Resource
👥 Strategy & Technical Guide to ABM & CBM
8/6/2025
Created by: Sara McNamara
ABM isn’t just about targeting accounts anymore, it’s about getting in front of the exact people who can actually move a deal forward. Whether you’re running high‑touch 1:1 plays for your biggest accounts, segmenting into 1:Few clusters, going broad with 1:Many, or layering in CBM to reach the right contacts inside those accounts, the goal’s the same: connect with the right people at the right time with the right message.
This guide walks you through how to pick the right ABM model, the tools and workflows to make it run smoothly, the plays that actually work, and how to measure if it’s paying off. It’s meant to be practical…less theory, more “here’s how to do it and what it looks like in the real world.”
🧠 Strategic Foundation🔍 Account & Contact Selection and Tiering🛠 ABM & CBM Tech Stack🧩 Personalization Strategy📣 ABM Channels and Tactics📊 Unified ABM + CBM Metrics Table (Color‑Coded by Model Priority)🎯 Executive Targeting💼 Example Campaigns/Case Studies🔄 Sales Hand-Off🧠 Strategic Maturity Roadmap with Model Guidance📚 Follow-On Resources
🧠 Strategic Foundation
Choosing the right ABM model starts with understanding your deal size, sales cycle length, total addressable market (TAM), and available resources. The more targeted the model, the more time, budget, and sales alignment it requires.
👩💼 1:1 ABM (Strategic ABM): High-touch, highly personalized plays for top-tier accounts, focused on engaging key executives, decision-makers, and influencers within those accounts. Messaging and outreach are customized for the specific people involved in the deal. Best when deals are high-value, buying processes are complex, and you can justify heavy personalization and dedicated resources per account.
🧑🤝🧑 1:Few ABM (ABM Lite): Targeted campaigns for small clusters of accounts that share similar characteristics, with messaging tailored to the personas most likely to influence the buying decision. Ideal when your TAM is moderate in size, you sell into clearly defined segments, and you need a balance between personalization and scale.
📣 1:Many ABM (Programmatic ABM): Scalable personalization for a larger volume of ICP-fit accounts, using persona-based messaging to reach individuals at scale. Works best when your TAM is large, you need to generate broad market awareness, and you want to layer intent data for efficiency.
👤 CBM (Contact-Based Marketing): A precision targeting approach layered onto 1:Few and 1:Many ABM programs, putting relevant ads in front of specific people and personas within an account, based on intent activities like website visits, content engagement, or buying signals. CBM ensures the right groups inside the buying committee see the right messages without going as far as one-to-one creative personalization.
⭐ How to Decide: If your Annual Contract Value (ACV) is very high, your deals involve complex buying committees, and each win significantly impacts revenue, prioritize 1:1 ABM for a small number of accounts. If your ACV is moderate to high, but you have more accounts than your team can fully customize for individually, use 1:Few ABM to cluster and scale. If you’re entering a market where awareness is low or you have a very large TAM, start with 1:Many ABM to build recognition, then layer in CBM to ensure ads are reaching specific decision-makers. Use CBM in any 1:Few or 1:Many scenario to improve efficiency by narrowing your ad spend to only the personas who can move the deal forward.
🔍 Account & Contact Selection and Tiering
Build your Ideal Customer Profile (ICP) by defining firmographics such as industry, size, and revenue; technographics such as stack fit; intent signals; and engagement data from CRM activity and past conversations.
In 1:1 ABM, limit your ICP to the absolute highest-value targets with proven fit and historical success patterns. In 1:Few, broaden slightly but still maintain segment-specific relevance. In 1:Many, focus on broader ICP attributes, but layer intent to avoid waste, and let CBM refine targeting inside those accounts to the right personas.
🥇 Tier 1: Strategic accounts — 1:1 plays to executives and decision-makers; heavy sales and marketing collaboration.
🥈 Tier 2: High-potential accounts — role-based messaging to clusters of contacts, plus CBM ads to personas showing engagement signals.
🥉 Tier 3: Broad ICP-fit programmatic campaigns — scalable persona targeting with CBM for high-intent contacts only.
