GTMStack
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Data Management GTM Engineer

Enrich Contacts Automatically

Automatically enrich every new contact with firmographic, technographic, and social data the moment they enter your CRM or GTM tools.

The problem

New contacts enter the CRM with just a name and email. Reps waste time manually researching companies, and incomplete data breaks lead scoring, routing, and personalization workflows.

The outcome

Automatic enrichment fills 85%+ of critical contact and company fields within seconds, enabling instant lead scoring and routing.

The problem

A prospect fills out a form with their name, email, and company. That’s all you know about them. To score this lead, route it to the right rep, and personalize outreach, you need their job title, seniority level, department, phone number, company size, industry, revenue, tech stack, and funding status. Getting this data manually takes 5-10 minutes per contact. At 200+ new contacts per week, that’s a full-time job nobody wants to do.

Without enrichment, your downstream systems break. Lead scoring assigns the wrong scores because it’s missing firmographic data. Routing sends enterprise leads to SMB reps because company size is blank. Personalization falls back to generic templates because there’s nothing to personalize with.

How GTMStack solves this

GTMStack enriches contacts automatically at the moment of creation, ensuring every downstream workflow has the data it needs.

Trigger-based enrichment. When a new contact enters your system — via form submission, list import, event capture, or manual creation — GTMStack immediately queries its enrichment engine to fill in missing fields. This happens before lead scoring, routing, or any workflow triggers execute, so those systems always have complete data to work with.

Multi-source enrichment. GTMStack doesn’t rely on a single data provider. It aggregates enrichment data from multiple sources and uses confidence scoring to select the best value for each field. If one provider has the job title but not the phone number, and another has the phone number but an outdated title, GTMStack assembles the most complete and accurate profile from all available sources.

Firmographic data. Company name, industry, employee count, annual revenue, headquarters location, founding year, and public/private status. This data feeds directly into ABM scoring and territory-based routing.

Technographic data. What tools and technologies the company uses: CRM, marketing automation, analytics, cloud infrastructure, and more. This is critical for competitive positioning — if a prospect uses a competitor’s product, your outreach should acknowledge that. Tech stack data also feeds into product-fit scoring.

Social and contact data. LinkedIn profile URL, Twitter handle, phone numbers, and other contact methods. The integrations module uses these to enable multi-channel outreach without reps manually hunting down contact information.

Enrichment freshness management. Company data changes constantly — people get promoted, companies grow, tech stacks evolve. GTMStack re-enriches contacts on a configurable schedule (30, 60, or 90 days) to keep data current. When enrichment data changes for a contact at a target account, the account owner gets notified.

Enrichment audit trail. Every enrichment action is logged: what data was added, from which source, and when. This transparency helps your team understand where their data comes from and troubleshoot quality issues when they arise.

Results you can expect

Teams using automatic enrichment in GTMStack see immediate improvements across their GTM stack:

  • 85%+ field completion rate on critical contact and company fields, up from 20-30% on form submissions alone
  • Instant lead scoring and routing because enrichment runs before downstream workflows
  • 70% reduction in manual research time for SDRs preparing for outreach
  • Higher personalization quality across email, phone, and LinkedIn outreach

The upstream investment in enrichment multiplies the effectiveness of every downstream process: scoring, routing, personalization, and reporting all work better with complete data. Read implementation guides on the blog.

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