15 Data Enrichment Tools, Ranked by What They Add to a CRM Record

Every other tool here can tell me how big a company is. Almost none of them can tell me what that company runs.

That is the field I actually want, because it is the only one that changes the first line of the email.

StackScan takes a domain and gives back the stack. Checkout platform, email tool, analytics, payment processor, hosting, the frameworks underneath. It watches more than 360 million domains and tracks over 55,000 technologies.

For enrichment specifically, the part that matters is that it does not end at a download. There is a REST API, direct CRM integrations, and an n8n node, so the stack can land on the record the same hour the record is created. There is an MCP server too, if your team has moved research into an AI client.

I use it two ways. Backfill, where I push an export of everything already in the CRM through it and get a stack column back. And watch, where anything new gets scanned on the way in.

The public technology pages are the cheapest way to see whether the data is any good before you pay. Shopify and Klaviyo are the two I check most, and WooCommerce if you sell into the WordPress half of ecommerce.

One honest caveat. This is company and domain data. Nobody's mobile number comes out of it, so you will still pay somebody else for contacts.

Clay is not a data provider. It is a spreadsheet that knows how to call fifty of them.

The idea is called waterfall enrichment. Ask provider one for the email. If it comes back empty, ask provider two. Keep going until somebody answers, and only pay for the answer.

That fixes the single most annoying thing about buying data, which is paying full price for a 40 percent match rate and then paying a second vendor full price to cover the gap.

It writes back to HubSpot and Salesforce, and it will run conditional logic per row, so you can say things like: only look for a phone number if the company has more than fifty staff.

Two warnings. The pricing is in credits and credits disappear quickly once people start experimenting, so put one person in charge of the account.

And it is genuinely a skill. Clay rewards somebody who enjoys building the machine. If nobody on the team is that person, it becomes an expensive spreadsheet.

Clearbit was the default answer to this question for about eight years. It joined HubSpot and now shows up as the intelligence layer inside the CRM rather than as something you wire in yourself.

If you already run HubSpot that is good news. Enrichment stops being an integration you maintain and starts being a toggle, and the data lands on the record without a sync job in the middle.

If you do not run HubSpot it is now a much less interesting option than it was.

The data itself is what it always was. Solid firmographics, good logo and domain resolution, weaker once you leave the United States and Western Europe.

Pricing moved to credits, which is worth modelling before you commit. Credit models punish teams with a lot of low value records, because every one of them costs the same to enrich as a good one.

People Data Labs sells you the dataset and expects you to build the product on top.

There is no pretty interface to log into and no workflow. There is an API, a schema, and a lot of records.

For a team with an engineer this is the cheapest way to get good coverage, because you are not paying for somebody else's UI.

For a team without one it is useless, and I would not pretend otherwise.

The free allowance is real and big enough to test properly. Pull a few hundred of your own customers and check the match rate against what you already know is true, which is the only benchmark that means anything.

Standardisation is the quiet strength here. Job titles and company names come back normalised, which saves a surprising amount of cleanup later.

Most databases will hand you a phone number. Cognism will hand you one that rings.

The difference is that a chunk of their mobile numbers are verified by a person rather than scraped and hoped for, and they sell that verification as the product.

If your team calls, that is worth real money. Connect rate is the whole game in outbound calling and a bad number list quietly destroys it.

European coverage is the other reason people buy it. Cognism does the notification and suppression work that European calling requires, which the American vendors mostly do not.

Pricing is seat based and quote only, which makes it awkward to compare with everything else on this page. Expect it to be the most expensive line on your data budget.

It enriches well through its integrations, but it is priced like a prospecting tool. If you only want to fill gaps on existing records you will overpay.

Dropcontact does something unusual. It does not keep a database of people.

It works out the likely address from the name and the company, then tests it. Nothing personal sits on their side waiting to be leaked or subpoenaed.

That sounds like marketing until your legal team asks where the personal data in your CRM came from. Then it is the whole reason to pick it.

European sellers care about this more than American ones, and Dropcontact is French, so the answer to the compliance question is already written down.

Billing is pay on success, which I like. You are charged when it finds something, not when it tries.

The limit is scope. This is emails and basic company tidying. It is not going to give you headcount, revenue or a technology stack, so it sits alongside other tools rather than replacing them.

Datanyze was a serious technographic product, got bought by ZoomInfo, and now lives on as a cheap browser extension with a credit allowance.

For twenty odd dollars a month you get technology signals and contact details on the same record, which is a combination nothing else here offers at that price.

The catch is depth. Coverage is thinner than it used to be and the technology list is nowhere near what a dedicated scanner sees.

I would not build a territory plan on it.

I would absolutely use it as a rep sitting on a prospect's website who wants to know two things before picking up the phone.

Treat it as a lookup tool for individuals rather than a data source for the whole team, and the price makes sense.

Coresignal is another raw data company, but the interesting part is the shape of what they hold.

