Four reasons why B2B is so good for predictive analytics
Glen Westlake, CEO and co-founder at BrightTarget and author of B2B Marketing's Introduction to predictive analytics, explains why predictive analysis represents a huge opportunity for B2B businesses
Companies with lots of customers and products who sell to other businesses are missing out on a huge opportunity to learn from their historic transactions to identify new sales.
Using modern machine learning and predictive analysis, it is now easier than ever to identify this hidden opportunity in your customer data – and the best bit is that the opportunities are huge, typically worth millions of pounds.
There are four key reasons why machine learning works so well for B2B sales and marketing:
1. Accuracy: With B2B sales, machine learning is incredibly accurate. Similar businesses have similar needs and therefore the machine draws on it’s existing knowledge – making more accurate predictions. As businesses are more logical and less emotional (not as much affiliation with a brand) compared to consumer sales (B2C) they are easier to predict.
2. Breadth of data: Mature B2B organisations are sat on stacks of data. This broad data set is great for the machine to learn from and includes amazing knowledge on what customers actually need and what works. This is ideal for data mining and machine learning to discover where the best opportunities are.
3. Size of opportunity: B2B organisations with lots of customers and products will have many gaps in their customer to product mix. Once these gaps are identified this is a huge opportunity.
4. Capability already exists: For most B2B organisations with this hidden opportunity in their data, they already have the capability to use this information and sell to their customers. BrightTarget shows the opportunities, your B2B marketing team provide the execution.