How to Build a Target Account List
I've been handed a lot of target account lists over the years. Some were pretty good. Plenty were not.
Usually the problem wasn't the strategy. Everyone generally agreed on who we wanted to target. The problems started when that strategy became a spreadsheet.
Missing domains. Duplicate companies. Subsidiaries mixed with parent companies. Companies that clearly didn't fit the ICP. Websites that didn't exist anymore. And, of course, the occasional "target" account list with tens of thousands of companies on it.
That's part of the reason we've built some of the tools we have at afterSpark.
A good target account list isn't just a list of companies that match a few filters. It should represent the companies you actually want to go after, and the underlying data needs to be good enough to use once that list hits your CRM, ad platforms, sales workflows or whatever else you're doing with it.
So this is how I think about building one.
What is a target account list?
A target account list (TAL) is simply the list of companies your sales and marketing teams have decided to prioritize.
Your ideal customer profile (ICP) describes the type of company you want. Your TAL names the actual companies.
If your ICP is US-based B2B software companies with 100–1,000 employees and $10M–$250M in revenue, that's your criteria. The actual companies that fit those criteria become the starting point for your TAL.
I say starting point because finding the companies is really only half the job.
1. Figure out who you actually want to target
This sounds obvious, but I'd spend more time here than most teams do.
Start with the characteristics that genuinely make a company a good fit for what you sell. Industry, geography, employee size and revenue are usually a good place to begin. Depending on your business, headquarters, company type, technology or other characteristics might matter too.
The key is figuring out what actually separates your good customers from everyone else.
And I wouldn't go crazy with filters.
I've seen teams make an ICP so specific that almost nobody qualifies. More data doesn't automatically mean better targeting. Start with the handful of characteristics you know matter and build from there.
There's also an important distinction between fit and timing.
If a company matches your ICP, it's probably worth having in your target universe. Intent, website activity, previous sales conversations and other signals can then help you decide which of those companies deserve attention right now.
I wouldn't use intent to fix bad fit. If a company that has absolutely no reason to buy from you visits your website five times, it's still probably not a great target.
Fit tells you who belongs. Signals help you decide who to prioritize.
2. Build the actual company list
Once you know what you're looking for, you need the companies.
Those can come from all over the place: your CRM, sales reps, existing customers, event lists, industry lists, company databases, partners or manually selected strategic accounts.
Or you can start from the criteria themselves.
We built our B2B Audience Builder for exactly this. You can start with geography and industry, then narrow the audience using company size or revenue.
I wouldn't worry about making the first version perfect. At this stage, you're trying to establish the universe of companies that reasonably fit what you're looking for.
Say that leaves you with 2,000 companies.
Great. You have a list.
Now we need to figure out whether it's any good.
3. Get the company data right
This is where I've seen a lot of target account lists fall apart.
The spreadsheet may look fine to a person, but the data underneath it is inconsistent.
You might have Microsoft, Microsoft Corp., Microsoft Corporation and microsoft.com scattered across different systems. A human knows those are probably referring to the same business. Your CRM isn't always so clever.
That's one of the reasons I like using domains as a foundation for company identity. They're not perfect — parent companies, subsidiaries and companies with multiple domains can still make things messy — but they're a hell of a lot more consistent than company names alone.
If someone hands you a list with company names but no domains, we built a free Company Name to Domain Finder that does exactly what it says on the tin. Upload the names, get the domains back, and move on with your life.
Of course, domains don't solve everything. Acquisitions, corporate structures and changes over time can still make things interesting. That's B2B data.
But now we have a much better foundation.
Add the company information you actually need
Once you have a reliable company and domain, you can start enriching the accounts with useful firmographic information.
That might include:
- Industry
- Employee size
- Revenue
- Headquarters and location
- NAICS or SIC classification
- Company type
- LinkedIn company URL
If you already have the domains, our Company Lookup by Domain can return available firmographic data for the companies behind them.
The important part here isn't collecting as much data as possible. It's collecting data you're actually going to use.
If employee size determines whether an account fits your ICP, get employee size. If geography determines sales territory, get headquarters information. If nobody on your team has any idea what they're going to do with a particular field, you probably don't need it just because somebody can sell it to you.
What should actually be in a TAL?
There's no perfect template, but I'd usually want something along these lines:
| Field | Why I'd want it |
|---|
| Company name | Obvious, but let's start there |
|---|
| Domain | A consistent way to identify the company |
|---|
| Industry | Qualification and segmentation |
|---|
| Employee size | ICP fit |
|---|
| Revenue | ICP fit |
|---|
| HQ / location | Territory and geographic targeting |
|---|
| LinkedIn company URL | Research and downstream workflows |
|---|
| Account tier | Prioritization |
|---|
| Account owner | Someone should probably own it |
|---|
| Reason selected | Why did this company make the list? |
|---|
That last one is underrated.
