Investor-Startup Matching Algorithm
A rules-based matching system connecting entrepreneurs with the right investors, backed by hypothesis testing on funding round patterns.
TL;DR: Before building matching logic, test which factors actually drive variation in the data — hypothesis testing on funding patterns turned an arbitrary filter list into a weighted, evidence-based system.
The Problem
Founders raising a round rarely know which investors are actually a fit — stage, sector focus, ticket size and geography all narrow the realistic list. Kiota Intelligence needed a way to shortlist relevant investors for a given entrepreneur automatically, instead of relying on manual scouting.
The Approach
I built a matching system that filters the investor universe against a startup's profile (industry, stage, funding needs) using a combination of rule-based filters and scoring logic in R. To validate which factors actually mattered, I ran hypothesis tests on historical funding round data to check whether round size and structure varied meaningfully across sectors and stages — findings that fed directly into how the matching filters were weighted.
Outcome
The resulting tool produced ranked investor shortlists per startup profile, replacing manual scouting with a repeatable, data-backed process used internally by the Kiota Intelligence team.
Key Takeaway
Design insight: Before building matching logic, test which factors actually drive variation in the data — hypothesis testing on funding patterns turned an arbitrary filter list into a weighted, evidence-based system.
FAQ
What is the key takeaway from "Investor-Startup Matching Algorithm"?
Before building matching logic, test which factors actually drive variation in the data — hypothesis testing on funding patterns turned an arbitrary filter list into a weighted, evidence-based system.
Who wrote this and what is it about?
This was written by Mahmoud Trigui, Senior Data Scientist. Matching system to connect entrepreneurs with the right investors using multi-filter logic and hypothesis testing on funding round variations.