Salesforce Data Enrichment: 2026 Setup Guide & Best Practices

Open any Salesforce org that's been running for more than a year. You'll find the same story: thousands of records with missing phone numbers, outdated job titles, company sizes from three acquisitions ago, and email addresses that haven't worked since 2019.

This isn't a Salesforce problem, it's a data decay problem. People change jobs (a lot). Companies get acquired or go under. Contact info goes stale faster than you'd think.

Salesforce data enrichment solves this by automatically supplementing your CRM records with current, verified information from external data sources. Done right, it turns a messy database into a competitive advantage. Done wrong (or not at all), your sales team wastes hours researching prospects before every call.

This guide covers how to set up enrichment in Salesforce, which Salesforce enrichment tools work, and the best practices that separate good implementations from great ones.

What Data Enrichment Does for Salesforce

At its core, enrichment fills gaps. A lead comes in with just a name and email address. Enrichment adds their job title, phone number, company size, industry, technology stack, and whatever else your sales process needs.

But it goes beyond just filling blanks.

Data correction catches when fields are wrong, not just missing. Someone entered "VP of Slaes" three years ago and nobody noticed. Their company moved headquarters. The phone number has an extra digit.

Data standardization makes sure "Information Technology" and "IT" and "Tech" all mean the same thing in your reports.

Data freshening updates records that were accurate six months ago but aren't anymore. The VP you were selling to is now at a different company. Their competitor just got acquired.

Here's what typically gets enriched in a Salesforce environment:

Data Category	What Gets Added/Updated
Contact info	Verified email, direct phone, mobile number
Professional data	Title, department, seniority, LinkedIn URL
Firmographics	Company size, revenue, industry, location, year founded
Technographics	Tech stack, tools used, platforms
Intent signals	Hiring activity, funding news, buying indicators

The downstream impact is real. Your lead scoring actually means something because it's based on accurate data. Your segmentation works. Your personalization sounds informed rather than awkward.

Salesforce's Native Enrichment Options

Before you start evaluating third-party tools, know what Salesforce offers out of the box.

Data Cloud Enrichments

If you're on Data Cloud (formerly Customer Data Platform), you get access to native enrichment capabilities. This includes copy field enrichments that pull data from unified profiles into standard Salesforce objects, and related list enrichments that surface Data Cloud information directly on record pages.

The catch? Data Cloud isn't cheap, and it's designed more for unifying existing data than pulling in net-new external data. Great for connecting your own sources; less useful for adding firmographic or contact data you don't already have.

Data Pipelines

For Enterprise+ customers, Data Pipelines can clean and transform large volumes of data within Salesforce. You can connect external sources and run calculations. But again, it's primarily about processing data you can access, not sourcing data you're missing.

What's Not Available Anymore

Data.com is gone. If you're reading old blog posts mentioning it, ignore that section. Salesforce retired it years ago, and there's no direct replacement at the same price point.

The honest truth? For most Salesforce data enrichment use cases, you'll need a third-party tool. The native options work for specific scenarios but don't cover the bread-and-butter need of "add firmographics and verified contact info to my leads."

Third-Party Salesforce Enrichment Tools

The market for data enrichment tools for Salesforce has exploded. Here's how to think about the options.

Single-Provider Platforms

These are the big databases - ZoomInfo, Cognism, Apollo, Lusha. You get access to one large dataset through their Salesforce integration.

The upside: Simple setup, usually strong AppExchange integration, one vendor relationship.

The downside: Coverage gaps. No single provider has good data on every company in every industry in every geography. If 60% of your target accounts are well-covered but 40% aren't, that 40% is still a problem.

Pricing ranges wildly. ZoomInfo can run $15,000+ per year for a small team. Apollo and Lusha have more accessible entry points.

Data Enrichment Platforms (Waterfall Systems)

These platforms connect multiple data sources and query them in sequence until they find what you need. Databar is a good example - it connects to 90+ data providers and runs waterfall enrichment logic automatically.

The upside: Best coverage, because if Provider A misses something, Provider B might catch it. One integration instead of managing many.

