Predictive Sales Analytics
Predictive sales analytics is the process by which intelligent algorithms are able to analyze key sales performance indicators in order to deliver accurate sales projections and even provide actionable intel. Such algorithms become increasingly accurate over time as more data is analyzed.
The best predictive sales data live in a sort of Maslow’s Hierarchy of Needs:
- Basic Fit data is the fundamental layer. The most predictive data point is Job Title.
- Intent data comes next. The most predictive intent data point is Companies Comparing the Products of Other Vendors in Your Category. But intent data is meaningless unless it’s informed by fit data. Companies can “compare the products of other vendors in your category” all day long, but without the proper fit criteria such as industry, department budget, or complimentary technologies – a sale will never happen.
- Finally, the data stack is topped with more sophisticated Opportunity data. The most predictive data point in this category is Requests for Proposal / Pain Points. But once again, without fit and intent, that RFP will never turn into a winning proposal.
The combination – and mutual integration – of predictive sales analytics data can be difficult and expensive outside of an integrated platform like DiscoverOrg.