Account-Based Data: Building Data for ABM Campaigns

I still remember the first time I saw an ABM campaign fall apart. The company had identified 1,000 “target accounts” and sent one email to one person at each company. They called it account-based marketing, but really, it was just regular email marketing with fancier reporting. The results? Predictably terrible.

The fundamental mistake was treating ABM like demand gen with different labels. ABM requires a completely different approach to data—one that prioritizes depth over breadth, quality over quantity, and strategic precision over mass outreach.

Why ABM Data Is Different

Traditional demand generation focuses on volume. You cast a wide net, capture as many leads as possible, and let your funnel sort out who’s actually qualified. It’s a numbers game where individual contact data matters most.

Account-based marketing flips this on its head. Instead of thousands of individual leads, you’re targeting hundreds of specific accounts. Instead of one contact, you need coverage across the entire buying committee. Instead of broad demographic targeting, you need precise firmographic and technographic alignment.

Think about it this way: in demand gen, getting one email address from Microsoft is a win. In ABM, you need the VP of Engineering, the Director of DevOps, two engineering managers, and a couple of team leads—all from the specific division you’re targeting. That’s not just different, that’s an entirely different ballgame.

The Four Layers of Account-Based Data

Effective ABM requires four distinct layers of data, each serving a specific purpose in your go-to-market strategy.

Layer 1: Firmographic Data for Targeting

Firmographics are your foundation. This is how you identify which companies actually match your ideal customer profile. We’re talking industry, company size, revenue, location, and growth stage.

Here’s a real example: one of our clients sells developer tools to mid-market B2B SaaS companies. Their ICP filter looks like this: B2B SaaS companies with 200-2000 employees, $20M-$200M in revenue, based in the US, UK, or Canada, and at least Series B funded. These criteria immediately narrow their universe from millions of companies to a few thousand potential targets.

The key is specificity. “Technology companies” is too broad. “B2B SaaS companies with engineering teams of 50-200 people” is actionable. The more precise your firmographic criteria, the better your targeting will be.

Layer 2: Technographic Data for Relevance

Technographics tell you what technology a company uses. This is gold for ABM because it lets you target companies based on their actual tech stack, not just their industry or size.

Let’s say you sell a data pipeline tool that integrates with Snowflake. You can specifically target companies that use Snowflake but don’t have a robust data pipeline solution. Or if you have a competitor, you can target companies using that competitor’s tool who might be open to switching.

One marketing team I know uses technographics to identify “trigger moments.” They target companies that just implemented Salesforce, because those companies are usually in a growth phase and actively building out their go-to-market tech stack. Perfect timing for their sales engagement platform.

The sophistication of a company’s tech stack also tells you about their maturity. A company using HubSpot, Salesforce, ZoomInfo, and Gong is probably more sophisticated than one using basic tools. This helps you customize your messaging and positioning.

Layer 3: Intent Data for Prioritization

Not all target accounts are created equal. Some are actively researching solutions right now. Others won’t be in-market for another year. Intent data helps you identify which accounts are showing buying signals.

Account-level intent signals include things like researching your category on review sites, consuming content about problems you solve, visiting competitor websites, and engaging with related topics on social media. When you see a target account showing high intent, that’s your cue to prioritize them.

Here’s how one company uses intent tiering: Tier 1 accounts are high intent plus perfect ICP fit—these get personalized campaigns and immediate sales outreach. Tier 2 accounts are medium intent with good ICP fit—these get automated nurture with personalized touches. Tier 3 accounts are ICP fit but no intent yet—these get awareness campaigns and patient nurturing.

Intent data isn’t perfect, but it’s dramatically better than guessing which accounts to prioritize. The companies showing research behavior are significantly more likely to be in-market than those showing zero signals.

Layer 4: Relationship Data for Warm Introductions

The warmest paths to an account are through existing relationships. Relationship data tracks who at your company knows who at the target account, whether you’ve had past interactions, if they’re a former customer, or if you have mutual connections.

I’ve seen deals accelerate by months just because someone found out they went to college with the VP at the target account. Or because a former customer now works there and can make an introduction. These warm connections are incredibly valuable.

Track relationship indicators like former customer employees at target accounts, executive connections through LinkedIn, partner company relationships, and event attendees who’ve interacted with your brand before. When you’re planning outreach to an account, always check for warm paths first.

Building Contact Coverage: The Buying Committee

Here’s where most ABM programs fail: they identify great target accounts but only reach one person. Then they wonder why deals stall or go dark.

B2B buying decisions aren’t made by individuals—they’re made by committees. Research from Gartner shows the average B2B buying committee has 6-10 people. If you’re only talking to one person, you’re missing most of the conversation.

Who You Need on Your List

A typical B2B buying committee includes several key roles. The Economic Buyer is the person with budget authority—usually a VP, Director, or C-level executive. This is the person who ultimately says yes or no to the purchase.

