What Happens When Your Enrichment Tool Only Checks One Database

Most enrichment tools query a single database when you ask for someone's contact info. You click "enrich," the tool checks its records, and you get a result or you don't. The whole thing takes about a second.

The problem is what happens on the "you don't" side. When the tool comes back empty, there's no second attempt. No backup. That contact just becomes a gap in your pipeline, and you move on to someone you can actually reach.

I started paying attention to how often this happens after running a 25-profile enrichment test across three tools. The tool with the smallest data pool missed emails on 14 out of 25 profiles. The tool checking 20+ databases missed 6. Same people, same day. The difference was entirely about how many places each tool looked.

Where single-source databases come from

Every enrichment provider builds their database from some combination of web scraping, data partnerships, business registries, social media profiles, and user-contributed contacts. Some providers buy data from telecom companies. Others scrape public filings. A few rely heavily on users opting in and sharing their own contact books in exchange for credits.

The mix of sources determines what the database is good at and what it misses.

A provider that scrapes US business directories and SEC filings will have strong coverage of American companies with over 50 employees. That same provider might have almost nothing on European startups, because those companies don't file with the SEC and aren't listed in US directories.

A provider that gets most of its data from user-contributed contacts will have good coverage wherever its user base is concentrated. If the tool is popular with US tech sales teams, the database will be deep on US tech companies and shallow on everything else.

None of this is a flaw. It's just how databases work. Every source has a geographic, industry, and company-size bias baked into the way it collects data.

What the gaps actually look like in practice

During my test, the gaps showed up in predictable patterns.

The smallest gaps were at larger companies. All three tools found emails for contacts at places like Kaseya, FreshBooks, and TIAA. These are mid-size to large companies with public-facing directories and thousands of employees. When I tested contacts at companies with under 50 employees, like a solo recruitment firm in the Netherlands or a 10-person AI startup, the single-source tool came back empty on most of them. The multi-source tool still found matches for about half.

Geography widened the gap further. US-based contacts were the easiest for every tool. But when I tested a recruiter in the Netherlands, a lawyer in the UK, or contacts at Canadian companies, the coverage difference became obvious. One tool found zero emails for UK-based contacts. Another found personal emails instead of work emails, which is almost worse because it wastes your time without being usable for outreach.

Recent job changers were another weak spot. Two people in my test had started new jobs in January 2026. The single-source tool still had their old employer's email. The multi-source tool also had stale data on one of them, but caught the other because at least one of its 20+ providers had already updated. When someone changes jobs, databases update at different speeds. Checking more databases increases your odds of getting current information.

Then there's regulation. One of the tools I tested was blocked entirely by US state privacy regulations on 8 out of 25 profiles. Massachusetts, Florida, Virginia, New York, and a few others. The tool literally couldn't show me data for people in those states. If your prospect list includes US contacts, and you're using a tool that's subject to state-level blocking, a third of your list might return nothing regardless of whether the data exists.

The math behind coverage gaps

If a single database has a 60% chance of having any given contact's email, you'll find 60 out of 100 emails. The other 40 are gone.

If you check a second independent database that also has a 60% chance, your combined probability goes up to about 84%. Not because either database got better, but because the 40% that Database A missed overlaps only partially with the 40% that Database B missed.

Add a third database and you're around 94%. A fourth gets you to 97%.

In reality, databases aren't fully independent. They share some of the same underlying sources, so the actual improvement is smaller than the theoretical maximum. But the principle holds: checking more sources always improves coverage, even if each additional source adds less than the previous one.

The important thing is that the contacts you're missing aren't random. They're systematically biased toward certain geographies, company sizes, and industries. If you sell to US enterprise tech companies, a single source might cover you fine. If your prospect list is more varied than that, the gaps start to compound.

What happens downstream when contacts are missing

A missing email isn't just one fewer person on your list. It affects the math of the entire outreach sequence.

Say you have 200 prospects in a campaign. Your enrichment tool finds emails for 120 of them (60% match rate). Of those 120, about 50% open the email and maybe 5% reply. That's 6 replies from 200 prospects.

Now imagine a tool that finds 160 emails from the same 200 prospects (80% match rate). Same open and reply rates give you 8 replies. That's 33% more conversations from the same prospect list, with no change to your messaging, targeting, or outreach strategy.

The gap matters most in the middle of the funnel. If you're already struggling to book meetings, the difference between finding 60% and 80% of emails is the difference between a functional campaign and one that barely produces enough pipeline to justify the time spent building it.

And the contacts you're missing aren't random rejects. They're the people at smaller companies, in less common geographies, or in industries where data coverage is thin. In some cases, those are exactly the prospects with less competition in their inbox.

How to find out if your tool has this problem

You probably don't need to switch tools. You need to measure what your current tool actually finds on your specific prospect list.

Run a 20-profile test. Pick 20 real prospects from your pipeline. Not the easy ones at big tech companies. Pick a mix: some international, some at small companies, some recent job changers. Run them through your current tool and count how many come back with usable emails and phone numbers. "Usable" means current employer, correct country, and a format you can actually send to.

Compare against a second tool. Sign up for a free tier on a competing tool and run the same 20 profiles. If Tool B finds 5-8 more emails than Tool A on the same list, your current tool has meaningful gaps.

Check your bounce rates. If your email bounce rate is above 5%, some of those bounces are stale data that your tool returned confidently. A tool that checks more sources and cross-references recency is less likely to give you emails from two jobs ago.

Look at your "no data found" rate. Most enrichment tools have a dashboard or export that shows how many lookups returned empty. If more than 30% of your lookups come back empty, your tool's database probably doesn't cover your prospect profile well. That doesn't mean the data doesn't exist. It means your tool can't find it.

When a single source is actually fine

Not every sales team needs multi-source enrichment. If your ICP is narrow and well-covered by mainstream databases, a single-source tool might be perfectly adequate.

You're probably fine with one source if your prospect list is mostly US-based contacts at companies with over 200 employees in tech, finance, or professional services. Those are the profiles that every database covers well, because that's where most of the data collection effort is focused.

You're likely to hit problems if you sell to SMBs (under 50 employees), prospect internationally, target industries like manufacturing, healthcare, or government, or need phone numbers (which are harder to find than emails across all tools).

The honest answer is that the only way to know is to test on your own list. General claims about match rates don't tell you much because the rates vary wildly depending on who you're looking for.

The cost tradeoff

Tools that check multiple databases cost more per lookup. That's not a rip-off. It's the actual cost of querying 10-20 providers per contact instead of one. If a single-source tool charges $0.01 per lookup and a multi-source tool charges $0.08, the multi-source tool is doing 10-20x the work behind the scenes.

Whether that's worth it depends on what a reply is worth to you. If you're selling a $500/year product, an extra $0.07 per contact might not make sense. If you're selling $50K+ deals, paying more per lookup to reach 30% more contacts is an obvious trade.

The calculation gets simpler when you factor in the time you already spend building prospect lists, writing sequences, and managing campaigns. All of that work produces zero value for the contacts your tool couldn't find an email for. Better coverage means more of your existing effort converts to conversations.