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outbound

ABM account engine

  • abm
  • outbound
  • b2b
  • account-based

Select the right accounts (adopt an existing scored list or build one), define exclusions, map the buying committee, coordinate LinkedIn ads + outbound as one experience per account, and measure at the account level, not the lead level.

Get access See how it runs
6 Steps in the flow
8 Tools orchestrated
2 Human checkpoints
Weekly Run cadence
15–40 / month Engaged target accounts

The objective

What this system is built to do

ABM isn't better targeting, it's a different game. Pick 50–200 accounts you intend to win, map every stakeholder in the buying committee, and coordinate outbound + LinkedIn ads into one coherent experience per account. Measure engaged accounts and pipeline, not MQLs.

Pick the accounts you intend to win, then surround every stakeholder in the buying committee with coordinated ads and outbound before the sales conversation starts. Not doing: generating MQLs, running 1,000-account 'ABM' lists, or handing off to sales without a committee map.

How it runs

The steps your team follows

The workflow, exactly as it runs inside . It plays through step by step, or pick any node on the map.

1Select & score target accounts
2Map the buying committee
3Launch LinkedIn committee ads
4Run coordinated outbound sequences
5Work intent alerts & replies
6Measure account engagement & refine
Start
1

Select & score target accounts

Weekly
  1. Start from a list, not a blank pull. If the team already has a scored target list, adopt and refresh it here rather than rebuilding, a client's hand-scored list (with call-prep intel and trigger events) usually beats a cold firmographic pull. Otherwise pull ICP-fit accounts from or on firmographic + technographic filters (industry, headcount, tech stack, growth signals).
  2. Define exclusions first. Write the negative criteria, who NOT to target and why (accounts you can't realistically penetrate, partner-channel accounts, live deals/pilots). Exclusions shape the list as much as inclusions.
  3. Enrich each account in , waterfall enrichment, hiring patterns, tech installs, recent funding.
  4. Overlay intent, two kinds, whatever is connected. (a) *Trigger events*, regulatory actions, M&A, leadership changes, incidents, often a stronger buying signal than digital intent in regulated/technical markets. (b) *Digital intent* on a graceful ladder, not a fixed toolset: person-level de-anon (/) → identified analytics visitors → company-level third-party research (/Bombora). Missing the premium tools does not block this step.
  5. Score on an explicit, editable model. Publish the formula + weights as a tunable artifact (e.g. Penetrability × w1 + Ability-to-Serve × w2, with per-sub-segment priors) rather than a generic "fit × intent." Then tier: T1 (≤25, 1:1), T2 (10–50 per cluster, 1:few), T3 (100–500 programmatic).
  6. Human approval, review and approve the tiered list, the scoring weights, and the exclusions before committee mapping begins.
2

Map the buying committee

Weekly
  1. For T1 accounts, identify Champion, Economic Buyer, and ≥1 Influencer, minimum 3 stakeholders. Instantiate this archetype for your ICP (write the actual roles, e.g. "Champion = Head of Integrity; Economic Buyer = VP Ops/CIO; Influencer = IT-Security").
  2. In regulated or technical verticals the Compliance / Security / Legal stakeholder is a GATE, not just an influencer, they can veto (SOC2/ISO, safety/regulatory, procurement security review). Map and warm them early, not at procurement.
  3. For T2 cluster accounts, map Champion + Economic Buyer per account; use to enrich contact profiles and verify emails.
  4. For T3 accounts, pull all ICP-role contacts from , at least 2 per account.
  5. Log the committee map in the CRM; flag single-threaded accounts as at-risk.
  6. Use person-level site identification (, or identified analytics where RB2B isn't connected) to catch uncontacted stakeholders already visiting the site.
3

Launch LinkedIn committee ads

Weekly
  1. Upload the committee contacts list as a Matched Audience (CSV upload; minimum 300 contacts, combine T1+T2 lists to hit the threshold).
  2. Run a Sponsored Content campaign with one coherent asset per cluster. Match the asset to the tier on the content resource-intensity ladder: T3 = broad pain-point / industry content; T2 = segment or company-size benchmark / teardown; T1 = hyper-personalised or bespoke.
  3. Set budget by tier against a resourcing model (see the playbook's *Resourcing & scale* section) so account count and spend stay consistent: T1 warrants higher CPM bids; T2 clusters run at standard rates.
  4. Let the campaign run for 3 weeks before outbound sequences launch, the pre-warming window.
  5. Monitor frequency per stakeholder; pause accounts where an individual has seen the ad 8+ times without engaging.
4

Run coordinated outbound sequences

Weekly

Owner (suggested): Sales / AE.

  1. For T1 accounts: personalised AE-signed email to Champion and Economic Buyer simultaneously, referencing the same asset as the LinkedIn ads. Opener = one specific insight from their company or role, sourced from enrichment.
  2. For T2 clusters: semi-personalised sequences via or , cluster theme + asset, not a generic product pitch.
  3. For T3: full-sequence automation from , fire only on accounts that hit the engagement threshold (ad click + email open + pricing page visit).
  4. Interrupt all sequences immediately on a reply, don't let automation continue after a human conversation starts.
  5. High-touch plays for T1 (run as time-boxed experiments): an invite-only roundtable/workshop for the committee, and/or a bespoke per-account report, the two highest-converting motions in the field. Spin these up as initiatives off this step.
  6. Human approval, T1 account touches require AE approval before send.
5

Work intent alerts & replies

Daily

Owner (suggested): Sales / AE.

