When you think about what goes into winning a Nobel Prize in a field like economics, it’s a lot like machine learning. In order to make a breakthrough, you need to identify an interesting theory for explaining the world, test your theory in practice to see if it holds up, and if it does, you’ve got a potential winner. The bigger and more significant the issue addressed by your theory, the more likely you are to win the prize.
In the world of business, there’s no bigger issue than helping a company be more successful, and that usually hinges on helping it deliver its products to those that need them. This is why I like to describe my company SalesPredict as helping our customers win the Nobel Prize in business, if such a thing existed.
In a nutshell, the SalesPredict solution helps a company identify its most likely prospects, and determines the actions that their salespeople should pursue to win the deal. To accomplish this, we’ve built a platform that consumes data from hundreds of public and private data sources to produce a machine learning model of a given prospect’s likeliness to buy. To make this actionable by salespeople, we boil everything down to a single numerical or letter score that they can sort on, and a set of actions that they should take for each prospect. But invariably, they want to know “Why?”