Context
Pharmaceutical research services company targeting decision-makers within 400 biotech and pharma organizations across Europe and the US. Relevant buyers held inconsistent titles across organizations.
The problem
Standard title-based targeting was unreliable. Relevant stakeholders used 20 to 40+ different job title variations. Targeting by title alone would miss a significant portion of the actual buying population.
What changed
- Built a keyword-based extraction system across LinkedIn profiles, working from profile content rather than title matching.
- Analyzed job experience descriptions and role context, not just title fields.
- Scored profiles on keyword relevance and frequency across profile content.
- Ranked candidates on contextual fit to the actual buying role.
Outcome
- Accurate identification of decision-makers across all 400 target accounts.
- Consistent targeting maintained despite 20 to 40+ title variations per role.
- Dataset aligned with real functional relevance rather than label-based assumptions.
- Signal-based system replicable across future account sets without manual review.