Not just how many people work somewhere, but how that number moved, and what roles were being hired.

A company record that says 200 employees is a fact. A record that says 200 employees, up from 120 last year, with four open engineering roles, is a reason to call.

That is a genuinely different kind of enrichment and it is why I have it above the identity tools.

Pricing starts low and climbs steeply with volume, and it is credit based, so the same discipline applies as with everything else here. Decide what you are enriching before you turn it on.

It is an API, so the People Data Labs caveat applies. No engineer, no value.

Diffbot crawls the web and turns it into a graph of things and the links between them.

So the question it answers is not what is this company, it is how is this company connected to that one.

Subsidiaries, acquisitions, who sits on which board, which brand belongs to which parent.

For most CRM work that is more than you need and the price reflects it.

For a few jobs it is the only sensible answer. Untangling a corporate group so that eight records collapse into one account is the obvious example, and anyone selling to enterprise knows that pain.

The free tier is real and the API is well documented. If you have a graph shaped problem, test it before you dismiss the price.

This one solves a problem you might not know you have.

The same person signed up with a work address in 2023, a personal address on a webinar in 2024, and filled in a form last month with a typo in their surname.

Your CRM thinks that is three people. Your reporting thinks you have three times the pipeline you do.

FullContact stitches those fragments back into one identity. It is the least glamorous job on this page and it quietly ruins the most dashboards when nobody does it.

There is no public pricing, which is a real mark against it in a list where the entry price column is supposed to mean something.

It is also worth being clear that identity resolution is not the same as enrichment. It adds no new facts. It just stops you counting the same person four times.

Everything above this line puts new facts into your CRM. Insycle deals with the fact that your CRM is already a mess.

Duplicate companies. Job titles typed nine different ways. Country as US, U.S., USA and United States in the same column. Phone numbers in four formats.

It dedupes, merges, standardises and does it in bulk with a preview before anything is written, which is the feature that matters, because bulk operations on a CRM are how people lose their jobs.

Here is why it is on an enrichment list at all. If you enrich a database that has 15 percent duplicates, you pay to enrich those duplicates. Twice, sometimes three times.

Cleaning first is cheaper than cleaning later, and it makes every match rate you measure afterwards mean something.

No public pricing, which is annoying, but the free trial is enough to see the size of your own problem.

Plenty of companies buy enrichment for facts they already own.

Product usage, support ticket counts, invoice history, plan tier. All of it sits in the warehouse and none of it reaches the CRM, so the rep never sees it.

Hightouch pushes warehouse tables out into the tools people actually work in. The category name is reverse ETL and it is unglamorous plumbing.

The reason it belongs on this list is that a record showing this account's usage dropped 40 percent last month is worth more than any firmographic field you can buy.

It also makes bought data cheaper. Enrich once into the warehouse, sync out to every tool, rather than paying each tool to enrich the same record separately.

You need a warehouse and somebody who can write SQL. If you have neither, skip to the next three.

The last three do not enrich anything. They decide whether enrichment ever happens without somebody remembering to do it.

n8n is the one I reach for first, because you can run it on your own server and the data never leaves it.

That matters here more than in most automation jobs. Enrichment workflows carry personal data by definition, and every hop through somebody else's cloud is another paragraph in a data processing agreement.

A typical flow looks like this. New company in the CRM, call StackScan for the stack, call an email provider for a contact, write both back, notify the owner in Slack if the stack contains something you sell against.

That took me an afternoon and it runs forever.

Self hosting is real work though. Somebody has to patch it, back it up and notice when it stops. The cloud version exists for people who would rather not.

Zapier wins on one thing and it is enough. Whatever obscure tool your marketing team bought, it connects to it.

For enrichment that translates into working today rather than after a sprint. Trigger on a new record, call the enrichment API, write the fields back, done before lunch.

Non technical people can build and maintain these, which is the real argument. A workflow nobody but one engineer understands is a workflow that breaks the week they go on holiday.

Costs scale with task volume and get uncomfortable at enrichment scale, because every record is tasks and records are many.

There is also the question of where the data goes. Your records pass through Zapier's infrastructure. For most companies that is a signed agreement and a shrug, for some it is a hard no.

Fine for thousands of records a month. Look at the other two if you are doing hundreds of thousands.

Make sits between the other two. Cheaper per operation than Zapier, easier than running your own server.

The visual canvas is the part people either love or ignore. When an enrichment flow has six branches, seeing it drawn out is genuinely faster than reading a list of steps.

Its iterator and aggregator handle the shape of enrichment work well, which is take a list, do a thing to each item, put it back together.

Error handling is better than Zapier's. You can define what happens on a failed lookup rather than watching the whole run stop.

Pricing counts operations, and every module in the chain is an operation, so a five step flow costs five per record. Model it on your actual volume before committing.

If you are choosing between these three, ask one question. Is the data sensitive enough to keep on your own server? If yes, n8n. If not, Make for volume and Zapier for breadth.