Six months from now, someone should be able to look at an account and understand why it's there. "It was in the spreadsheet" isn't a particularly strong targeting strategy.
4. Check the list before you use it
This is probably the step I'm most opinionated about.
You can have a beautifully formatted spreadsheet full of companies that theoretically match your ICP and still have a bad target account list.
Before you spend money or sales time against it, check the underlying data.
Are the domains active? Are some redirecting somewhere unexpected? Are there parked or invalid domains? Do you have duplicates? Are companies missing important information? Did businesses disappear or get acquired since the list was originally built?
Not every one of those problems can necessarily be caught automatically, but you want to find as many as you can before the list gets activated.
This became enough of a recurring problem that we built the Target Account List Grader. You can upload the domains from a TAL and get a much better picture of the health of the list before you start using it.
I think this matters because a TAL isn't really the end product. It's an input.
Marketing may upload it to an advertising platform. Sales might use it for prospecting. RevOps may push it into the CRM. Someone may feed it into an AI workflow for account research.
Bad data doesn't magically get better when you upload it somewhere else. It just becomes more expensive bad data.
Building the right list is half the job. The data also has to survive contact with your actual GTM stack.
5. Prioritize based on what you can actually execute
Once I'm reasonably confident we've got the right companies and the underlying data is solid, then I'd worry about prioritization.
You can make this as sophisticated as you want, but a simple Tier 1, Tier 2 and Tier 3 structure is often enough.
Tier 1 might be the accounts that justify highly personalized sales and marketing. Tier 2 could be strong-fit companies where you can use more scalable personalization. Tier 3 might be the broader ICP-fit universe you can reach through larger programs.
There's no magic number that belongs in each tier.
A business selling $500,000 enterprise contracts should probably approach this very differently from a company selling a $5,000 product.
The important question is: how many companies can your team realistically do something meaningful with?
If your "target" account list contains 40,000 companies, I'm not saying it's wrong. But we may need to have a conversation about what the word target means.
I'd rather have 500 companies that we understand, can prioritize and have a realistic plan to reach than 20,000 rows sitting in a CSV because technically they met a filter.
6. Put the list to work
Eventually the TAL has to leave the spreadsheet.
This is where all the boring data cleanup suddenly becomes quite useful.
Your list might end up in your CRM, an ad platform, a sales engagement tool, an audience, an account research workflow, a personalization platform or an AI agent.
And those systems don't always agree on how a company should be identified.
One may rely on the company name. Another wants the domain. Another workflow might need a LinkedIn company URL. Your CRM may have yet another version of the company name.
If you need LinkedIn company pages as part of that process, our free LinkedIn Company URL Finder can take company names and match them to LinkedIn company pages in bulk.
This is why I care about getting company identity right earlier in the process. The cleaner the data going in, the less time you spend fixing things downstream.
A fairly simple workflow can get you a long way:
Company name → Domain → Firmographics → Validate → Prioritize → Activate
That's a much more useful TAL than a spreadsheet containing a company name and a vague feeling that someone should probably sell to them.
Don't treat your TAL like a finished project
One last thing: the list is going to change.
Companies grow, shrink, move, get acquired, change domains, enter new markets and sometimes disappear altogether. Your own definition of a good customer will change too as you win deals, lose deals and learn more about who actually gets value from your product.
So revisit the list.
You don't need to rebuild the entire thing every Tuesday, but you should periodically check whether the companies still fit, whether the data is current and whether your prioritization still makes sense.
A TAL should get better as you learn.
The short version
If I were building a target account list tomorrow, this is the process I'd use:
- Define the ICP. Figure out what genuinely makes a company a good fit.
- Build the universe. Find the actual companies that match those characteristics.
- Get the identity right. Normalize company names and domains.
- Enrich what matters. Add the firmographic information you need to make decisions.
- Check the data. Validate the list before spending money or sales time against it.
- Prioritize realistically. Focus on the number of accounts your team can actually work.
- Activate it. Put the list to work across your sales and marketing stack.
- Keep it current. Companies change. Your ICP will too.
A lot of what we're building at afterSpark comes from dealing with these problems ourselves.
I've spent enough time in B2B marketing to know that most teams don't have a shortage of data. They have a shortage of clean, consistent company data they can actually put to work.
That's the difference between having a target account spreadsheet and having a target account list that's actually useful.
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