If you’re tired of spending hours cleaning up customer account data, or you keep hearing about “data-driven GTM” but all you have is a messy spreadsheet, this guide’s for you. We’ll walk through a realistic, step-by-step approach to automating account enrichment in Tamr so you can actually segment and target accounts the way marketing claims you can. This isn’t magic—just a set of practical steps (and a few warnings about what not to waste time on).
Why automate account enrichment, anyway?
Let’s cut through the hype: most B2B orgs have junk account data. Even if you think your CRM’s in good shape, once you try to segment for a campaign or prioritize accounts, you run into duplicates, missing firmographics, or outdated info. Manually fixing this is a black hole for your time.
Automating account enrichment means:
- You get clean, unified account records across your tools.
- Marketing and sales can actually segment by something useful—industry, size, location, tech stack.
- You spend less time “fixing” data and more time using it.
Tamr’s not the only way to do this, but if you have complex data from multiple sources, it’s one of the more flexible tools out there.
Step 1: Get your account data together (and be honest about the mess)
Before you even touch Tamr, you need to know what you’re working with. This is the step most teams skip, and it bites them later.
What to do: - Pull all your account data exports—from CRM, marketing automation, spreadsheets, enrichment vendors, whatever you’ve got. - Make a quick inventory: how many sources, what fields do you have, where’s the overlap, what’s missing? - Don’t try to “clean” anything yet. Just admit to yourself how messy things are.
Pro Tip: Open up a few random records in each source. Are “Acme Corp” and “Acme Corporation” showing up as different accounts? This is the kind of duplicate you’ll want Tamr to unify later.
Step 2: Decide what “enriched” actually means for you
Not every field matters. Figure out what you actually need for GTM segmentation. Ignore the rest.
Ask yourself: - What attributes do sales and marketing actually use to segment and prioritize? (Industry, size, region, tech used, etc.) - Which of these are missing or low quality in your current data? - What outside data sources can fill those gaps? (Think: Clearbit, Dun & Bradstreet, BuiltWith, etc.)
What doesn’t matter: - Don’t worry about every last data point. Focus on what drives segmentation. - You don’t need to enrich every account—start with your top segments or target list.
Step 3: Set up Tamr projects for data unification and enrichment
Here’s where Tamr comes in. Tamr is built to unify and enrich data from multiple sources using machine learning and human feedback. But it’s not push-button simple—you’ll need to set up some basics.
How to get started:
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Connect your data sources.
- Use Tamr’s connectors or upload flat files (CSV, Excel).
- Map fields as best you can—don’t stress about perfect mapping on the first go.
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Create a unification project.
- This is where Tamr finds and merges duplicate accounts.
- Set your match rules (name, domain, address, etc.).
- Expect some manual review—ML gets close, but humans still need to check for weird edge cases.
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Set up enrichment rules.
- Bring in your third-party data sources (Clearbit, D&B, etc.).
- Map key attributes you care about (industry, employee count, etc.).
- Decide whether you want Tamr to automatically overwrite existing data, fill in blanks, or flag conflicts.
Watch out for: - Overly aggressive matching. Tamr’s ML is good, but if you set the threshold too low, you’ll merge accounts that aren’t actually the same. - Data source conflicts. Two sources say different things—pick a “source of truth” or set up rules for which wins.
Step 4: Automate the enrichment workflow
Manual enrichment is for people with a lot of free time (hint: that’s no one). The point here is to set up a repeatable, mostly hands-off process.
What to automate:
- Scheduled data imports: Set Tamr to pull in fresh data from your sources every week (or whatever cadence makes sense).
- Automated unification and enrichment: Tamr can run these processes on a schedule.
- Notifications for manual review: If Tamr’s not confident about a match, push it to someone to review, not everyone.
How to do it:
- Use Tamr’s built-in workflow tools or APIs to schedule jobs.
- Set up alerts for jobs that fail or need human input.
- Push enriched, unified data back into your CRM/marketing tools via API or export.
Ignore for now: - Real-time enrichment. Unless you really need it, batch processing is simpler and less painful to maintain. - Fancy custom rules unless your use case demands them. Start simple, iterate.
Step 5: Validate and measure (don’t just assume it worked)
Automation doesn’t mean perfection. You’ll want to check if your process is actually improving segmentation. Here’s how:
- Spot check samples: Look at 20–30 random enriched accounts. Are key fields now filled in? Any obvious errors?
- Review segments: Can sales and marketing now pull useful account lists by industry, size, etc.?
- Track enrichment rates: How many accounts are still missing key info? Is that number shrinking?
If it’s not working: - Check your match rules—too strict or too loose? - Are third-party sources actually providing better data, or just more noise? - Is your “source of truth” logic creating conflicts?
What works, what doesn’t, and what to ignore
Here’s the honest rundown:
What works: - Automating the basics (dedupe, fill in blanks, standardized fields). - Iterative improvement—start with a few fields, then expand. - Involving end users (sales ops, marketing) in reviewing test outputs.
What doesn’t: - Trying to automate every edge case. Some judgment calls still need a human. - Relying just on third-party data—those sources are often outdated or wrong. - Treating this as a one-time project. Data decays fast; enrichment needs to be ongoing.
Don’t waste time on: - Overdesigning your Tamr workflows. Get something working, then refine. - Chasing “perfect” data. Good enough is good enough for most segmentation.
Pro tips and gotchas
- Don’t skip documentation. Keep a simple doc with what you’re enriching, where data’s coming from, and what rules you’ve set up. You’ll thank yourself later.
- Test small, roll out wide. Run your process on a sample set before pushing to your whole database.
- Keep stakeholders in the loop. Sales and marketing will trust the new data a lot more if they know what’s changing (and why).
Wrapping up: Keep it simple, iterate often
Automating account enrichment in Tamr isn’t about chasing perfection—it’s about not drowning in bad data. Get your basics right, automate what you can, and keep tuning over time. If you keep things simple and focus on the fields that actually matter, you’ll spend less time cleaning data and more time putting it to use. And if something’s not working, don’t be afraid to scale back and try a simpler approach. That’s how real progress happens.