🛠 ABM & CBM Tech Stack
Function | Tools |
CRM | Salesforce, HubSpot |
Marketing Automation | Marketo, HubSpot, Pardot |
Intent Data | Bombora, 6sense, Demandbase |
Website Deanonymization & Ad Targeting | Vector |
Personalization | Mutiny, Drift, Qualified |
Orchestration | Terminus, Demandbase, RollWorks |
Enrichment | Clearbit, Clay, Apollo |
Data Warehousing | Snowflake, BigQuery |
Attribution | Dreamdata, Bizible, HockeyStack |
🧩 Personalization Strategy
Layer | Tactic |
Account | Industry-specific value propositions, case studies, ROI data |
Role | Persona-based messaging for decision-makers vs. influencers |
Stage | Funnel-specific CTA |
Behavior | Triggered outreach and ads based on engagement |
CBM | Persona-level ad creatives served |
👆 Match personalization depth to the ABM model: deep and unique for 1:1, semi-customized for 1:Few, scalable persona messaging for 1:Many with CBM refinement.
📣 ABM Channels and Tactics
Channel / Tactic | Description | Best-Fit ABM Models | Example Tools / Platforms (to scale campaigns once proven out) |
Targeted Display Ads | Serve ads to ICP accounts and personas using firmographic and intent filters. | 📣 1:Many / 🧑🤝🧑 1:Few | Demandbase, 6sense, Terminus, RollWorks |
LinkedIn Sponsored Content | Run role-specific ads to buying committee members within target accounts. | 🧑🤝🧑 1:Few / 📣 1:Many | LinkedIn Campaign Manager |
CBM Persona Ads | Serve ads to specific contacts within accounts based on intent activities. | 👤 CBM / 🧑🤝🧑 1:Few / 📣 1:Many | Vector, 6sense, Demandbase |
Website Personalization | Dynamically adjust site content by account, industry, or persona. | 🧑🤝🧑 1:Few / 👩💼 1:1 | Mutiny, Demandbase, Adobe Target |
Executive Targeting | Create campaigns focused on C‑suite and VP personas with tailored value propositions. | 👩💼 1:1 / 🧑🤝🧑 1:Few | Boardroom Insiders, LinkedIn, Demandbase |
Retargeting Ads | Re-engage visitors from target accounts who previously interacted with content. | 📣 1:Many / 🧑🤝🧑 1:Few | Demandbase, 6sense, Google Ads |
Account Warm‑Up | Run ads before outreach to increase familiarity and response rates. | 📣 1:Many / 🧑🤝🧑 1:Few / 👩💼 1:1 | Demandbase, 6sense, LinkedIn |
Buying Committee Blitz | Coordinate multi-channel touches to all personas in a target account simultaneously. | 👩💼 1:1 / 🧑🤝🧑 1:Few | Salesforce, Outreach, Demandbase |
Direct Mail / Gifting | Send physical gifts or collateral to key stakeholders to spark engagement. | 👩💼 1:1 / 🧑🤝🧑 1:Few | Sendoso, Reachdesk, Alyce |
Email Nurture (ABM-Specific) | Highly tailored email cadences for decision-makers in target accounts. | 👩💼 1:1 / 🧑🤝🧑 1:Few | HubSpot, Marketo, Outreach |
Event Invitations | Personalized invites to private events, roundtables, or webinars for target accounts. | 👩💼 1:1 / 🧑🤝🧑 1:Few | Splash, Bizzabo, Zoom Events |
Custom Content / Microsites | Industry- or account-specific assets to address unique priorities. | 👩💼 1:1 / 🧑🤝🧑 1:Few | Uberflip, PathFactory, Turtl |
Intent-Driven Outreach | Trigger SDR or AE outreach based on account engagement or buying signals. | 📣 1:Many / 🧑🤝🧑 1:Few / 👩💼 1:1 | 6sense, Demandbase, Salesloft |
Video Messaging | Personalized video outreach to buying committee members. | 👩💼 1:1 / 🧑🤝🧑 1:Few | Vidyard, Loom, BombBomb |
📊 Unified ABM + CBM Metrics Table (Color‑Coded by Model Priority)
When we think about measuring ABM campaigns, it’s important to measure your ABM campaigns against a baseline of your non-ABM campaigns, or previous campaigns. This will help you understand if the right metrics are being lifted, or if ABM is actually not helping your efforts.
