Using algorithms and data to shortcut deal identification and prioritization.

Hi All,

Brand new here, but would be curious to know have or are developing their own algorithms to short cut deal sourcing and prioritization of acquisition targets.

I have access to a data set of 420M Linked IN profiles, about 18 million company profiles (inc owner / leadership contact info) via one of my business partners. Going to run an experiment over the next couple of weeks to see if I can create an algorithm that identifies US, lower middle market companies that may be looking for an exit. Thinking of keying off of information like owners age (are they 55+), length of ownership, presence of a family member in the company with the same last name, etc, past private equity acquisitions, etc.

Be open to input and ideas on what other characteristics, behaviors, or patterns I should consider when building this model.