Who is the client?

Cloudset operates in the Zendesk ecosystem and supports customer experience implementations and related work.

Their growth depends heavily on correctly identifying companies that truly use the target platform and then reaching the right stakeholders inside those accounts.

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What was the problem?

Off-the-shelf technographic tools were inaccurate for their niche, which meant they couldn’t reliably identify all companies actively using the target platform.

Without trusted identification, outbound targeting suffers: reps waste time on the wrong accounts, and real opportunities remain undiscovered.

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The Approach we took:

• Defined what “verified” actually means for their ICP: We aligned on strict criteria: regions, size ranges, and what signals truly indicate active platform usage.

• Aggregated companies from multiple sources: We pulled candidates from several channels (ecosystems, directories, search patterns, and niche sources), then normalized and deduped the dataset into one clean base.

• Built a verification waterfall instead of a single check: We used layered verification methods such as subdomain patterns, website content signals, keyword detection, help-center structures, support-widget signals, and AI classification, then scored each company by confidence (A/B/C style tiers).

• Mapped decision-makers with validation: We used Clay, Apollo, and manual enrichment to map the right contacts, validated email data, and removed risky or low-quality records.
• Delivered CRM-ready outputs with prioritization: We packaged everything with scoring and structured fields so the sales team could import, prioritize, and start executing immediately.

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Results:

Cloudset received a verified dataset of 6,287 in-target companies and 14,046 qualified contacts mapped to those accounts.

The dataset was delivered in a CRM-ready format with scoring, enabling sales to prioritize high-confidence accounts first instead of guessing.

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