Deal Closure Prediction based on User's Browsing Behaviour of Sales Content

We present PrediTilk, a data-driven win prediction service based on user's browsing of sales content, such as quotes, competitor comparisons or product sheets. It makes part of our GDPR-compliant system of electronic document tracking designed for marketing and sales, and addresses win prediction problem (also known as deal closure prediction). The latter consists in estimating the probability of a given opportunity to close, becoming a customer. Given the information about user's consultation of documents issued from our tracking system, our service predicts win probability of this opportunity using machine learning models. Our evaluation shows that PrediTilk provides accurate predictions, while being purely based on automatically collected data about user's browsing behaviour. Besides, it can provide objective signals to a CRM system, where most of the prospects data are entered manually. The combination of such sources can become a highly valuable asset for win prediction.