From firmographics to market signals, AI promises deeper account intelligence than traditional data providers ever delivered. But pushing untested enrichment directly into Salesforce risks polluting core systems, breaking reporting, and eroding confidence across sales, marketing, and ops.

Traction Complete’s new product, Complete Discover, is designed to close that gap.

The company has introduced Complete Discover as a way to turn Google Sheets into an experimentation layer for AI-driven account enrichment—a place where teams can test prompts, validate outputs on real accounts, and uncover go-to-market insights without touching production data in Salesforce.

In short, it’s a playground for AI curiosity—with guardrails.

From AI Ambition to Operational Reality

The launch addresses a growing tension inside RevOps teams. Leaders want to explore AI enrichment that goes far beyond static firmographics—think sub-industry detail, market-level context, growth signals, and competitive insights. But operations teams are tasked with keeping Salesforce clean, consistent, and auditable.

According to Traction Complete CEO David Nelson, too many organizations are forced to choose between those two priorities.

“What we’re seeing in the market is a growing disconnect between AI ambition and operational reality,” Nelson said. “Too many teams are forced to choose between innovation and data integrity.”

Complete Discover is positioned as the missing middle layer—where AI enrichment can be explored, pressure-tested, and refined before it ever becomes operational.

Why Google Sheets Is the Right Testing Ground

Choosing Google Sheets isn’t accidental. It’s where revenue teams already explore ideas, test hypotheses, and share early insights before committing them to systems of record.

Complete Discover effectively turns Sheets into an account data lab, allowing teams to:

• Experiment with AI enrichment prompts

• Compare AI-generated insights against known data

• Identify what’s useful, what’s noisy, and what’s wrong

• Iterate quickly without governance risk

This approach mirrors how analytics teams validate models before deployment—but applied to AI-driven GTM data, where mistakes can directly impact pipeline, targeting, and sales execution.

Beyond Basic Firmographics

One of the key themes behind Complete Discover is that enrichment has outgrown traditional data categories.

Basic firmographics—company size, location, industry—are now table stakes. AI makes it possible to surface richer, harder-to-find insights, but only if teams can trust the outputs.

Complete Discover enables revenue teams to explore and validate enrichment such as:

• Hard-to-find firmographics, including private SMB data and companies outside North America

• Validation and supplementation of location, headcount, and industry fields

• Automatic industry normalization across records

• Revenue estimates and year-over-year growth rates derived from company name or domain

• Real-world sales intelligence, including M&A activity, technology usage, and competitor relationships

This shift toward sub-industry and market-level context reflects a broader MarTech trend: precision targeting over volume-based enrichment.

From Experiment to Execution With Complete AI

Crucially, Complete Discover isn’t a dead-end sandbox.

Once teams identify prompts and enrichment logic that consistently deliver value, they can deploy those workflows directly into Salesforce using Complete AI, Traction Complete’s no-code automation layer.

That handoff is where governance comes back into play. Complete AI allows RevOps teams to scale validated insights with:

• Consistent application across accounts

• Clear rules and controls

• No engineering dependency

• Protection of Salesforce as a trusted system of record

The result is a structured pipeline from experimentation to execution—something that’s been largely missing as AI tools flood the RevOps stack.

Why This Matters for RevOps Teams

As AI moves from novelty to necessity, revenue operations teams are increasingly responsible for deciding how AI gets used—not just if it does.

The risk isn’t underusing AI. It’s deploying it too quickly, without validation, and undermining trust in core data systems.

Complete Discover reframes AI enrichment as a RevOps-led discipline, not a vendor-driven black box. It gives teams a way to answer critical questions before scaling:

• Does this enrichment actually improve segmentation or targeting?

• Is the data consistent enough to automate?

• Where does AI outperform traditional providers—and where does it fall short?

Stephen Daniels, VP of GTM & Strategic Operations at Cresta, highlighted the appeal of that nuance.

“The product delivers nuanced, sub-industry insights that go far beyond what typical data platforms provide,” Daniels said. “It puts the information I’ve always wanted right at my fingertips—precise, comprehensive, and effortless to capture.”

The Bigger Picture: AI Needs a Staging Environment

Complete Discover reflects a larger shift happening across MarTech and RevOps: AI needs staging environments, not just production endpoints.

Just as modern data teams rely on dev, test, and prod environments, AI-driven enrichment demands a similar lifecycle. Tools that jump straight into Salesforce risk backlash when data quality slips or insights fail to translate into results.

By positioning Google Sheets as the “AI test kitchen” and Salesforce as the execution layer, Traction Complete is aligning AI enrichment with how operations teams already think about risk, governance, and scale.

As AI continues to expand what’s possible in go-to-market strategy, platforms that respect operational reality—not just innovation hype—may be the ones that actually stick.

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