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How GTM Teams Use HG Insights Data in Clay to Build a Stronger Sales Pipeline

If your team is already using HG Insights data in Clay, you’re ahead of many organizations that leverage technographic intelligence for go-to-market (GTM) strategies.

However, if your workflow stops at pulling a list of companies using a technology adjacent to your product and pushes those contacts directly into an outreach sequence, you’re only scratching the surface of what technographic data can provide.

Knowing that a company uses a technology is a starting point, not a strategy.

What you’ll learn in this session


In this AMA session, HG Insights’ CTO, Satish Grandhi, joins Stefan Kollenberg and Alex Lindahl from Clay and Elias Stråvik from The Kiln to show how leading GTM teams use technographic intelligence more strategically within Clay workflows.

In the replay, you’ll learn:

  • Two primary ways top teams use HG Insights data within Clay
  • How technographic signals can be used for smarter  account prioritization
  • The “anti-signal” strategy for identifying and eliminating poor-fit accounts
  • How to identify real displacement opportunities using technology usage trends

From technographics data to pipeline intelligence

Most technographic datasets tell you which technologies a company uses. What they rarely show is how important those technologies are to the organization. Signals like Total Product Signal Count, Intensity Score, and Verified Date Trends help GTM teams understand whether a technology is deeply embedded across an organization or quietly losing ground. That shift from binary fit to contextual intelligence is what turns technographic data into a true pipeline asset.

Two ways GTM teams use HG Insights data in Clay

During the session, we discuss two primary ways teams are using HG Insights data inside Clay, and the most effective teams combine both approaches.
  1. Net-new account targeting Build highly targeted account lists based on specific technology usage across your ideal customer profile (ICP), for example, identifying companies running a given technology with high usage intensity.
  1. Account prioritization Enrich existing CRM accounts with HG Insights signals such as IT spend forecasts, usage intensity, and verified technology usage dates to prioritize which opportunities deserve immediate attention.
  As Elias Stråvik shows in the session, combining these approaches enables powerful total addressable market (TAM) mapping and account prioritization strategies.

The “anti-signal” strategy

Most teams use technographics data to find companies to pursue. The strategic move is to use it to identify whom not to pursue. In the AMA, Elias shares how some teams run technology lookups specifically to disqualify poor-fit accounts, saving API credits, sales bandwidth, and campaign budget while dramatically improving list quality. In the full session, Satish, Stefan, Alex, and Elias walk through real Clay workflows used by GTM teams, frameworks for building high-precision TAM models, and practical ways to prioritize accounts using technographic signals, and answer some of the audience’s top questions.