Our client is a specialist private equity firm focused on 5 core sectors – software, e-commerce, financial technology, healthcare, and digital infrastructure. The client wanted to leverage data science on traditional and alternate B2B data to identify the good fit companies and help prioritize the leads.
The client wanted to
- Build models to identify good-fit companies from the incoming leads
- Score companies to rank and prioritize for due diligence
- Lack of historical internal data on prior deal evaluations
- No set rules for evaluation of a company due to subjective nature and different viewpoints of investment teams
- Sparsity and low reliability of data for smaller private companies limited the ability to go granular