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We just classified 250 million people across 50 million distinct job titles.
Traditional job title classification is broken because it assumes titles are universal. They’re not. A CMO in healthcare is a Chief Medical Officer. An Executive in Singapore is entry-level. A Director in the UK is C-suite.
We built a system that actually understands context across 75 million unique combinations of title, country, and industry. No lookup tables. No keyword matching. Just intelligent classification at massive scale.
Most providers dump what they can’t classify into “Other.” When you’re dealing with 50 million distinct titles, that’s not acceptable.
English-centric classification systems fail systematically because the same keywords mean completely different things across countries:
“Executive”
“Director”
“General Manager”
“Associate”
“Manager”
“Principal”
“Officer”
“Coordinator”
“Engineer”
“Trainee”
An English team building a keyword system would misclassify every single one of these. Multiply that by millions of professionals per country.
The same title in different industries means completely different roles:
“CMO”
“CDO”
“Principal”
“VP Operations”
Without industry context, you’re just guessing.
Instead of a 50-million-entry lookup table, we built a reasoning system:
Inputs:
- Job title
- LinkedIn industry (heavily weighted)
- Country of employment
- LinkedIn job description
Outputs:
- JOB_FUNCTION (21 categories)
- JOB_LEVEL (6 tiers)
- PERSONA (25 buyer archetypes)
The system triangulates across all signals. A “Senior Executive” in Singapore gets classified as manager-level. A “Director” in the UK gets C-suite. A “General Manager” in China gets CEO. Automatically. Every time.
Keyword Matching: Assumes “Executive” means the same thing everywhere. It doesn’t.
Lookup Tables: Can’t handle 50 million entries that change meaning by geography.
Rule-Based Systems: Try writing if/then rules for 75 million combinations. Impossible.
Our approach reasons about each title in context, handling all 250 million people through the same intelligent system.
Accurate ICPs: “Target Directors only” won’t exclude UK executives while including US middle managers.
Global Expansion: Launch in any country knowing titles are classified correctly for local context.
Less Waste: SDRs stop calling Singapore “Sales Executives” thinking they’re senior leaders.
Better Routing: Route based on actual roles, not incorrect assumptions about titles.
Job titles aren’t universal. They never were.
When you’re trying to reach 250 million professionals globally, knowing that an “Executive” in Singapore isn’t your senior buyer, that a “Director” in London IS your C-suite target, and that a “CMO” in healthcare has nothing to do with marketing—that’s everything.
We didn’t just build a better classifier. We built the only one that actually works at global scale.
Want to see how our classification handles your specific markets? Your RevenueBase account team can walk you through the logic for your target industries and geographies.
Mark Feldman
2025/10/17
Mark Feldman
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Mark Feldman
2025/09/28
Mark Feldman
2025/09/28
Mark Feldman
2025/09/28