Key:
🟦 = Most critical in 1:1
🟩 = Most critical in 1:Few
🟨 = Most critical in 1:Many
Metric | Definition | Calculation | Model Guidance |
Website-identified contact reach | Number of unique ICP contacts identified on your website. | Count of distinct contacts from your website matching ICP criteria. | 🟩 🟨 Validates reach in 1:Few & 1:Many; in 1:1, just confirms targeting. |
CBM ad engagement rate | % of targeted contacts who clicked or interacted with CBM ads. | (Contacts who clicked ÷ Total targeted contacts) × 100 | 🟩 🟨 Higher in 1:Few due to focused spend; lower acceptable in 1:Many. |
Buying committee penetration | % of known buying committee members engaged. | (Engaged committee members ÷ Total known committee members) × 100 | 🟦 🟩 Core in 1:1 for full coverage; valuable in 1:Few. |
Account coverage | % of target accounts with complete data for all key roles. | (Accounts with complete data ÷ Total target accounts) × 100 | 🟦 🟩 🟨 Foundational across all models. |
Role coverage | Avg. % of buying committee roles filled per account. | (Roles filled ÷ Total possible roles) × 100 | 🟦 🟩 Critical for multi-threading in 1:1; useful in 1:Few. |
Account reach | % of target accounts with at least one engagement. | (Engaged accounts ÷ Total target accounts) × 100 | 🟨 Key in 1:Many; irrelevant in 1:1 where aim is 100%. |
Marketing Qualified Accounts (MQAs) | Accounts meeting engagement thresholds. | Count of accounts reaching MQA score. | 🟩 🟨 Vital for triggering sales in 1:Few & 1:Many. |
Stage progression rate | % of accounts moving to the next ABM stage. | (Accounts advancing ÷ Accounts in stage) × 100 | 🟦 🟩 Health check in 1:1; movement signal in 1:Few. |
Time in stage | Avg. days accounts spend in a stage. | Total days in stage ÷ Accounts in stage | 🟦 Velocity control in 1:1; optimization in 1:Many. |
Stage conversion rate | % of accounts in a stage that become opps. | (Opps created ÷ Accounts in stage) × 100 | 🟦 🟩 🟨 Valuable across all models. |
Opportunity multi-threading | Avg. # of contacts engaged per opp. | Total engaged contacts ÷ Number of opps | 🟦 🟩 Strong win driver in 1:1; valuable in 1:Few. |
Win rate with CBM engagement | % of opps with CBM engagement that close. | (Closed-won opps with CBM ÷ Total CBM opps) × 100 | 🟩 🟨 Justifies CBM in 1:Few; validates targeting in 1:Many. |
ACV lift from committee engagement | Deal size increase when committee engages. | (ACV with engagement − ACV without) ÷ ACV without × 100 | 🟦 High ROI proof in 1:1. |
Deal cycle acceleration | Days reduced in sales cycle from early engagement. | Avg. cycle without − Avg. cycle with engagement | 🟦 🟩 🟨 Important in all models. |
Closed-won influence from CBM ads | % of wins with CBM ad touches. | (Closed-won with CBM ÷ Total closed-won) × 100 | 🟨 Shows CBM influence in 1:Many. |
ABM-attributed revenue | Revenue from ABM accounts. | Sum of closed-won opp value from ABM accounts. | 🟦 🟩 🟨 Ultimate metric across all models. |
ABM win rate | Win rate for ABM vs. non-ABM accounts. | (Closed-won ABM opps ÷ Total ABM opps) × 100 | 🟦 🟩 🟨 Demonstrates strategic impact. |
Cost per engaged contact | Ad cost to engage one contact. | Total ad spend ÷ Engaged contacts | 🟨 Key scale control metric in 1:Many. |
Cost per engaged account | Ad cost to engage one ICP account. | Total ad spend ÷ Engaged accounts | 🟩 🟨 Budget optimization in 1:Few & 1:Many. |
Cost per opportunity influenced | Ad cost to influence a pipeline opp. | Total ad spend ÷ Opps with CBM engagement | 🟩 Justification metric in 1:Few. |
Channel ROI | ROI per advertising channel. | (Attributed revenue ÷ Channel ad spend) × 100 | 🟨 Used to prune channels in 1:Many. |
ABM ROI | ROI for ABM program overall. | (ABM revenue − ABM cost) ÷ ABM cost × 100 | 🟦 🟩 🟨 C-suite metric for all programs. |
🎯 Executive Targeting
Executives influence strategic purchasing decisions, can shorten deal cycles, and often increase deal value. Use Boardroom Insiders for deep executive profiles, LinkedIn Sales Navigator for relationship mapping, press releases and earnings calls for current priorities, and CRM history for past interactions. In 1:1, executive targeting is critical; in 1:Few, it’s best for deals with visible C-suite involvement; in 1:Many, it’s rare unless targeting a specific executive persona across multiple accounts.
