Client Snapshot

We initially pitched three competitors. The client came back with something far more specific: rather than buying a generic competitor list, they wanted the data structured around their own ICP definitions – and then overlaid with competitive intelligence.

What the client defined:

The VP of Marketing provided two distinct ICP frameworks reflecting the company’s dual deployment model:

• Private ICP – companies whose infrastructure, compliance requirements, or data sovereignty needs make them candidates for on-premise or private cloud help desk deployments
• Cloud ICP – companies whose size, tech maturity and operational model align with cloud-hosted help desk adoption

Each ICP came with its own set of target personas – the specific titles and functions most likely to evaluate and purchase help desk software within companies matching that profile.

Our scope: find the companies that are verified customers of a named competitor and match one of the two ICP definitions and include decision-makers aligned to the specified personas.

This was not a simple competitor scrape. It was a three-layer filter: competitor tech stack → ICP match → persona alignment.

Data fields delivered per record: Contact name · Job title · Verified business email · Phone numbers · Company name · Website · Physical address · State · Country · ZIP code · SIC code · Industry · Revenue size · Employee size

We delivered approximately 1,842 verified companies and around 5,276 decision-maker contacts, all focused on the competitor within the client’s displacement target set.

Every record passed through the client’s dual-ICP framework and persona criteria before inclusion. The result was not a broad competitor list – it was a surgical dataset where every company and every contact had been pre-qualified against the client’s own go-to-market logic.