Nuno P. if your goal is to predict the likelihood of a prospect converting, which I think it is, I wouldn't rely on CRM data only . As a couple other people have said you have data about the contact, and all their interactions both on and off your website and web properties... Then you have data about the account or company, provided that you sell a high ticket product where the buying committee is multiple people. Then you have information about the companies.. firmographics, tech used, leadership structure. These are three separate but related data sets. The idea is to figure out, based on all the data that you have, and all the data that you don't yet have about the past but can look up retroactively, and do Factor analysis, meaning: what are certain combinations of factors (such as size activity on the website, companies structure, number of decision makers involved....) that are shared among closed won deals. Once you have this understanding you can build a model that will weigh each Factor ( datapoint) and certain combinations accordingly. It's not going to be scores only it's also going to be thresholds, meaning if an ICP fit account collect a huge score because they are actively consuming your stuff and are all over your website, but for example, they never book a demo, then they prob should be considered hot lead.... So its gonna be a company nation of scoring as well as puring people and companies into buckets.... Hth 🙂
We solved this with some custom automation thru make.com... lmk your use case, might be able to help.
