Data enrichment is the process of taking a thin record (a name, an email, a company) and filling in the rest: verified work email, direct mobile, job title, company size, buying signals, and more. Done well, it turns a half-built list into contacts your reps can call today.
Done badly, it hands your team a spreadsheet full of gaps. Wrong numbers. Stale titles. Whole regions missing. This guide covers what enrichment does, how the waterfall model works, why coverage breaks, and what to look for in a tool that holds up across APAC and North America.
What is B2B data enrichment?
Enrichment adds missing or better information to a contact or company record you already have. You start with a little (say, a LinkedIn URL, or a first name and a company domain) and end with a full profile your team can act on.
Two flavors show up most often. Contact enrichment fills in a person: their verified email, direct mobile, current title, and seniority. Company enrichment fills in the account: headcount, industry, tech stack, funding, location. The best enrichment does both in one pass, so a rep sees the whole picture and knows exactly who to reach, how, and with what context.
The point is speed to action. A name with no phone number is a dead end. A name with a verified mobile and a “just changed jobs” signal is a call worth making this morning.
Why B2B enrichment is a routine, not a project
Enrichment is not a one-time clean-up, because the underlying data does not sit still. Two benchmarks are widely quoted: MarketingSherpa found B2B contact data decaying at roughly 2.1% per month, and HubSpot’s Database Decay Simulation annualizes that to 22.5% a year.
Checking that number from the other direction, looking at the people rather than the databases, the US Bureau of Labor Statistics puts median employee tenure at 3.9 years as of January 2024. That’s the shortest reading since 2002, and the Bureau reported that 22% of wage and salary workers had been with their employer a year or less.
So the figures broadly agree, and they were arrived at entirely independently. One measures records going stale. The other measures people moving jobs. They converge because they are describing the same event from opposite ends: if roughly a fifth of the workforce is new in role each year, roughly a fifth of your contact records describe a job someone no longer holds.
The detail of the data tells you something more useful than a single blended rate: your database does not decay evenly, and you can predict which parts go first. Median tenure for workers aged 25 to 34 is 2.7 years. For managers it is 5.7 years. So the junior champion who runs your trial and the senior buyer who signs the contract decay at roughly half and double the average respectively. If your ICP skews young, or you sell into high-churn functions, the headline 22.5% understates your real exposure.
A job change also does not simply invalidate one column, either. It takes the title, the direct dial, the work email and often the company with it, all at once. Title is the quietest of those and the most expensive. Routing, scoring and segmentation all run on title, and a wrong title never bounces. Nobody gets an alert. The list just quietly stops describing the people on it.
The cost lands on reps. In our survey of 220 B2B sales professionals, 80% said they lose at least 10% of their selling time to finding, cleaning or updating data. More telling for anyone buying enrichment: 58% had only discovered bad sales data after contacting a prospect. By then the cost is already paid, in a bounced email or a call to someone who left two years ago.
What good enrichment appends
| Field | Why it matters to a rep |
|---|---|
| Verified work email | Lands in the inbox, not the bounce folder |
| Direct mobile | The difference between a connect and a switchboard |
| Title and seniority | Are you talking to the buyer or the intern? |
| Company firmographics | Size, industry, location, to qualify fast |
| Tech stack | Personalization and fit in one data point |
| Buying signals | Job changes, funding, hiring, so timing is right |
Notice what sits at the bottom of that list. Buying signals are the hardest part to get right, and they separate a data platform from a lookup tool.
How does waterfall enrichment work?
Waterfall enrichment is the standard way teams squeeze more coverage out of their data spend. Instead of asking one provider for an email, you line several up in order. You send the record to the first provider. If it returns a confident result, you stop and pay for that one. If not, you fall through to the second, then the third, and so on down the “waterfall.”
The upside is obvious. No single provider covers everyone, so chaining several lifts your hit rate. You also pay only for the lookup that returns data, not for every provider you tried.
Orchestration tools like Clay made this model popular, and it works. A growth lead at an enterprise software company described their setup to us in one line: “I’m running cold email at scale, ten to fifteen thousand emails a month, and I rely on updated data in our warehouse. We source that from a waterfall method. We have a bunch of different providers.”
That is the standard shape of a modern enrichment stack. But the model has a limit worth understanding before you rely on it.
Why your enrichment waterfall misses contacts
A waterfall is only as good as the providers inside it. If none of them cover a region well, the waterfall doesn’t fail gracefully. It just fails. Three gaps show up repeatedly.
Coverage gaps by region. The largest, legacy providers come from the US and skew heavily to US and European data. Run them against a list in Singapore or Sydney and the hit rate drops off a cliff. If every provider in your chain shares the same blind spot, stacking them changes nothing. You need a source that owns strong data where the others are thin, not five more that share the same weakness.
