decision?
1) ICP Fit Rate
% of target accounts that match ICP (firmographics, technographics, use-case fit)
2) Contactability
of valid contacts per target account (deliverable email, correct title, active)
3) Buying Group Completeness
of core roles identified per account
(example roles: Economic Buyer, Executive Sponsor, Champion, User Lead, Security, Procurement)
4) Buying Group Coverage by Tier
Tier 1 accounts should have the deepest buying group mapping
Tier 2 and Tier 3 can be lighter, but still need minimum reach
These vary by ACV and sales cycle, but as a baseline:
Tier 1: 4 to 6 roles identified, multiple contacts per role
Tier 2: 3 to 4 roles identified
Tier 3: 2 to 3 roles identified
Why account-level measurement matters:
"Buying groups are more diverse than ever, ranging from five to 16 people across as many as four functions." – Gartner
If you do not have buying group coverage, your “engagement” metrics will lie. You will think accounts are cold when you simply do not have the right people.
Readiness answers:
Are those accounts showing meaningful signals and multi-persona engagement that a deal could be created or accelerated soon?
This is where most teams track “engagement,” but the key is engagement across buying group roles, not just total engagement volume.
1) Number of Engaged Contacts (by account)
Unique contacts engaging in the last 30 to 60 days
2) Engagement Rate
Engagement Rate = (Engaged Contacts / Total Target Contacts) × 100
3) Account Penetration Rate (buying group depth)
Account Penetration Rate = (Engaged Key Contacts / Total Key Contacts in Account) × 100
4) Engaged Personas per Account
How many distinct buying group roles engaged in the last 30 to 60 days
5) Intent and Signal Lift (optional but powerful)
of accounts with high-intent topics surging
of accounts with repeat web visits to solution pages, pricing, integration docs, security docs, etc.
Engagement is rising across multiple roles
Accounts with high readiness show shorter time-to-meeting when routed properly
SDR and AE outreach becomes more timely and more relevant because it reacts to signals
Throughput answers:
Are target accounts progressing through your pre-opportunity stages & conversion ladder?
Since we’re talking pre-opportunity, this is not about Opportunity stage progression yet. It’s about account progression through the stages that happen before an opportunity record exists (think: target, awareness, consideration, evaluation, and purchase-ready stages).
In this post, we’re defining throughput around the ABM / ABX conversion ladder that happens pre-opportunity and ends at the point a Sales Qualified Opportunity is created.
Target → MQA → AQA → SQO
Here’s a clean, RevOps-friendly way to define each stage:
Target
ICP-confirmed account on your target list (tiered). This is “eligible” but not yet qualified.
MQA (Marketing Qualified Account)
Account meets your marketing qualification threshold. Typically includes: intent + engagement + the right personas, and the right “why now” signal.
AQA (Accepted Qualified Account)
Account is accepted for active sales pursuit. This is your “SDR/BDR Accepted” moment at the account level (many orgs previously called this SAL). Sales is committing time, outreach is underway, and there is a clear next step.
SQO (Sales Qualified Opportunity)
A qualified opportunity is created (or whatever your org defines as the official “opportunity created and qualified” milestone). This is the handoff point from pre-opportunity progression into pipeline stages.
Marketing teams often think in journey stages like:
Target → Awareness → Consideration → Evaluation (or Decision) → Purchase-ready
Revenue operations needs a conversion ladder that triggers ownership, SLAs, routing, and reporting.
The easiest way to connect them is to treat marketing stages as readiness signals that live inside the Target stage until the account becomes MQA:
Marketing: Target
→ RevOps: Target (on the list)
Marketing: Awareness
→ RevOps: Target (early engagement, low intent)
Marketing: Consideration
→ RevOps: Target (deeper engagement, more personas involved)
Marketing: Evaluation (or Decision)
→ RevOps: Target (high intent, stronger buying signals, approaching MQA threshold)
Marketing: Purchase-ready
→ RevOps: MQA (meets the qualification threshold and should trigger a sales motion)
From there, RevOps stages take over:
MQA → AQA is your sales acceptance and activation point
AQA → SQO is where qualification converts into an opportunity
This alignment helps everyone stop debating labels and start agreeing on the only thing that matters: what qualifies an account to move forward, and what happens next when it does.