The Champion is your internal advocate. They’re typically a manager or senior individual contributor who sees value in your solution and will push for it internally. Champions are critical—deals without champions rarely close.

Influencers are people who have input on the decision. They might be team leads, specialists, or other stakeholders who will be affected by the purchase. They don’t have final authority, but they can definitely derail a deal.

Users are the people who will actually use your product day-to-day. In some organizations they have significant influence. In others, they’re not consulted much. Know the difference.

And don’t forget potential Blockers like procurement or legal. You might not sell to them directly, but knowing who they are and what they care about can prevent last-minute surprises.

The Coverage Target: 4-8 Contacts Per Account

For most B2B companies, 4-8 contacts per account is the sweet spot. That usually gets you 1-2 decision makers, 2-3 influencers, 1-2 potential champions, and maybe a user or two.

Enterprise deals with complex buying processes might need 10-15 contacts. Simple products with shorter sales cycles might only need 3-4. The key is covering the buying committee, not just hitting an arbitrary number.

Here’s how one company approaches this: For each target account, they identify the likely buying committee based on company size and structure. For a 500-person SaaS company, they might target the VP Engineering (economic buyer), Director of DevOps (champion potential), two Engineering Managers (influencers), and a DevOps Lead (user). That’s five contacts, all strategically chosen.

How to Build Your ABM Target Account List

Let’s walk through the practical process of building a target account list from scratch.

Start With Your ICP Criteria

You can’t build a good target list without a clear ideal customer profile. Define your must-have criteria—the non-negotiables that determine whether an account is even worth considering. For most B2B companies, this includes industry verticals, employee count range, revenue range, and geography.

Then define your “strong fit” criteria. These are the characteristics that make an account particularly attractive—things like specific technology usage, growth indicators, or lack of competitor usage.

One company I worked with required accounts to be in financial services, healthcare, or e-commerce (industry), have 500-5000 employees (size), generate $50M-$500M in revenue (budget capacity), and be based in North America (territory). Those were their must-haves.

Their strong fit criteria included using Salesforce (because they integrate), showing growth signals like recent funding or hiring sprees, and not currently using their main competitor. Accounts that hit both must-haves and strong fits got prioritized.

Generate and Score Your Initial List

Use a data platform like ZoomInfo, Apollo, or LinkedIn Sales Navigator to query companies matching your ICP criteria. Start broad—pull 500-1000 accounts that meet your basic criteria.

Then score and rank them. A simple scoring model might allocate 40 points for ICP fit, 30 points for intent signals, 20 points for existing relationships, and 10 points for strategic value. Accounts scoring 80+ become Tier 1 (highest investment), 60-80 become Tier 2 (moderate investment), and 40-60 become Tier 3 (programmatic approach).

This scoring helps you focus resources appropriately. Your best accounts deserve personalized campaigns, dedicated sales attention, and significant investment. Lower-tier accounts get more automated approaches.

Get Sales Alignment

This step is critical and often skipped. Review your target account list with sales before you commit to it. Sales will have insights you don’t have—they might know that a company is already a customer, or that you’ve lost deals there before, or that a particular account is strategically important.

Sales might also add accounts you missed. Maybe there’s a major prospect they’ve been trying to break into, or a former customer they want to win back. Joint account selection between marketing and sales ensures everyone’s working toward the same goals.

Territory assignments matter too. Make sure accounts are aligned to the right sales reps based on geography, industry expertise, or existing relationships.

Expand Contact Coverage

Once you have your target account list, it’s time to build out contact coverage. For each account, identify the likely buying committee based on company size and structure. Then find those specific people.

Use tools like ZoomInfo or Apollo for initial contact discovery, LinkedIn for verification and additional research, and enrichment services to verify emails and find direct dial numbers. Prioritize contacts based on their role in the buying process—economic buyers and potential champions first, then influencers, then users.

For a Tier 1 account, you might spend an hour researching the buying committee, finding the right people, and gathering intelligence about them. For a Tier 3 account, you might spend five minutes pulling standard contacts. The investment should match the account value.

Keeping Your ABM Data Fresh

Here’s an uncomfortable truth: B2B data decays fast. People change jobs. Companies get acquired. Contact information becomes outdated. If you’re not actively maintaining your ABM data, it’s getting worse every day.

The Continuous Enrichment Model

Different types of data need different refresh cadences. Intent signals should be updated daily or weekly—they’re real-time indicators of buying behavior. Job change alerts should be weekly so you know when your champion left the company or when a new decision-maker arrives.

News and trigger events should be monitored daily. Firmographic data like company size and revenue can be refreshed monthly. Contact data including emails and phone numbers should be verified monthly to catch bounces and changes.

Set up automated triggers for data refresh. When a sales rep views an account in your CRM, trigger a data refresh. When you detect engagement from an account, refresh their data. If it’s been 90 days since the last refresh, refresh it. When you get a job change alert, refresh that contact and find their replacement.

