Data enrichment services that fill the gaps in your CRM and product records

What do data enrichment services add to a record?

They add the fields your team needs to act on a record and that nobody had time to type in. For B2B companies that usually means firmographics on accounts and role details on contacts; for product and catalog teams it means specifications, categories and descriptions pulled from supplier sheets or manufacturer sites.

The fields are chosen by what they feed. If territory routing depends on state and employee count, those two fields come first. If lead scoring needs industry and tech stack, they do. We avoid enriching fields that nothing downstream reads, because each one costs money to fill and keep current.

• Accounts: domain, industry, employee band, headquarters location, LinkedIn page, parent company.
• Contacts: job title, seniority, department, verified work email where permitted.
• Products: dimensions, materials, compliance marks, category, cleaned descriptions.
• Custom: any fact visible on a company's own website, extracted by a language model with the page cited.

How does lead enrichment work inside HubSpot or Salesforce?

A trigger fires when a record is created or a key field changes, the enrichment workflow looks up the missing values, and the results write back through the CRM's API. In HubSpot that is typically a workflow webhook into n8n or a Python service; in Salesforce it can be a platform event or a scheduled job against a filtered list view.

Lead enrichment at form-fill time lets you keep forms short: ask for name and work email, then fill company size and industry behind the scenes before the lead reaches routing. We write enriched values into dedicated fields at first, so your team can compare them with what reps typed before anything is overwritten.

Which data sources and tools do you use?

We use prospect data platforms such as Clay and Apollo where they fit, alongside the client's own data, public company websites and language models that read those sites. The mix depends on your market, your budget per record and the terms each provider sets on reuse.

Sources are arranged as a waterfall: the cheapest reliable source runs first, and only records still missing a field move to the next one. Each value is stamped with its provider and fetch date, which matters when two sources disagree and when you need to show where personal data came from.

How do you keep enriched data accurate?

We validate before we write. Rules check formats (a real domain, a state code, a number in a sensible range), compare new values with existing ones, and refuse to overwrite a field a rep edited by hand unless you say otherwise.

When a language model extracts a fact from a website, it must quote the passage it used, and a confidence threshold decides whether the value posts or goes to a review list. We also measure fill rate and accuracy on a sample of records against a hand-checked set before go-live, then track both on a small dashboard so decay is visible month to month.

Can enrichment clean up duplicates and messy records too?

Yes, and it usually should come first. Enrichment works best on records that are already deduplicated and normalized, so most projects start with matching companies by domain, merging contact duplicates by email and standardizing values like country names and job titles.

That clean-up step often pays back on its own, because routing rules, reports and email sends stop double-counting. We run merges in review batches so a person approves anything ambiguous.

What about privacy rules for contact data?

Company facts are low risk; personal contact details need more care. We record the source of every contact field, respect each provider's terms on storage and reuse, and add a suppression list so people who opt out are never re-enriched or re-imported.

Access is limited by role inside the CRM, and enrichment logs keep who requested what and when. If you sell into regions with stricter privacy rules, we design the field plan with your counsel's guidance before any data is pulled.

What does ongoing enrichment cost?

Running cost is mostly per-record fees from data providers plus model calls for website extraction, so it scales with how many records you enrich and how often you refresh them. We set a cost cap per record and per month, and the waterfall order is tuned to keep expensive sources for records that matter, such as target accounts.

Our build is a fixed price agreed after a free review of a sample export. Provider subscriptions are billed to your accounts, so you keep them if we part ways.