This is the most common reason a global enrichment program underperforms in one region while looking healthy on the average. A tool that’s brilliant in the US and blank in APAC isn’t a global tool. It’s a US tool with a map of Asia on the homepage and it short-changes not only users in Asia, but those in the US targeting overseas businesses.
Mobile numbers. Most providers lean on work emails because emails are cheaper to find and verify. Direct mobiles are harder, so coverage thins out fast, exactly when your team is trying to cold call. A waterfall full of email-first providers gives you a lot of inboxes and very few phones.
The provenance black box. When a waterfall returns an email, you often can’t see which provider it came from, how recently that source refreshed, or how it was verified. “Returned a result” is not the same as “returned a fresh, verified, privacy-compliant result.” A confident-looking record can still be a year out of date, and you won’t know until it bounces.
That’s the real cost of coverage bought purely on volume. You get more records, but you can’t always tell which ones to trust, and the phones are missing.
What that looks like on a real file
A prospect recently sent us a sample of roughly 1,950 contacts to enrich. This was not a random slice of their database. It was deliberately the hard set: records their existing stack had already failed to return an email or a mobile number for. In their words, “a list of stuff that we didn’t have.”
Running that file returned mobile numbers for 63% of the total input and email addresses for 62%. Every one of those was a contact their current tooling had given up on.
The more interesting number was 216. That many people in the file had changed roles, and nothing in their CRM had flagged it. Roughly one record in nine wasn’t missing a phone number at all. It was pointing at the wrong person, and a waterfall that returned a confident-looking result for those records would have made the problem harder to see, not easier.
That is the argument for treating enrichment as a standing routine rather than a gap-filling exercise. Filling blanks is the visible half of the job. Correcting records that already look complete is the half that decides whether your reps reach anyone.
What to look for in a data enrichment tool
Volume is the number every vendor leads with. It’s also the least useful one on its own. When you compare data enrichment tools, weigh these instead.
Does the provider own its data, or route to it? An orchestration layer routes your request across many third-party sources and manages the workflow. A data provider owns the underlying data, which means it can verify it, refresh it on a known cycle, and build signals on top of it by comparing records over time. Both jobs matter. They are just different jobs, and knowing which one you are buying tells you what to expect from it.
Coverage where you sell. Ask for hit rates in your real territories, not a global average. When our team runs an enrichment evaluation, we report the match rate market by market, because a single global number hides exactly the variation you are trying to measure. Australia, Singapore and Japan routinely return different rates against the same list, and Japan is consistently the hardest of the three: coverage everywhere depends on how much professional information a market publishes about itself, and that varies more than most buyers expect.
Two questions are worth asking any provider running an evaluation for you. What happened to the records you could not match? A useful answer names reasons, duplicates, entity-name mismatches, companies trading under a different registered name, rather than returning a silent blank. And what do you do when you cannot verify a field? A provider that leaves revenue empty rather than estimating it is telling you something about the rest of the record.
Direct mobile depth. If your team calls, mobile coverage is the metric. Check it separately from email. They are not the same, and the gap is usually large.
Freshness. How often does the data refresh, and on what cycle? Weekly beats quarterly by a wide margin when two in three job titles change in a year. Ask for the cadence in writing.
How matching works. Registry-based matching, tied to official company registries, is more reliable than guessing an email from a name and a domain and pinging to see if it sticks. Guessing works passably in the US, where naming conventions are predictable. It falls apart in markets with different name formats. Local identifiers matter here too: a record carrying an official registration number is far easier to re-verify against a public register than a name and an email.
How the pricing model behaves at volume. Credit models differ in what a credit buys. Some charge per action, so a single enriched row can spend several credits across a workflow. Others charge once per contact record. Model it against your actual monthly volume before you sign, not against the headline rate.
Signals. Can the tool tell you when an account raises funding, hires a VP, or changes tech? That’s the difference between a static list and a reason to reach out this week.
If you want to run that checklist against us specifically, our B2B data enrichment software page answers each of these in order: coverage, mobile depth, refresh cadence, matching, pricing and signals. Our guide on how to choose a sales intelligence platform covers the rest of that evaluation.
Where Firmable fits, including inside Clay
Firmable is a data and signals provider. We own our data across APAC and North America, validate contact data on a weekly cycle, and hold 15m+ company records and 135m+ people records across 1,000+ data attributes. More than 1,300 companies use us. One credit unlocks a contact’s full record, and the Firmable ID means you keep that contact for life, including through their next job move.
Our data enrichment page sets out exactly which fields get appended and how they sync back to your CRM. The rest of this section is about where that data sits in your stack.
Here’s the part teams miss: if you already run Clay, you don’t have to choose.