1) Account Progression Count
How many target accounts advanced at least one stage in the period.
Account Progression Count = # of Target Accounts that advanced ≥ 1 stage in period
2) Account Progression Rate
A simple “momentum” metric leadership understands.
Account Progression Rate = (Progressed Target Accounts / Total Target Accounts) × 100
3) Stage Progression Rate (by conversion hop)
This is how RevOps finds bottlenecks.
Stage Progression Rate (X → Y) =
(Accounts that moved from Stage X to Stage Y in period / Accounts in Stage X at period start) × 100
Track these hops at a minimum:
Target → MQA
MQA → AQA
AQA → SQO
4) Stage Hop Time (days in stage)
Median days per stage transition (or average, if your org prefers).
Examples:
Median days from Target → MQA
Median days from MQA → AQA
Median days from AQA → SQO
5) Sales Acceptance Rate (MQA → AQA)
This is your alignment metric.
MQA → AQA Acceptance Rate = (AQAs / MQAs) × 100
6) SQO Creation Rate (from target accounts)
This tells you whether your target list is turning into qualified pipeline.
SQO Creation Rate = (Target Accounts that became SQO / Total Target Accounts) × 100
If Target → MQA is weak, revisit your readiness thresholds and buying-group reach. You may be targeting the right logos but missing the right people or signals.
If MQA → AQA is weak, tighten definitions, routing, and SLAs. Sales acceptance is usually a process problem, not a content problem.
If AQA → SQO is slow, look at discovery quality, qualification criteria, and early-stage enablement (security, procurement, business case).
The real power of throughput reporting is that it tells you exactly where momentum breaks, so you can fix the system instead of “doing more marketing.”
Yield answers:
Are we getting the revenue outcomes ABM promised, and are we doing it efficiently?
1) Win Rate (target accounts)
Track by tier, segment, region, and play type
2) Deal Size Growth
Deal Size Growth = (Current Avg Deal Size − Previous Avg Deal Size) / Previous Avg Deal Size × 100
3) Customer Renewal Rate
Customer Renewal Rate = (Renewed Accounts / Accounts Up for Renewal) × 100
4) Net Revenue Retention (NRR)
NRR = [(Starting Revenue + Expansion Revenue − Churned Revenue) / Starting Revenue] × 100
5) Share of Wallet
Share of Wallet = (Customer Spend with You / Total Potential Customer Spend) × 100
6) CAC (program and segment level)
CAC = Total Sales and Marketing Expenses / Number of New Customers Acquired
7) ROI (campaign or play level)
ROI = (Net Profit from ABM Program / Cost of ABM Program) × 100
A quick reminder: CAC and ROI are lagging indicators. Use them for quarterly learning, not weekly steering.
If you want a dashboard that drives decisions, build it as a layered system. One view per account (for execution), plus rollups by segment and tier (for leadership).
Coverage
ICP Fit (Y/N)
Buying Group Roles Identified (#)
Contactable Stakeholders (#)
Missing Roles (list)
Readiness
Engaged Contacts (30d / 60d)
Engaged Personas (30d / 60d)
Engagement Rate (%)
Last High-Intent Date
Throughput
Current Stage
Hop Time (days in stage)
Next Stage Probability (optional)
Decision-maker touchpoints (count)
Yield
Current Pipeline Value
Forecast Category
Won Revenue (if Closed Won)
Expansion Pipeline (if customer)
Pipeline and wins from target accounts
Stage conversion rates by segment
Cycle time by stage
Buying group completeness vs win rate
Engagement density vs conversion
Attribution should be a learning system, not a scorekeeping system. This matters even more pre-opportunity because most of the work happens before an opportunity exists.
1) Opportunity Source (governance field)
One “source of truth” for finance, reporting, and sales alignment.
2) Program Influence (analysis model)
Multi-touch, stage-based influence that helps you learn what moved the deal.
Influence by role (Economic Buyer vs Champion vs Procurement)
Influence by stage movement (what correlates with Target → MQA vs MQA → AQA vs AQA → SQO)
Influence by play type (events, outbound, content, paid, partner)
Last-touch over-credit (usually favors late-stage email or SDR touches)
Lead-only attribution that ignores the rest of the buying group
No campaign taxonomy aligned to funnel stages (you cannot learn without structure)
This matters a lot for ABM, because ABM reporting relies on rolling people-level activity up to the Account.
