What is a Revenue Data Platform?

The problem with how GTM teams manage data today

Most B2B sales and marketing teams are running on a stack that was never designed to work together. A contact database here. An enrichment tool there. A reverse ETL connection duct-taped to the CRM. The result: data that's incomplete, inconsistent, and out of date by the time anyone acts on it.

A Revenue Data Platform is the answer to that problem. Not another point solution -- a unified system that connects enrichment, activation, and intelligence into a single platform that revenue teams can actually use.

What is a Revenue Data Platform?

A Revenue Data Platform is a purpose-built infrastructure layer for B2B go-to-market teams. It aggregates data from external enrichment providers, internal systems (CRM, product, support), and real-time signals, unifies it into a coherent model of your accounts and contacts, and pushes the output back into the tools your teams use -- Salesforce, Slack, Outreach, HubSpot -- automatically.

The defining characteristics of a true Revenue Data Platform:

• Multi-source aggregation. Pulls from third-party enrichment providers (150+ in the case of Lantern), first-party product data, and behavioral signals simultaneously -- not sequentially.

• Unified data model. Resolves conflicts between sources into a single, deduplicated view of every account and contact. No more "which version of this record do I trust?"

• Autonomous execution. AI agents run enrichment, scoring, and workflow logic without manual triggers. The platform acts on data, not just stores it.

• Reverse ETL. Enriched, scored data flows back into Salesforce, HubSpot, and other downstream tools automatically -- not via CSV export or manual import.

How it differs from what most teams are using today

Traditional B2B data tools fall into one of a few buckets: contact databases (ZoomInfo, Apollo), enrichment workflow builders (Clay), intent platforms (6sense, Demandbase), or reverse ETL pipes (Census, Hightouch). Each solves a slice of the problem.

A Revenue Data Platform replaces all of them with a single system. The key differences:

• Data coverage without subscriptions. Instead of managing 6-10 separate vendor contracts, you get a unified enrichment layer across 150+ providers.

• Semantic understanding. The platform builds a custom data model -- a Revenue Ontology -- specific to your business: your territory logic, your account hierarchies, your product lines. It understands what "enterprise account" means in your context, not generically.

• Action, not just enrichment. Most enrichment tools stop when they've added data to a record. A Revenue Data Platform runs the downstream workflow -- scoring the account, routing it to the right rep, triggering the sequence, updating the CRM field.

Who uses a Revenue Data Platform

The primary buyers are VP of Revenue Operations and Head of Revenue Operations at B2B SaaS companies with 50-5,000 employees. These are the people responsible for making the GTM stack work -- and they're the ones most frustrated when it doesn't.

Secondary buyers include CROs who care about pipeline quality, VP of Sales who need their team to act on better data, and GTM engineers who are tired of building and maintaining bespoke data pipelines.

What they have in common: they've tried stitching together point solutions and found the maintenance cost exceeds the value. They want a platform that handles the infrastructure so their team can focus on revenue.

The Revenue Ontology: what makes a platform "semantic"

The term that separates a Revenue Data Platform from a general-purpose enrichment tool is the Revenue Ontology -- a custom data model built around each customer's specific business.

Where a generic enrichment tool treats every company the same, a semantic Revenue Data Platform learns your business: which firmographic signals predict a good fit for you, how your account hierarchy is structured, what "ready to buy" looks like in your pipeline. This semantic layer is what makes the agents' decisions defensible -- not just data-driven, but business-aware.

What changes when you run on a Revenue Data Platform

The practical outcomes for revenue teams:

• Reps work with complete, accurate account data rather than hunting for it manually.

• Signals -- champion job changes, intent spikes, product usage events -- trigger automated workflows instead of getting buried in reports nobody reads.

• CRM data quality improves continuously rather than degrading between quarterly cleanup sprints.

• The GTM stack consolidates from 10+ tools to one unified platform, reducing both cost and coordination overhead.

The stat that tends to land with RevOps leaders: 70% of CRM data becomes obsolete every year. A Revenue Data Platform is the only architecture designed to fix that continuously rather than intermittently.

Is Lantern a Revenue Data Platform?

Lantern is the Revenue Data Platform built for enterprise. It aggregates 150+ enrichment providers into a unified account model, deploys AI agents that run research, scoring, and CRM hygiene workflows autonomously, and pushes results back into Salesforce, Slack, and Outreach in real time -- with forward-deployed engineers who configure and optimize the system alongside your team.

If you're evaluating whether a Revenue Data Platform is the right architecture for your GTM stack, see how Lantern works with your existing tools.