The analogy our team uses is that Clay is the race car and Firmable is the fuel. Clay is an orchestration layer for the people running the machine behind the team: RevOps and GTM engineers who think in workflows, stitching together sequential steps, AI agents and a waterfall of providers. Firmable is built for the people closest to the phone: sellers, SDRs and sales leaders who think in lists, filters and signals. They aren’t competing for the same job, and neither replaces the other.
Firmable is a native data provider inside Clay. There are two ways to connect it:
- Clay-managed. Use Firmable through Clay’s own credit system. No separate contract, billed alongside everything else in your Clay workspace. The fastest way to start.
- Bring your own key. Connect your own Firmable account, available on the Firmable Enterprise plan, so your Clay workflows draw on your direct Firmable plan instead of Clay credits. For teams using Firmable data at volume this is typically the more cost-efficient path. Worth a side-by-side plan comparison with your rep.
Four ways teams actually run this
RevOps teams already on Clay. Add Firmable as a contact data provider inside your workflows, tables or waterfall to maximize coverage of accurate contact information before records sync to HubSpot or Salesforce.
GTM engineers building agents. Firmable doesn’t just return an email or phone number. It returns a contact’s full profile, with work history, LinkedIn summary, title and more, ready to feed into an AI qualification agent. Only accounts that clear the bar reach a rep’s queue, with the reasoning attached.
Sales teams with no Clay in place. Use Firmable directly to build territory lists, track hiring and funding signals, and push verified contacts straight into your CRM. No orchestration layer, no GTM engineer, no implementation project. Live in a day, not a quarter.
Mixed organizations running both. Sales champion Firmable for their own outbound motion while RevOps run Clay centrally for broader enrichment workflows. Same underlying Firmable data, two different access points, no conflict between teams.
That last pattern is the most common one we see, and it’s worth naming because teams often assume they have to pick a side. They don’t.
What it looks like when it works
Lineer had the regional coverage problem and the tooling problem at once:
“There was inconsistency in the data available in APAC. We kept running into inaccurate email addresses and phone numbers. And salespeople aren’t software developers. They shouldn’t need to spend their day learning a complex platform.”
That second sentence is the whole argument for keeping a rep-facing tool alongside an orchestration layer. The workflow belongs with the people who build workflows. The list, the signal and the mobile number belong with the person about to make the call.
Cotiss lifted contact accuracy from around 30% with a US-based provider to 85-90%, and more than doubled call connects within weeks. Solutions Plus now enriches inbound leads in HubSpot automatically, after years of data that “appeared to be quality data on the surface” and “turned out to be outdated or inaccurate.”
Frequently asked questions on B2B data enrichment
Data enrichment adds missing or better details to a record you already have, like appending a verified email, direct mobile, title, and company firmographics to a name. The goal is a contact your team can act on right away.
You line up several data providers in a set order and send each record through them one at a time. The first provider to return a confident result wins, and you pay only for that lookup. If none have the data, the record comes back empty.
An orchestration layer routes your request across many third-party providers and manages the workflow. A data provider owns the underlying data, which lets it verify, refresh and build signals on top of it. The two work well together: the orchestrator runs the workflow, the provider supplies the data. Most teams running Clay use a data provider inside it.
Both, depending on your team. For RevOps and GTM engineers who need orchestration, Firmable is a data provider inside Clay. For sales teams who need lists, signals and verified contacts without building workflows, Firmable is a complete platform on its own.
For teams using Firmable data at volume, bring your own key is typically the more cost-efficient path, because you buy Firmable data on a Firmable plan rather than through Clay credits. Below that volume, Clay-managed is simpler and faster to start. It’s worth a side-by-side plan comparison with your rep.
Cleansing removes what is wrong: duplicates, bounced emails, records for companies that no longer exist. Enrichment replaces it with what is right and fills fields that were never populated, such as direct dials, company size, industry and buying signals. Cleansing makes your file smaller and more honest. Enrichment makes it usable. You need both, in that order.
Most providers are email-first, because emails are cheaper to find and verify than direct mobiles. If every provider in your waterfall shares that bias, you’ll get plenty of emails and few phones. Adding a source with strong mobile coverage fixes it.
Ask for the cadence in writing, and ask what “refreshed” means: re-validated against source, or simply re-served from cache. Weekly validation keeps pace with job changes; quarterly data is already drifting by the time you use it.
No. A common pattern is sales championing Firmable for their own outbound motion while RevOps run Clay centrally for broader enrichment workflows. It’s the same underlying Firmable data through two different access points, so there’s no conflict between teams.
Yes. Firmable is a native data-provider integration inside Clay. You can pull verified work email, personal email and mobile number lookups directly into your Clay tables. Learn how to connect Firmable and Clay.