The Data Quality Process

Establish a regular cadence for data maintenance. Weekly, monitor email bounces, review engagement patterns, and check for intent changes. This keeps you aware of immediate issues.

Monthly, refresh contact data across your target accounts, verify email addresses, update firmographic information, and add new contacts to fill gaps in buying committee coverage.

Quarterly, do a comprehensive list review. Re-tier accounts based on updated scoring. Remove accounts that have churned, been acquired, or are no longer a fit. Add new targets that have emerged. This prevents your target list from becoming stale.

Common ABM Data Mistakes to Avoid

I’ve seen these mistakes kill ABM programs. Learn from others’ failures.

The first mistake is targeting too many accounts. Companies get excited about ABM and create lists of 5,000 “target accounts.” That’s not ABM, that’s just marketing with account-level reporting. Real ABM focuses on 100-500 accounts with significant depth and personalization. Quality over quantity.

The second mistake is single-threading. Reaching only one person per account is a recipe for stalled deals. You need buying committee coverage—4-8 contacts per account for most B2B companies. Multi-threading is essential.

The third mistake is letting data go stale. I’ve seen companies running ABM campaigns with contact data that’s two years old. Bounce rates are terrible, information is wrong, half the people have changed jobs. Target accounts deserve fresh data. Invest in continuous enrichment.

The fourth mistake is ignoring intent data. Treating all target accounts the same regardless of buying signals is inefficient. Intent data helps you prioritize which accounts to focus on now versus which to nurture for later.

The fifth mistake is poor sales alignment. When marketing’s target account list doesn’t match sales priorities, nobody’s happy and results suffer. Joint account selection and regular alignment are critical.

The Tools That Power ABM Data

You’ll need several types of tools to execute effective ABM data strategies.

For account selection and firmographic data, platforms like ZoomInfo, Apollo, Clearbit, and LinkedIn Sales Navigator each have strengths. ZoomInfo offers comprehensive filtering and deep data coverage. Apollo provides good value with solid filtering capabilities. Clearbit excels at real-time data enrichment. LinkedIn is unmatched for role-based discovery and research.

For intent data, consider platforms like Bombora (largest intent data network), G2 (review site intent signals), 6sense (predictive analytics combined with intent), or Demandbase (intent integrated into a full ABM platform).

For full ABM orchestration, platforms like Demandbase, 6sense, Terminus, and RollWorks provide comprehensive capabilities including account identification, contact discovery, intent monitoring, and multi-channel campaign execution.

The right tool stack depends on your budget, team size, and ABM maturity. Early-stage ABM programs might start with just a contact data platform and manual processes. Mature programs often invest in dedicated ABM platforms with intent data and orchestration capabilities.

Making ABM Data Work

Account-based marketing is fundamentally about focus. Instead of spray-and-pray tactics across thousands of leads, you’re concentrating resources on hundreds of carefully selected accounts. But that focus only works if you have the right data.

You need firmographic data to identify the right accounts. Technographic data to understand their environment and find relevant angles. Intent data to prioritize which accounts are in-market right now. And relationship data to find warm paths into those accounts.

Then you need contact-level data covering the entire buying committee—not just one person, but 4-8 contacts representing different roles in the decision-making process. Economic buyers, champions, influencers, and users all play a part.

And you need to keep that data fresh through continuous enrichment. ABM accounts deserve higher data maintenance investment than your general database. Stale data on target accounts costs real opportunities.

The companies that win at ABM are the companies that invest in account intelligence. They know their target accounts deeply. They have comprehensive buying committee coverage. They prioritize based on intent signals. And they maintain data quality as a core discipline, not an afterthought.

Key Takeaways

ABM data requires a fundamentally different approach than traditional demand generation. Here’s what matters most:

• ABM needs both account-level data (firmographics, technographics, intent) and contact-level data (buying committee coverage, verified contact information)
• Target 4-8 contacts per account to ensure you’re reaching the full buying committee, not just single-threading into one person
• Intent data helps you prioritize which accounts to focus on right now versus which to nurture for later engagement
• Quality beats quantity in ABM—deep data on 300 accounts is more valuable than shallow data on 3,000 accounts
• Continuous enrichment keeps your data fresh, with different refresh cadences for different data types (daily for intent, monthly for contacts, quarterly for full list reviews)

The best ABM programs are powered by the best account intelligence. Data depth, buying committee coverage, and continuous maintenance separate successful programs from those that struggle.

Ready to Build Better ABM Data?

We’ve helped hundreds of companies build and maintain high-quality account data for their ABM programs. Whether you’re just starting with account-based marketing or looking to improve an existing program, we can help you get the account intelligence you need.

Book a call with our team to discuss your ABM data strategy and how we can help you achieve better coverage, fresher data, and more effective targeting.