BusinessBeginnerPreview
Account-Based Marketing (ABM)
A practical, evidence-driven course on running account-based marketing the way the best B2B teams do: defining an ideal customer profile and a finite target account list, mapping the buying group, aligning marketing and sales on shared goals, choosing the right ABM model and tooling, running coordinated personalized plays across channels, and measuring the program on pipeline and revenue instead of vanity metrics.
Beginners, B2B marketers, founders, and sales or revenue operators who want to run account-based marketing and make a finite set of high-value accounts the focus of coordinated sales and marketing effort.
Course content
Workbook & downloads
Put the course into practice — a printable workbook plus editable templates you can fill in and reuse.
Preview the workbook
This workbook turns the course into the real artifacts of running an ABM program. Each section mirrors one course module with hands-on exercises, fill-in worksheets, and checklists you apply to your own business. Pick one product and one realistic segment you sell to, and carry them through every section. You will finish with a data-backed ideal customer profile, a scored and tiered target account list, mapped buying groups, a written marketing-sales SLA and joint account plan, a designed multi-channel play, and an account-based scorecard that reports pipeline, win rate, and deal size instead of leads and clicks.
What ABM Is and When It Wins
Decide whether ABM fits your economics, pick the right mix of one-to-one, one-to-few, and one-to-many, before you build a single list.
Worksheet: ABM Fit & Economics Check
Be honest about whether your business should run ABM at all, and for which accounts. Fill in your real numbers so the decision is grounded, not aspirational.
- Average annual contract value (ACV) of a typical deal
- Win rate on serious opportunities (%)
- Number of decision makers in a typical deal (buying-group size)
- Typical sales cycle length (months)
- Roughly how many companies in the world actually fit (dozens / hundreds / thousands / millions)
- Revenue goal, and the number of wins and opportunities needed to hit it (work backwards from ACV and win rate)
- Verdict: is ABM justified, and for which slice of accounts?
Exercise: Choose Your Model Mix
Map the three ABM models to your accounts and your actual capacity. Most beginners over-invest in one-to-one; right-size it to the people you have.
- List the handful of dream accounts that could warrant one-to-one (strategic) treatment.
- Sketch 2-3 clusters of similar accounts that could share a one-to-few campaign (what do they have in common?).
- Describe the broad good-fit list you would cover one-to-many (programmatic), and roughly how many accounts.
- Stress-test against capacity: how many true one-to-one accounts can each rep realistically run? Adjust tier sizes to fit.
Checklist: Readiness Gut Check
- Each target account is worth enough (deal size + lifetime value) to justify concentrated effort.
- Our sale involves multiple stakeholders and a cycle long enough to reward orchestrated touches.
- We can actually name the companies worth pursuing — the market is finite, not millions of anonymous buyers.
- We are not trying to replace all demand gen with ABM — broad demand gen still runs underneath.
- We are starting with a model mix we can staff, not a fleet of expensive one-to-one campaigns.
Picking the Right Accounts: ICP, Scoring, and Tiers
Build an ICP from your own won deals, score and tier a finite target account list, and map the buying group with real data.
Worksheet: Reverse-Engineer Your ICP from Won Deals
Do not invent the ICP in a meeting. Pull your best customers and find the firmographic traits they share, plus the anti-patterns of your worst-fit deals.
- Top 10 customers by value-and-retention (the ones you wish you had 100 more of)
- Shared industries / verticals across them
- Shared employee-size band and revenue band
- Shared technographics (CRM, cloud, ERP, or stack your product complements/replaces)
- Common situational triggers before they bought (funding, hiring, new exec, expansion, regulation)
- Disqualifiers — traits that make a company a BAD fit (too small, unsupported region, incompatible platform)
- One-sentence ICP a new rep could apply in seconds (specific enough to exclude most of the market)
Exercise: Score and Tier Your Account List
Turn the ICP into a finite, ranked list. Score every account on fit AND on intent, then split into tiers that match your model mix and capacity.
- Define your fit factors and point weights (e.g. industry 30, size 25, target tech 25, trigger 20).
- Define your intent/engagement factors (site visits, content downloads, ad engagement, third-party intent surges).
- Score a sample of accounts on both axes and place them on a fit-by-intent grid (high-fit/high-intent first).
- Assign tiers: Tier 1 (one-to-one, a few to a few dozen), Tier 2 (one-to-few clusters), Tier 3 (one-to-many) — and confirm tier sizes fit your team.
Worksheet: Map a Buying Group
Pick one Tier-1 account and name the six-to-ten real people who decide. Engaging only the friendly champion leaves the deal exposed.
- Account name and why it fits the ICP
- Decision maker / economic buyer (name + title)
- Champion — likely internal advocate (name + title)
- Influencers (names + titles)
- Evaluators / technical buyers — IT, security, procurement (names + titles)
- End users who affect adoption (roles)
- Blockers / gatekeepers (roles)
- Data sources used to find them (ZoomInfo / Apollo / Cognism / LinkedIn Sales Navigator) and whether titles were verified
Checklist: Selection & Data Quality Check
- My ICP came from real won-deal data, not a brainstorm, and explicitly names disqualifiers.
- My target account list is finite and counted — I can state the exact number.
- Every account is scored on both fit and intent, not chosen by gut.
- Tiers are assigned and sized to the people and budget I actually have.
