Build and run an account-based marketing program end to end: decide if ABM fits, score and tier target accounts, map the buying committee, run full orchestrated plays across marketing and sales, and measure account coverage, penetration, and pipeline against a non-ABM comparison group. Use when someone asks to start or fix an ABM program, tier a target account list, build an account scoring model, plan a one-to-one or one-to-few campaign, coordinate sales and marketing on named accounts, or report ABM results. For a single atomic play note or one cold email, use an outreach skill instead; this skill ships the whole program.
./install.sh abm-playbookname: abm_playbook description: "Build and run an account-based marketing program end to end: decide if ABM fits, score and tier target accounts, map the buying committee, run full orchestrated plays across marketing and sales, and measure account coverage, penetration, and pipeline against a non-ABM comparison group. Use when someone asks to start or fix an ABM program, tier a target account list, build an account scoring model, plan a one-to-one or one-to-few campaign, coordinate sales and marketing on named accounts, or report ABM results. For a single atomic play note or one cold email, use an outreach skill instead; this skill ships the whole program."
Account-based marketing treats a small set of high-value accounts as the unit of work. Marketing and sales pick the accounts together, learn how each account buys, run coordinated plays against the whole buying committee, and judge the program on pipeline and revenue from those accounts, not on lead volume.
This skill produces a working program, not a strategy memo: a scored and tiered account list, a buying committee map, at least one full play per tier with owners and timing, an orchestration calendar, and a measurement sheet with definitions written down.
The three program models, from the ITSMA typology that most ABM practice follows:
| Model | Also called | Shape | Personalisation | |---|---|---|---| | Strategic ABM | 1:1 | A handful of top accounts, each handled on its own | Custom research, custom content, executive contact | | ABM Lite | 1:few | Clusters of similar accounts (shared industry, pain, or tech stack) | Cluster-level content adapted from existing assets | | Programmatic ABM | 1:many | Hundreds of accounts | Rules-based personalisation, intent-triggered touches, ads and automated sequences |
Most real programs run all three at once, one per tier. Match the model to account value and to the hours the team actually has. A Tier 1 promise made to 200 accounts is a Tier 3 program wearing a costume.
ABM costs more per account than broad demand generation. It pays back only when most of these hold:
If almost anyone can buy the product and deals close fast with one buyer, broad campaigns will beat ABM on cost. Say so and stop.
Define the ideal customer profile in fields a CRM or data provider can actually filter on:
Pull the criteria from the last 10 to 20 closed-won and closed-lost deals, not from opinion. Note which criteria came from wins and which from losses.
Score fit separately from timing. A perfect-fit account with no trigger is a nurture account. A mediocre-fit account showing active research is a fast follow, not a Tier 1 account.
Starting model (calibrate it in step 8, the weights are a method, not a law):
| Dimension | Points | What earns points | |---|---|---| | Firmographic fit | 0 to 35 | Industry, size, revenue, and geography against the ICP | | Technographic fit | 0 to 20 | Complementary stack present, integration path clear, competitor due for renewal | | Intent and triggers | 0 to 25 | Research on relevant topics, visits to high-value pages, trigger event in the last 90 days | | Relationship | 0 to 20 | Known contacts, past meetings, partner overlap, prior deal history |
Total 100. Worked thresholds to start from: 75 and up is a Tier 1 candidate, 55 to 74 is Tier 2, 35 to 54 is Tier 3, under 35 stays out of the program and gets normal inbound and outbound only.
Score with the helper instead of by hand when the list is longer than a screen:
bash
python3 ~/workspace/skills/abm-playbook/bin/score_accounts.py accounts.csv --tier1-cap 15
Input columns and rules are in the script header. The cap matters: if 60 accounts clear the Tier 1 threshold but the team can run true one-to-one work on 15, the top 15 by score get Tier 1 and the rest drop to Tier 2. Capacity sets the tier, the score only ranks.
Record for each account: tier, owner, score, the trigger or reason it made the list, and the date it entered. Both sales and marketing leads sign the list in the same document. An unsigned list gets ignored within a month.
Re-tier on a fixed cadence: review intent and triggers monthly for Tier 2 and 3, quarterly for the full list. Promote on a real signal (intent spike, new champion, trigger event). Demote after a full quarter with no engagement and no trigger. Freeze the list during an active play so reporting stays honest.
For each Tier 1 and Tier 2 account, fill the committee map (template in assets/account-plan.md):
For each person record what they care about, what proof they need, and the one asset or conversation that serves them. A map with only the economic buyer filled in is a single point of failure. Target at least three engaged roles per Tier 1 account before calling the account covered.
Research rule: personalisation must come from a checkable source (the account's own site, a filing, a job post, a public talk, CRM history). Never invent an account's priorities, stack, or headcount plans. If the research comes back thin, personalise to the cluster problem instead and say so in the plan.
One page per Tier 1 account, one per Tier 2 cluster. Fields are in assets/account-plan.md. The plan states: the account's situation in two or three sourced sentences, the problem hypothesis, the committee map, the play chosen, the first three touches with dates and owners, the offer that earns a meeting, and the exit rule if nothing moves.
A play is a timed sequence of touches by several people on your side aimed at several people on theirs. It is not a single email or ad. The full play library is in references/plays.md. It covers:
Orchestration rules for every play:
Use the orchestration sheet in assets/orchestration-template.md to lay out a play week by week before launch.
Define these before launch, in writing, with the formula and the data source for each (full sheet in references/measurement.md):
Always report program accounts next to a similar set of non-program accounts from the same period. Without that comparison the numbers describe activity, not effect. Review engagement weekly, pipeline monthly, win rate and cycle length quarterly. Engagement with no pipeline movement after two quarters means the plays or the list are wrong. Change one of them, on purpose, and note the change.
After each quarter, and after every five closed deals from the program:
A finished run delivers all of these:
assets/account-plan.md.assets/orchestration-template.md, with named owners, dates, and exit rules.publisher key 2e43c913833850e6d80f939677e3de76e806d47785c0f1caaca90f9d18c98e1e
No ratings yet — be the first to rate it.