We’ve all experienced predictive analytics: it’s the data science used to make personalized product recommendations for you on Amazon, Netflix and other sites. And predictive analytics is way ahead of lead scoring in helping companies close new business.
Large B2B and B2C companies have been using predictive analytics (PA) for years to better prioritize sales leads, determine which products a prospect would be most likely to buy, nurture contacts who aren’t yet ready to buy, and develop more reliable sales forecasting. In the last few years SaaS predictive analytics have become available for mid-market companies, too.
The first step in predictive analytics is making available your CRM so the software can profile existing customers and accounts (predictive analytics can potentially be applied at either the contact or account level). PA vendors then add public data about thousands of attributes from social media activity to patents filed to jobs posted to your prospect data. From all of this data they find correlations between prospects and existing customers to prioritize the best prospects.
PA is not for small companies; it takes too much data. Talking with one SaaS PA provider they told me that a minimum client would need at least 400 existing customer accounts and 100,000 records in their CRM. But for mid-market and enterprise companies predictive analytics can create a huge competitive advantage.
Did you think this was interesting? Then sign up to get our daily email marketing tip that people call “very impressive and helpful”
