Building a Tiered LP Database Across Europe
Built an end-to-end LP sourcing framework using PitchBook and Capital IQ to support a VC fund raise
Rashi Bansal
Financial Analyst at Northstar Analytics
From their time as
Financial Analyst
Northstar Analytics • 2024
Overview
Rashi took on the LP sourcing project at a point where the VC needed to identify and prioritize potential limited partners across Europe for a new fund raise for a VC based in Europe. The brief was clear in its goal but required building the research infrastructure from scratch.
The Story
Rashi took on the LP sourcing project at a point where the VC needed to identify and prioritize potential limited partners across Europe for a new fund raise for a VC based in Europe. The brief was clear in its goal but required building the research infrastructure from scratch.
She pulled data from PitchBook and Capital IQ, supplementing those databases with independent research to identify LPs who were likely to be interested in the fund's thesis. The core challenge was not just finding names, but deciding which contacts were worth the VC's time. The total LP list was of about more than 1,300 names.
To solve that, she built a tiered classification system, ranking LPs into Tier 1, Tier 2, and Tier 3 based on fit, likely interest, and strategic value to the fund. The team used this tiering directly to sequence their outreach, starting with the highest-priority contacts.
The tiering framework performed better than the team expected, given that the underlying data came from public databases. The conversion rate from outreach was significant, and the team converted 25% of the 24 Tier 1 contacts into first meetings within 2 months. Despite relying on public-database inputs rather than proprietary data, the tiering framework matched or exceeded the team's benchmark for outreach efficiency.