HubSpot primarily uses Contacts and Companies, and contacts are typically associated to companies automatically (often via email domain, depending on your settings and data quality). That means account rollups and account-based reporting are usually easier to establish.
Still, audit this regularly:
contacts with no company
contacts associated to the wrong company (subsidiaries, free email domains, agencies)
Salesforce commonly uses both Leads and Contacts. The big issue:
In Salesforce, Leads do not automatically have an Account relationship.
Leads only become tied to an Account after conversion (or via a separate matching process).
For ABM metrics and especially attribution, that creates a blind spot:
Engagement and touches happen on Leads
ABM reporting needs those touches rolled up to Accounts
Without lead-to-account association, your account engagement, account penetration, and influence reporting will be incomplete
In other words, when Leads are not matched to Accounts, you cannot reliably:
calculate account engagement and account penetration
attribute marketing and SDR/BDR pre-opportunity touches to target accounts
measure Target Account → MQA progression accurately if engagement is happening on your orphaned Lead records.
RevOps fix: implement lead-to-account matching.
Use a lead-to-account matching and routing tool so every Lead can be tied to the correct Account as early as possible
This unlocks accurate account engagement metrics and account-based influence reporting
It also improves routing, prioritization, and SDR productivity
"Match Leads to Accounts". Salesforce’s own help documentation describes matching leads to accounts so you can identify relationships and unify records. – Salesforce
Without lead-to-account matching, ABM metrics and influence reporting will be incomplete in Salesforce.
If you are serious about ABM in Salesforce, this is not optional. It is foundational.
Confirm the conversion ladder: Target → MQA → AQA → SQO
Agree on clear entry and exit criteria for each stage
Align marketing journey stages (Awareness, Consideration, Evaluation, Purchase-ready) to the Target → MQA promotion logic
Document SLAs for what happens when an account becomes MQA and AQA
Salesforce: implement lead-to-account matching (critical for account-based metrics)
HubSpot: audit contact-to-company associations (fix missing or incorrect company links)
Confirm your target account list is represented consistently in CRM (tiers, segments, regions)
Create an Account Stage field (Target, MQA, AQA, SQO) on Account / Company records
Add stage entry timestamps (or a lightweight stage history approach) so hop time can be measured
Set up automation or workflow rules to update stages based on agreed criteria and sales actions
Add buying-group completeness tracking (roles identified, engaged roles)
Build reports for:
Account Progression Rate
Stage Progression Rates (Target → MQA, MQA → AQA, AQA → SQO)
Hop Time by stage
Buying-group completeness vs progression
Establish a weekly review:
Which accounts progressed?
Which stalled, and where?
What play runs next based on signals and missing roles?
This is the fastest path to turning ABM measurement into a system RevOps can manage and the whole revenue team can trust.
If you want ABM (and the buying experience behind it) to become predictable, you need two things:
a measurement system that shows where momentum is building and where deals are stalling
an execution engine that can respond fast, across channels, and across the buying group
That’s exactly what we help teams build through our programs and agents, including hands-on sprints, ABX orchestration workshops, and RevAI SDR Agents that turn signals into consistent pipeline motion.
ABM vs ABX? We like to talk about account-based motions through the lens of the buyers and customers – that takes it from 'm'arketing or a 'm'otion to an 'eXperience' (or emotion). Human interaction still matters even as automation grows. Even Gartner predicts that by 2030, 75% of B2B buyers will prefer sales experiences that prioritize human interaction over AI.
If your RevOps dashboard had to answer just one thing next quarter:
A. Are we reaching the full buying group?
or
B. Are we just collecting engagement from whoever happens to click?
Which would you choose?
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I'm curious to hear your thoughts on how you and your teams are tackling the topic of attribution in your account-based motions. Feel free to continue the conversation by leaving a comment below.
If you want help implementing this KPI stack in Salesforce or HubSpot, and operationalizing it with AI-driven orchestration and agents, explore RevBuilders AI programs or book a walkthrough so we can map it to your target accounts and pipeline goals.