💼 Example Campaigns/Case Studies
Vector‑Triggered Ads — 👤 CBM / 🧑🤝🧑 1:Few / 📣 1:Many
MezzoLab identified high‑intent website visitors, filtered for ICP fit, and served persona‑specific ads—reducing wasted spend and boosting engagement with the right contacts.
6sense Audience Activation — 📣 1:Many / 🧑🤝🧑 1:Few
Flexential segmented accounts by buying stage using predictive intent data, then activated ads to in‑market audiences—achieving a 77% progression rate and a 101% lift in closed‑won revenue.
Demandbase Retargeting — 📣 1:Many / 🧑🤝🧑 1:Few
Zuora transformed its GTM via Demandbase orchestration by aligning teams, amplifying visibility, and creating a unified ABM platform for campaigns and personalization.
Buying Committee Blitz — 👩💼 1:1 / 🧑🤝🧑 1:Few
Thales launched coordinated ads and personalized messaging across multiple buying committee members, doubling MQAs and boosting CTRs.
Account Warm‑Up — 📣 1:Many / 🧑🤝🧑 1:Few / 👩💼 1:1
AVEVA used targeted ads ahead of SDR outreach to build familiarity and warm up key accounts, increasing engagement and improving conversion rates globally.
Executive Targeting — 👩💼 1:1 / 🧑🤝🧑 1:Few
Unfortunately Boardroom Insiders scrapped their old website 😭 but the idea with a vendor like them is that you can learn everything possible about specific executives at larger companies, like Amazon. You can then have this information available to sales and marketing for targeting to build rapport. You could use a list of executives in Vector, target ads to them, and then have sales armed with their personal/professional interests right behind 1 click.
NOTE: I mention a lot of tech vendors here, and they certainly can help with getting campaigns up more quickly — BUT please first have a strategy BEFORE purchasing expensive tech! You can do all of these manually, it’ll just be a bit slower. I recommend starting small and slow to test your hypotheses, and then scale (and consider purchasing tech if needed).
🔄 Sales Hand-Off
This is an area that many companies miss — sure, you can launch these beautiful personalized campaigns, but does your sales team know what your campaigns are telling their audiences? Do they have a follow-up playbook for each persona or lead source? Make sure that, for each campaign, you meet with sales pre-launch to figure out the follow-up motion they should take. For an example, if you are running an extremely targeted executive campaign, you’ll want them to try to meet those executives for a dinner…or, at the very least, spend good time preparing and really impressing the executive during the call.
The best ABM collaboration I’ve seen includes a campaign playbook channel for each campaign as well as an account channel for each tier 1 account.
🧠 Strategic Maturity Roadmap with Model Guidance
1️⃣ Stage 1: Foundations — Define ICP, TAM. Keep lists small in 1:1, clustered in 1:Few, broad but intent-filtered in 1:Many.
2️⃣ Stage 2: Activation — Launch ABM + CBM plays for Tier 2 and Tier 3. In 1:Many, run persona-based CBM ads; in 1:Few, combine with tailored messaging; 1:1 may not enter until later.
3️⃣ Stage 3: Orchestration — Integrate ABM tools and CRM. In 1:Many, automate targeting rules; in 1:Few, build segment-level orchestration; in 1:1, coordinate sales outreach with content sequencing.
4️⃣ Stage 4: Optimization — Test messaging and sequencing. In 1:Many, focus on cost per engaged contact and opportunity creation; in 1:Few, on buying committee penetration; in 1:1, on content quality for executives.
5️⃣ Stage 5: Expansion — Predictive full-funnel ABM + CBM at scale. In 1:Many, adjust spend and messaging dynamically; in 1:Few, expand to new clusters; in 1:1, slightly increase account volume without losing personalization depth.
📚 Follow-On Resources
- Demandbase ABM Certification (I haven’t taken this, but have heard good things!)
Related Guides
🌐 The Ultimate Guide to Forms & Landing Pages That Perform
🕵️♂️ Intent Data Use Case Template
The Marketing Operations Strategist Newsletter
Join 3,500+ operations professionals. Get actionable MOPs tips every month.