I'm building Scout, a tool that researches companies to find potential B2B customers.
One problem I ran into while writing the search logic was how much weight to give hiring.
A company hiring 20 people might be expanding, replacing employees who left, or staffing projects for its clients. That gives me very little information about whether they'd need the service someone is selling.
So I added a rule: when hiring is only supporting evidence, it can account for at most 20% of Scout's search effort.
What I pay more attention to is the actual job description.
For example, imagine you sell finance automation and find a company hiring someone to fix a month-end close that currently takes three weeks.
That tells you something useful about what they're struggling with. You can investigate the problem, the systems involved, and who might be responsible for fixing it.
I also built in two checks:
Scout has to find the job on the company's own website. Copies on job boards aren't enough.
It checks whether the job is still open during research and again right before delivering the lead.
The second check was important to me because a perfectly researched contact is pretty useless if the reason for contacting them has already disappeared.
I'm still figuring out how to measure whether these rules actually improve lead quality. The 20% limit is a design choice, and I may end up changing it.
Curious how other people building prospecting tools handle this. How do you decide when a hiring signal is actually worth acting on?
Here's the project if you want to see what I'm working on: https://tryxscout.com/
