Spot buyers from the very beginning of their research. Meet them at every step of their journey armed with the details to build influence and win more deals.
Predictive Modeling

Poor timing kills deals
As marketing and sales leaders, you’re expected to have a knack for knowing which accounts to target. You need to figure out where buyers are in their journey, and what kind of messaging will actually get their attention.


Understand the buying journey
Predictive Modeling uses 6AI™ to interpret the myriad telltale signs of buying activity that pulse through the Signalverse™. It then determines the buying stage of each account so you can master the fundamental questions:
- Who should I prioritize?
- What should I say?
- When should I say it?
Get those answers right, and your sales volume, average contract value, and deal velocity soar.
Predictive Modeling turns data into action
Every day, 6sense’s Signalverse collects over a trillion pieces of B2B data. 6AI ties that data to specific accounts and contacts, then uses Predictive Modeling to analyze which accounts share the characteristics and behaviors of your best customers.
Predictive Modeling scores opportunities using factors including:
- ICP-fit
- Which key buying personas are engaged
- Buying stage
- Revenue potential
These characteristics help your marketing and sales teams prioritize and tailor campaigns and outreach.

End guesswork to multiply your ROI
This is where 6sense’s Predictive Modeling transforms your revenue strategy. Instead of hoping to catch buyers at the right moment, you’ll know exactly when and where to engage.
Frequently asked questions
What are predictive analytics in marketing?
Predictive analytics for marketing collects data to be analyzed using predictive models that identify ideal accounts, where they are in the buyer’s journey, and what contacts make up the buying team. Marketing uses these insights to effectively target buyers at the right time in their buying stages with the right message.
What are predictive analytics for sales?
Predictive analytics for sales collects data to be analyzed using predictive models that identify ideal accounts, where they are in the buyer’s journey, and which personas make up the buying team. Sales use these insights to effectively target buyers with the right message at the right time in their buying stages.
What are examples of predictive marketing analytics?
Some examples of predictive marketing analytics are ingesting intent data as a buyer researches on your website and after predictive modeling displaying the likely buying stage of that account. Another is taking historical data of how many interactions a certain buyer requires to move to the next stage in their buyers journey and using that insight to highlight buyers that likely need more marketing touches.
What are examples of predictive sales analytics?
Some examples of predictive sales analytics are ingesting intent data as a buyer researches on your website and after predictive modeling displaying the likely buying stage of that account. Another is taking historical data of how many interactions a certain buyer requires to move to the next stage in their buyer’s journey and using that insight to highlight buyers that likely need more marketing touches.