  1. Monitor intent alerts from the best source connected, person-level de-anon (/) where available, otherwise identified analytics visitors and company-level triggers. Any target-account signal on pricing/solutions (or a fresh regulatory/M&A trigger) fires an immediate Slack notification.
  2. Set the SLA by signal precision: a person-level signal (named stakeholder on pricing) = respond within 4 hours with a personalised touch; a company-level or lower-confidence signal = same-day / daily digest, don't burn AE time chasing noise.
  3. Work all replies across channels: classify as Interested / Not now / No; route Interested to a fast booking link or two suggested times.
  4. escalate any multi-stakeholder reply thread needing strategic judgement.
  5. Log the sourcing signal (which trigger preceded the reply) for the measurement step.
6

Measure account engagement & refine

Weekly

Owner (suggested): Marketing-ops. This step doubles as the weekly sales–marketing account review.

  1. Compute the weekly engaged accounts count: target accounts with ≥2 stakeholders active in the last 30 days (any channel, ad impression + open counts; meeting = definite).
  2. Track the full account-level scoreboard, not just engagement: pipeline influenced (£/$ of opps with a prior ABM touch), win rate vs unengaged baseline, average buying-committee size, account velocity (days first-touch → opp), and cost per engaged account.
  3. The win-rate / velocity comparison is the business-case number, report it to the shared sales + marketing forum.
  4. Review which signals and clusters produced the most engaged accounts; cut clusters that aren't moving.
  5. Update the target account list, scoring weights, T1/T2/T3 thresholds, and the promoted asset; feed changes into next week's account-selection step.
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Setup

The stack

The tools this system drives, and the context you bring once. Connect your own accounts, or swap in your team's equivalent.

Tools to connect

ApolloFree – $99 / mo Powers Select & score target accounts Or Clay, ZoomInfo
LinkedIn Sales Navigatorfrom $99 / mo Powers Select & score target accounts Or HeyReach, Expandi
Clayfrom $149 / mo Powers Select & score target accounts Or Clearbit, Apollo
RB2BFree – $149 / mo Powers Select & score target accounts Or Koala, Clearbit
KoalaFree – $50 / mo Powers Select & score target accounts Or RB2B, Clearbit
6senseCustom Powers Select & score target accounts Or Demandbase, Clearbit
Instantlyfrom $37 / mo Powers Run coordinated outbound sequences Or Smartlead, Lemlist
HeyReachfrom $79 / mo Powers Run coordinated outbound sequences Or Expandi, Dripify

Context to bring

Your documents 4 files
  • Target account list The named accounts, tiered, with the buying committee mapped.
  • ICP & fit criteria What makes an account a fit, and what disqualifies it.
  • Tone & messaging The per-persona angles and the voice for outreach.
  • Offer & proof The positioning and proof that lands with each tier.

Proven in market

Run by 63 teams, verified on real accounts

ABM account engine is built and verified by Growth Division, the GTM team behind 150+ companies. Here is what the same play has produced for their clients.

+£48k ARR after rebrand + ABM

Maji · B2B

First enterprise deal, £2.5m revenue

LUX Rewards · Loyalty / Rewards

Repositioned for the heat-pump market

Clade · Energy / Hardware

Built & verified by Growth Division

What we've learned running it hundreds of times

The small, hard-won details that decide whether it works, from every run.

3× win rate vs unengaged accounts
40% shorter sales cycles
3+ stakeholders per target account
win rate high confidence
Before 18%
After 38%

Multithreading the buying committee doubled win rate

A single-threaded ABM play is just expensive cold outreach. The win-rate premium comes from the Economic Buyer being warm before procurement starts, that only happens if marketing has been running coordinated touches to the whole committee, not just whoever replied to the SDR.

Cohort A/B (single-thread vs multi-thread)n≈40 target accounts12 weeks
days to opportunity high confidence
Before 47
After 19

Triggering outbound on person-level intent cut time-to-opportunity

Intent data isn't primarily a targeting tool, it's a timing tool. The account was already going to evaluate you; the signal just tells you to move now instead of in three weeks. An AE with a 4-hour SLA on intent alerts will always outperform one running a fixed cadence.

Intent-trigger vs baseline cadencen≈60 intent-triggered touches10 weeks
Champion reply rate medium confidence
Before 8%
After 21%

LinkedIn Matched Audiences on the full committee lifted outbound reply rate

Running ads to a buying committee 3 weeks before the SDR emails is not a nice-to-have, it's the mechanism. The ad impression doesn't book the meeting; it earns the email a response. The cost of warming a 4-person committee on LinkedIn for 3 weeks is modest relative to the uplift in reply rate.

Pre-warming cohort vs cold-startn≈18 accounts, fintech cluster6 weeks
The full lab notebook Every experiment charted, with the raw before/after and the decision rules behind each call. Unlock free

Get started

How to run this system

Live in an afternoon. Clone it, connect your tools, set your inputs, and turn it on.

  1. 1

    Add to

    Clone the ABM account engine into your workspace, wired end to end.

  2. 2

    Connect your tools

    Apollo, LinkedIn Sales Navigator, Clay +5 more.

  3. 3

    Set your inputs

    Your ICP, targets and brand rules, once.

  4. 4

    Turn it on

    It runs weekly on autopilot, checking in with you only where it matters.

~45 min / week your time on autopilot · vs 12–16 hrs / week by hand
15–40 / month Engaged target accounts, produced for you

Early access

Run the ABM account engine in your workspace.

is in stealth with a first cohort of scaleups. Join the waitlist and we’ll open this system, and the full library, to you first.

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