- For Tier-1/2 accounts, the buying group is mapped to named people with verified titles, not one contact.
- Intent is used to prioritize good-fit accounts — never as the sole reason to pursue a poor-fit one.
Aligning Sales and Marketing
Make ABM a joint sport — one agreed list, shared definitions, a written SLA, and joint account plans that assign owners and next actions.
Worksheet: Agree the Shared Definitions
Most ABM failure is misalignment. Get marketing and sales to agree, in writing, on the words before the work. Fill this in together.
- The single agreed target account list (one list, not two)
- Definition of a Marketing Qualified Account (MQA): what account-level activity counts as ready for sales
- Stage definitions both teams will use (marketing-engaged, sales-engaged, opportunity, closed)
- Shared goals/metrics both teams are measured on (engaged accounts, pipeline, revenue)
- Channel ownership: who runs ads, content, email, outreach; who owns the account plan
Exercise: Draft the Marketing–Sales SLA
Put the alignment in a simple contract of mutual commitments with timeframes. This becomes your operating agreement.
- Marketing commitments: number of engaged target accounts per quarter, account intelligence, content, and air-cover campaigns.
- Sales commitments: follow up on every MQA within a set time (e.g. 24-48 hours), log activity/feedback in the CRM, execute the agreed outreach steps.
- The MQA threshold and what counts as accepted vs rejected by sales (and why).
- The feedback cadence (e.g. weekly) and the accountability metrics (MQA-to-opportunity rate, follow-up time, pipeline from the list).
Worksheet: Build a Joint Account Plan (Tier 1)
For one dream account, build the living document both teams work from so every touch is coordinated.
- Account overview: company, ICP fit, strategic value, current status
- Buying group map: named people, roles, and current engagement level
- Account goals and pain your solution addresses
- Plays and owners: the specific marketing and sales actions, who owns each, and the sequence
- Next steps with dates (so the plan drives activity, not dust)
Checklist: Alignment Check
- Marketing and sales work from ONE agreed target account list.
- We replaced the lead-based MQL with a jointly defined MQA and agreed what sales does when one appears.
- An SLA is written with mutual commitments and timeframes, not just good intentions.
- Tier-1 accounts have a joint account plan with named owners and next actions.
- There is a recurring (e.g. weekly) review where both teams walk the top accounts together.
- Both teams are measured on the same outcomes (engaged accounts, pipeline, revenue).
Plays, Channels, and Measuring What Matters
Run a personalized multi-channel play, then measure the program on account engagement, pipeline, win rate, deal size, and velocity — not leads and clicks.
Exercise: Design a Multi-Channel Play
Build one repeatable play for an account or cluster around a single relevant message. Match the personalization depth to the tier.
- Pick the target: one account (one-to-one) or one cluster of similar accounts (one-to-few), and state what they share.
- Craft the single message/theme and the proof point (peer case study, named pain, or trigger) you will lead with.
- Sequence the channels over ~4 weeks: targeted ads → tailored content → timed sales outreach → sustained air cover, with web personalization for known visitors.
- Set the personalization level (by segment / by cluster / bespoke) and note how you will reuse cluster-level personalization across accounts.
Worksheet: Build Your ABM Scorecard
Replace lead metrics with account-based metrics. Record a baseline first so you can prove lift versus non-target deals.
- Account engagement / coverage: % of target accounts engaging and avg people engaged per account
- Pipeline created from target accounts: number and dollar value of opportunities
- Win rate on target accounts vs non-target (baseline + current)
- Average deal size / ACV on target accounts vs non-target
- Sales velocity / cycle time for engaged vs unengaged target accounts
- Account-based ROI: pipeline and revenue from the program vs its cost (incl. expansion revenue)
Checklist: Pilot Launch & Pitfall-Avoidance Check
- I am starting with a focused pilot (e.g. 20-50 accounts, one aligned pod), not a big-bang rollout.
- Personalization is real and matched to tier — not just a company name dropped into a generic email.
- I report on pipeline, win rate, deal size, and velocity, with account engagement as the leading indicator.
- Sales and marketing share a single account view so neither operates blind or sends mixed signals.
- There is an operating rhythm: weekly account review, intent refresh, play iteration, MQA tuning, quarterly review.
- I will give the long B2B cycle time to convert engagement into closed revenue before judging the program.
Your Action Plan
- Run the fit-and-economics check on one product and segment, and decide whether ABM is justified and for which accounts.
- Reverse-engineer your ICP from your top won deals — capture firmographics, technographics, triggers, and explicit disqualifiers.
- Build a finite target account list from your CRM and a data provider (ZoomInfo / Apollo / Cognism), and count it.
- Score every account on fit and intent, place them on a fit-by-intent grid, and assign Tier 1 / 2 / 3 sized to your capacity.
- Map the buying group for each Tier-1/2 account — name the economic buyer, champion, evaluators, and blockers with verified titles.
- Get marketing and sales to agree on one list, a shared MQA definition, and common stage definitions, then write an SLA.
- Build a joint account plan for each Tier-1 account with named owners and dated next actions.
- Design one multi-channel play (ads → content → timed outreach → air cover) with personalization matched to the tier.
- Stand up an ABM scorecard with a baseline, and track engagement, pipeline, win rate, deal size, and velocity — not leads.
- Launch a 20-50 account pilot for a quarter, run a weekly account review, iterate on plays, and only scale what shows lift.
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