Fivos Aresti cuts TAM to 5.7k

On May 21, Fivos Aresti published a case study on X showing how he narrowed a software client’s target market from 66,000 companies to 5,700 before launching outbound. The post said the list was built with data from BuiltWith, Crunchbase and Apollo, then normalized in Clay and checked with AI verification. Aresti said the goal was to replace broad-volume prospecting with a smaller list shaped around ideal-customer signals. Clay, BuiltWith, Crunchbase and Apollo all market integrations or workflows that support that kind of enrichment-driven process. ### How did the list shrink from 66,000 companies to 5,700? Aresti said the starting market contained 66,000 companies and the final working market contained 5,700, a reduction of about 91%. The post described a filtering process that combined firmographic and technology signals rather than relying on a single database export. The sources named in the workflow were BuiltWith, Crunchbase and Apollo, with Clay used to combine and standardize the records. (clay.com) Clay says its platform combines multiple data providers, AI agents and action layers in one workflow. Its documentation and product pages show direct integrations for BuiltWith, Crunchbase, Apollo and HubSpot, which matches the stack Aresti described in his post. Apollo separately says its HubSpot integration is designed to keep data synchronized across both systems. ### Why did HubSpot usage matter in the scoring? (clay.com) Aresti said the account scoring centered on ideal-customer fit around HubSpot usage. The post described HubSpot as one of the operating signals used to decide which companies stayed in the narrowed market and how they were prioritized for outreach. HubSpot’s presence in the workflow fits the way Clay describes its own HubSpot integration. (clay.com) Clay says users can import, create, update and manage HubSpot objects directly in Clay, which allows prospecting and enrichment data to be matched against CRM records before outreach begins. ### What happened after the market was narrowed? (clay.com) Aresti said the resulting accounts were split into tiers, with a “Dream 150” reserved for manual handling and lower tiers assigned to more automated outreach. The structure described in the post paired higher-touch research and personalization for the top segment with scaled sequencing for the rest of the list. (university.clay.com) Workflows.io, the growth studio Aresti co-founded with Dan Rosenthal, says it builds automated outbound systems and AI RevOps agents for B2B technology companies. A separate Growth Unhinged article published earlier this year identified Aresti as a source for a tactical outbound guide and said he shared first-hand playbooks and recipes from client work. ### Why did the post put so much emphasis on pre-email work? (clay.com) Aresti said pre-email work mattered for deliverability and pipeline quality. The case study described enrichment, verification and segmentation as steps that came before any sequencing, rather than after a broad send. Clay and Apollo have both recently promoted workflows that move from enrichment into outbound execution. (ai-ark.com) Clay said in an April 15 blog post that its Apollo integration supports faster enrichment and direct sequencing, while Apollo’s documentation says its HubSpot connection is intended to reduce setup errors and keep records aligned across systems. ### Where can readers see the full playbook next? (clay.com) Aresti’s May 21 X post remains the primary public source for the case study and includes the account-count reduction, the Dream 150 structure and the HubSpot-based scoring approach. Workflows.io and Aresti’s other public materials, including a Clay campaign template listed on Gumroad, show similar outbound and enrichment workflows built around Apollo, Clay and email infrastructure. (clay.com) (fivoscoldiq.gumroad.com)