How we use natural language processing to qualify leads
In this blog post I’ll explain how we’re making our sales process at Xenetamore effective by training a machine learning algorithm to predict the quality of our leads based upon their company descriptions.
Head over to GitHub if you want to check out the script immediately, and feel free to suggest improvements as it’s under continuous development.
It started with a request from business development representative Edvard, who was tired of performing the tedious task of going through big excel sheets filled with company names, trying to identify which ones we ought to contact.
This kind of pre-qualification of sales leads can take hours, as it forces the sales representative to figure out what every single company does (e.g. through read about them on LinkedIn) so that he/she can do a qualified guess at whether or not the company is a good fit for our SaaS app.
And how do you make a qualified guess?