The downside: You're depending on the aggregator's data partnerships and orchestration quality. 

This approach makes particular sense for teams that have tried single providers and hit coverage limits, or those targeting diverse accounts where no single database excels.

Point Solutions

Smaller tools focused on specific enrichment types. BuiltWith focuses on technographics. Hunter.io is strong on email finding and verification.

The upside: Often best-in-class for their specialty. More affordable than the big platforms.

The downside: You end up with multiple tools, multiple integrations, multiple invoices.

Building Your Enrichment Architecture

Whatever tools you choose, the architecture matters. How does data flow? When does enrichment happen? What triggers it?

Enrichment Trigger Points

You've got three main options for when enrichment fires:

On record creation. A new lead enters Salesforce, enrichment runs immediately, the record is populated before any rep touches it. Fast, clean, but you're paying to enrich every single record, including the ones that will never go anywhere.

On-demand. Reps click a button (or a Flow runs) to enrich specific records when they need it. More selective, lower cost, but adds friction and delays.

Scheduled batch. Enrichment runs nightly or weekly against a segment of your database. Good for maintenance; less useful for inbound speed-to-lead scenarios.

Most mature setups combine these. Inbound leads get enriched immediately (speed matters). Existing database records get re-enriched quarterly to catch job changes and data decay.

Flow-Based Enrichment

Salesforce Flow is your friend here. With Record-Triggered Flows, you can fire enrichment whenever specific conditions are met:

A lead is created with a verified email domain but missing company size. That triggers an HTTP callout to your enrichment provider, response comes back, fields update, all before the lead assignment rules even run.

Here's a simplified example of what that flow logic looks like:

Trigger: Lead created

Condition: Company_Size__c is blank AND Email contains "@"

Action: HTTP Callout to enrichment API

Action: Update lead record with response data

Action: Run assignment rules

 

This works with platforms that expose APIs. Most modern enrichment tools do.

Webhook-Based Enrichment

If your enrichment platform supports webhooks, you can flip the model. Instead of Salesforce calling out to get data, your enrichment platform pushes data into Salesforce when it's ready.

This works well for async enrichment (where the provider takes minutes to gather data rather than returning instantly) and for ongoing monitoring scenarios (job change alerts, funding announcements, etc.).

Field Mapping and Data Governance

Here's where implementations succeed or fail: field mapping.

Your enrichment tool returns a field called employee_count. Where does it go in Salesforce? If you have a field called Company_Size__c, great. If your field is Number_of_Employees__c, you need mapping. If you have both (because someone set things up inconsistently years ago), you have a governance problem.

Before You Enrich, Audit Your Fields

Take inventory of what already exists in your Salesforce schema:

Which fields are actually used by your team and processes? Which are legacy cruft nobody touches? Are there duplicates that store the same concept differently?

Clean this up before you start enriching. Otherwise, you're pouring good data into a messy structure, and you'll just create new problems.

Mapping Best Practices

Create explicit mappings for every field your enrichment tool can populate. Document them. Include:

• Source field from enrichment provider
• Target field in Salesforce
• Data transformation (if any)
• Overwrite behavior: Does new data replace existing values, or only fill blanks?

That last one matters more than you'd think. If a rep manually updated a phone number last week after talking to the contact, you probably don't want automated enrichment to overwrite it with stale database data.

Protected Fields

Some fields should never be overwritten by enrichment. Maybe you have proprietary data from your customer success platform, or competitive intelligence gathered through sales conversations. Mark these as protected in your enrichment configuration.

Measuring Enrichment Quality

Paying for enrichment without measuring its effectiveness is just spending money.

Coverage Metrics

Match rate: What percentage of records that enter enrichment get any data back? If you're sending 1,000 leads and only 600 come back with firmographic data, that's a 60% match rate. Acceptable varies by use case, but sub-50% should trigger questions.

Field fill rate: For matched records, how many of the fields you care about actually get populated? A "match" that returns company name but nothing else isn't that useful.

Accuracy Metrics

Match rate doesn't tell you if the data is right.

Run periodic spot checks. Pull 50 random enriched records, manually verify them against LinkedIn and company websites. How often is the title accurate? The company size? The direct dial?

