How to Identify and Prioritize Target Accounts for ABM

May 14, 2025

(Last updated 30 July 2026)

An ABM program is only as strong as its account list. The strategy, the content, the sales play, all of it depends on whether the right accounts are in the program to begin with.

Most teams know this in principle. In practice, account selection tends to be driven by sales intuition, existing relationships, or last year’s list with minor updates. The result is a pipeline skewed toward familiar names rather than high-fit opportunities.

This guide covers how to build a structured target account identification process — from defining the criteria that matter to scoring and segmenting accounts so your tier assignments reflect actual potential, not familiarity. For a full breakdown of how ABM tiers work and how to assign accounts to the right tier, see our dedicated guide on ABM Tiers: What They Are, How They Work, and How to Assign Them.

What Is a Target Account?

Target accounts are companies you have identified as the highest-fit, highest-potential opportunities for your business. In an ABM program, these are the accounts that receive focused, coordinated attention from both sales and marketing — not broad-based outreach, but deliberate engagement built around their specific situation and buying context.

The quality of your target account list determines where your program’s resources go. Getting this right is one of the most consequential decisions in ABM execution.

How To Identify Your Target Accounts

Before you can identify target accounts, you need a clear picture of what a high-fit account actually looks like. That starts with building an ideal customer profile (ICP).

An ICP describes the company — not the individual buyer — that is most likely to buy, retain, and expand with you. It captures firmographic characteristics, common technology environments, buying behaviors, and the business conditions that typically precede a purchase. Without a defined ICP, account identification becomes subjective and inconsistent.

Once your ICP is defined, identification becomes a structured process of finding companies that match it across multiple data dimensions.

5 Ways To Identify Target Accounts for ABM

1. Use your ABM technology stack. Account identification tools can surface companies matching your ICP based on firmographic filters, technographic signals, and in-market indicators. Predictive tools can add a timing dimension — identifying which accounts are actively researching relevant solutions.

2. Mine your existing database. Your CRM and marketing automation platform contain signals most teams underuse. Past opportunities, churned accounts, and current customers with expansion potential are all worth analyzing for patterns that sharpen your ICP and surface new targets.

3. Analyze your competitors’ customers. Tools like Enlyft and HG Insights can surface companies using competitive solutions. LinkedIn groups, review sites, and professional communities offer additional signal. Accounts already using a competing solution are often actively evaluating options.

4. Look at your best customers’ competitive landscape. Platforms like Owler provide competitive overviews of any business. Your best existing customers often have competitors that share similar profiles — making those competitors logical targets. This approach identifies accounts with a high structural fit based on real evidence rather than assumptions.

5. Monitor job postings for buying signals. Hiring activity is one of the most underused intent signals in ABM. If a company is hiring for roles that indicate a need for your solution — specific job titles, functions, or technology keywords — that hiring activity often precedes a purchase decision. Set up job alerts using relevant buyer persona titles and solution keywords to catch these signals early.

How To Tier Your Target Accounts

Once you have a list of target accounts, the next step is prioritization. Not all accounts warrant the same level of investment. Tiering allows you to allocate resources deliberately based on revenue potential, strategic value, and fit quality.

Most B2B organizations use a three-tier model: highest-fit, highest-value accounts in Tier 1 receiving the most resource-intensive, personalized treatment; strong but lower-value accounts in Tier 2 receiving a scaled approach; and accounts that meet most but not all ICP criteria in Tier 3 receiving a more programmatic, lower-touch engagement.

Real-World Example: How Invoca Tiered 4,500 Target Accounts

Invoca is a call intelligence platform whose marketing team, led by VP of Marketing Julia Stead, took a programmatic approach to ABM — using technology to identify and tier a large number of accounts at scale.

Selecting target accounts using technology

The Invoca team began with a combination of tools to surface accounts matching their ICP across firmographic and technographic dimensions. Key data points included paid search spend and web versus mobile traffic ratios — both relevant signals for a call intelligence platform.

Tools used included Datanyze for technographic data and buying signals, SimilarWeb for digital market intelligence and competitive list building, InsideView for account and decision-maker identification, EverString for AI-driven firmographic and technographic matching, and LinkedIn for validating third-party data against self-reported company information.

Tiering the master list

Technology handled identification, but prioritization required a human layer. Julia explains: “We felt that a human touch was needed to really identify our top tier of accounts. Just because they have this technology profile does not necessarily mean they’re a good fit for Invoca. A really key piece for us is, do they care about phone calls? Do they have a 1-800 number on their website? Do they have a call center? These are all attributes that aren’t necessarily available through predictive tools.”

For Tier 1, a cross-functional team from marketing and sales reviewed accounts manually. For Tier 2 and Tier 3, the team used automated scoring based on how many target attributes each account matched, then passed the lists to sales reps to identify their focus accounts.

The Invoca example makes a practical point that applies broadly: data gives you the list, but judgment shapes the top of it.