ABM Lookalike Targeting

Build a tiered ABM target list from your best customers. Takes the top closed-won accounts from whichever CRM is connected, expands each into lookalike companies via Firmable, scores them for fit, and excludes anyone who’s already a customer.

Works with HubSpot, Salesforce, Pipedrive, or MS Dynamics 365 Sales. The skill detects your CRM automatically, so the same workflow runs regardless of what your team uses to track deals. You end up with three tiered lists saved in Firmable, ready to hand to sales or push straight into the CRM.

What It Does

• CRM-agnostic detection: Reads closed-won deal data from HubSpot, Salesforce, Pipedrive, or MS Dynamics 365 Sales without assuming which one you run.
• Aggregate-value ranking : Ranks seed accounts by total closed-won value per company, not per deal, so your true best customers anchor the list.
• Free lookalike expansion: Runs each seed through Firmable’s similarity engine to surface companies that look like your winners.
• Overlap-based scoring: Tiers candidates by how many different closed-won accounts they resemble, the strongest fit signal available, with rank as a tiebreaker.
• Automatic exclusion: Drops seed accounts and existing customers from the candidate pool so every list is genuinely net-new.
• Ready-to-use output: Saves three tiered lists in Firmable and prints a summary table in chat, with an option to push Tier 1 straight to the CRM.

Use Cases

---
name: abm-lookalike-targeting
description: Build a tiered ABM target list by taking the top closed-won accounts from whichever CRM is connected (HubSpot, Salesforce, Pipedrive, MS Dynamics 365 Sales), finding lookalike companies in Firmable, scoring them for fit, and excluding existing customers. CRM-agnostic — detects the connected CRM rather than assuming HubSpot. Use this skill whenever the user asks to build an ABM list, find similar companies to our best customers, expand pipeline using lookalikes, build a Q3 (or any quarter) target list, or anything along the lines of "find companies like our top accounts" or "who should we be targeting next". Trigger on phrases like "ABM target list", "lookalike accounts", "find companies similar to our customers", "net-new target list", or "tiered target list".
---

# ABM lookalike targeting

Take the top closed-won accounts from whichever CRM is connected, expand each into lookalike companies using Firmable's find_similar_companies, score the net-new candidates for fit, and produce a tiered target list saved to Firmable lists with a summary table in chat.

## Workflow

0. Detect the connected CRM — check loaded tools or search for one; HubSpot and other CRMs each follow a dedicated reference file for query syntax.
1. Pull the top N closed-won accounts from the CRM, ranked by aggregate deal value per company.
2. Resolve each seed account to a Firmable company id via bulk_get_companies (credit-charged) or a free name-based filter_search fallback.
3. Expand each seed into lookalikes with find_similar_companies (free), tracking overlap_count and best_rank per candidate.
4. Remove the seeds themselves and any existing customers from the candidate pool.
5. Score and tier the survivors: Tier 1 (overlap 3+), Tier 2 (overlap 2), Tier 3 (overlap 1, ranked by best_rank, capped around 150 total).
6. Save each tier to a Firmable list, reusing existing lists where they already exist.
7. Present a summary table in chat and offer to push Tier 1 to the CRM.