If you're finding 20% error rates, your enrichment is creating as many problems as it solves.

Decay Tracking

Set up a simple process to track how quickly enriched data goes stale. Re-check records 90 days after enrichment. What percentage of emails still deliver? How many contacts have changed jobs?

This tells you how often you need to re-enrich to maintain quality.

Salesforce vs. HubSpot: Enrichment Compared

If you're evaluating CRM platforms or considering migration, here's how enrichment capabilities compare:

Capability	Salesforce	HubSpot
Native enrichment	Limited (Data Cloud, Data Pipelines)	HubSpot Insights
AppExchange options	100+ enrichment tools	Growing marketplace
Flow/automation triggers	Strong (Record-Triggered Flows, webhooks)	Strong (Workflows, Operations Hub)
Custom field flexibility	Extensive	Good, less complex
API callout limits	Higher on Enterprise+	More constrained

Salesforce generally offers more flexibility for complex enrichment architectures, especially at Enterprise scale. HubSpot is often easier to set up but can hit limits faster as requirements grow.

What Actually Works: Best Practices

After watching plenty of enrichment projects succeed and fail, here's what separates them:

Start with your use cases, not the tools. What decisions do you make based on firmographic data? What personalization do you need? Work backward from actual requirements. Tools are means, not ends.

Don't enrich everything. Enriching your entire database sounds satisfying until you get the bill. Prioritize active pipeline, engaged leads, and target accounts. The rest can wait or skip enrichment entirely.

Build feedback loops. When reps find bad data from enrichment, make it easy to flag. Review flags monthly. If patterns emerge (e.g., "technographic data is consistently wrong for EMEA accounts"), adjust your approach.

Re-enrich on a schedule. Job changes happen constantly, somewhere around 30%+ of B2B contacts change roles annually. Quarterly re-enrichment for active records keeps data fresh.

Integrate enrichment with your scoring. Clean data makes scoring work. If you're investing in enrichment, make sure your lead scoring models actually use the enriched fields. Otherwise, what's the point?

Monitor what matters. Track match rates, accuracy, and ROI. If enrichment costs $500/month but helps close one additional deal worth $50K, that's a win. If it costs $5,000/month and you can't tie it to revenue impact, reconsider.

FAQ

What is Salesforce data enrichment?

Salesforce data enrichment is the process of enhancing your CRM records with additional, verified information from external sources. This typically includes contact details (email, phone, LinkedIn), professional data (title, seniority), and firmographic data (company size, industry, technology stack). Enrichment happens automatically through integrations, filling gaps and correcting outdated information.

What happened to Data.com?

Salesforce retired Data.com in 2020. There's no direct replacement at the same price point. Most organizations now use third-party enrichment tools from the AppExchange or connect external providers via API integrations.

How do I set up automatic enrichment in Salesforce?

The most common approach uses Record-Triggered Flows. Create a flow that fires when a lead or contact is created (or when specific fields are blank), then use HTTP Callout to query your enrichment provider's API. The response populates the appropriate fields automatically. For more complex scenarios, middleware platforms like Zapier or Make can orchestrate the data flow.

Which enrichment tool is best for Salesforce?

There's no single best tool, it depends on your data needs, target market, and budget. ZoomInfo and Cognism offer comprehensive databases but are expensive. Apollo and Lusha provide more affordable entry points. Aggregation platforms like Databar connect multiple providers for better coverage. Test match rates against your actual data before committing to annual contracts.

How often should I re-enrich Salesforce data?

For active records (current pipeline, engaged leads, target accounts), quarterly re-enrichment catches most job changes and company updates. For historical or dormant records, annual refreshes are typically sufficient. High-velocity sales teams with fast-changing markets might benefit from monthly refreshes on their hottest segments.

Can enrichment hurt my Salesforce data?

Yes, if implemented poorly. Low-accuracy data sources can overwrite correct information with bad data. Missing field mapping creates inconsistencies. Enriching without governance rules leads to conflicting values across records. Start with clear mapping, protected fields, and accuracy monitoring to avoid making things worse.