Who is Cloudset?

As one of Zendesk’s pioneering implementation and app partners, Cloudset specializes in making complex technical processes easy to understand and simple to achieve.

• Core Mission: Since 2009, Cloudset has provided best-practice Zendesk implementation services, helping customer support teams optimize their use of the platform.

• Custom Solutions: They develop add-on applications for Zendesk that enable sophisticated and tailored support solutions.

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The Context

Cloudset’s founder, Graham, had one primary goal: to build his dream database of qualified, accurate company information. He wanted to identify every company with 200+ employees across the US, UK, and major European countries that used a specific customer support platform.

In the past, Graham had tried multiple technographic data sources, including BuiltWith and Apollo, but consistently found the data to be outdated and incomplete. Many companies listed as platform users were not, while many actual users were missed entirely.

In Graham’s words: “The main motivation was ABM influenced. It was not only inefficient to include out-of-target customers, it’s a contribution towards not spamming people. We have done our research and we have now a legitimate interest.”

Business Development Blockers

• Lack of Sales Technology Expertise
  The team was unfamiliar with the latest AI-powered sales techniques and lacked a reliable method for verifying technographic data or finding platform users beyond what standard tools could offer.
• Inadequacy of Standard Databases
  Cloudset had exhausted all the typical sources for technographic data, including Apollo, BuiltWith, and Sales Navigator. Each provided inaccurate or incomplete information, leaving Graham frustrated with the results.

How Cloudset met TAM Acceleration

In July 2024, Cloudset’s founder, Graham, discovered TAM founder Matteo’s profile featured on La Growth Machine’s expert advisor page. After booking a call with Matteo, Graham was confident that TAM Acceleration was the right partner to finally build the high-accuracy database he had always envisioned.

Initial Goals

Before the project began, the objectives were clear:

• Use the latest AI techniques to ensure the accuracy of the customer support platform data.
• Merge multiple databases to find as many enterprise platform users as possible.
• Implement a scoring system based on the confidence level of the technographic data.
• Use a combination of advanced scrapers, data providers, and AI to confirm the platform’s presence.
• Update the HubSpot CRM with enriched contact data and create automated tasks to manage SDR activities.

How did we proceed?

We applied a custom variation of our proven methodology to build the ultimate database for Cloudset.

• TAM Analysis: Analysis of your TAM, ICP and Channel
• Highly Qualified Database Creation: Build your segmented, highly qualified lead list using Clay and AI Agents
• The Atlas Infrastructure: Create the necessary email and Tech Infrastructure to avoid spam
• The Aries Funnel: Find the Funnel and Message that brings you the highest response rate
• Scaling the Machine: Let’s scale your results by automating, connecting all the dots, and reverse engineering the system

How did we proceed then?

1. Company List Aggregation

We started by compiling a master list of companies in Clay.com. We merged data from multiple sources (BuiltWith, Apollo, Sales Navigator) and supplemented it with companies that followed the target platform on LinkedIn or were actively hiring for platform-specific roles.

2. Initial Company Filtering

On this master list, we applied a primary filter based on Cloudset’s criteria:

• Geography: US, UK, and main European countries.
• Size: 200+ employees.

3. Company Qualification and Verification

Companies that passed the initial filter entered a "waterfall" verification process to confirm they used the target platform. This multi-step process included:

• Verifying the existence of a platform-specific subdomain using JavaScript and Zenrows scraper.
• Scraping Google to find a valid platform URL.
• Deploying a Clay AI Agent to perform an autonomous search.

If any of the three steps returned a positive result, the company was confirmed as a platform user. A scoring system was applied to rank companies confirmed by multiple methods.

Behind the curtain – Process visual

Behind the curtain – Process visual

4. Contact Identification (Phase 1)

Once we had a verified list of companies, we identified key decision-makers by sourcing contacts from Apollo and Sales Navigator.

• All contacts were imported into Clay for de-duplication.
• We then created three tiers of seniority, with Tier 1 being the primary ICP, and excluded irrelevant keywords (e.g., intern, sales, success).

5. Contact Identification (Phase 2)

For companies where no contacts were found in Phase 1, a secondary waterfall procedure was initiated. Using Apollo and Clay AI Agents, we performed targeted searches for specific roles to ensure maximum coverage.

6. Email Finding and Validation

All contacts for qualified companies were enriched with verified work emails. For contacts in Tiers 1 and 2, we also sourced phone numbers.

7. CRM Enrichment and Task Automation

Finally, all enriched contacts were synced to the HubSpot CRM via Lemlist. Using Make.com, we automated the generation of call tasks in HubSpot for the SDR team to manage their activities efficiently.

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In Summary over the first 4 months we have:

• Generated an extremely targeted Database, that the client was trying to build for years
• Qualified and Disqualified companies and contacts based on strict ICP criteria
• Saved 300+ hours of the client time in sourcing these leads

The Results Achieved – In 4 Months

+6287 In-Target Database

+14046 Qualified Contacts

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