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
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.
“Knowing which accounts are in-market has allowed us to shift and be more agile in our marketing strategy. 6sense helps us focus on accounts that will move the needle.”
Explore resources
A Guide to Pre-intent Data
Introduction Meeting your customers ahead of time Intent data is the key to modern B2B selling. It empowers marketing and sales teams to identify accounts that have started searching for solutions. By flagging accounts as soon as they begin their buying journeys, intent data helps revenue teams begin outreach sooner and win more deals. But […]
How To: Identify and Influence the Entire Buying Team
Introduction Selling and marketing are harder than ever. Old-school tactics are pushing modern buyers away, leaving revenue teams frustrated, inefficient, and unable to compete. In No Forms. No Spam. No Cold Calls, Latané Conant delivers the recipe for scalable, repeatable, data-driven sales and marketing strategies that work today. In this How To, we provide a practical, […]
Buying Intent: The Future of Sales & Marketing
Introduction Buying intent transforms sales and marketing by removing guesswork and revealing which accounts are likely to buy and what’s driving their decision-making. This guide will explain what buying intent is and how revenue teams can use it to reduce go-to-market waste and achieve higher ROI. Buying intent: What is it and why is it important? Fifty-seven to 70 percent of a […]
Ways Our Operations Team Turns 6sense Data into Action
Saima Rashid, SVP of Marketing & Revenue Analytics at 6sense, discusses the critical steps necessary to turn data into insights, and insights into actions. She discusses the need for transparency and accessibility to key performance indicators (KPIs) through a centralized dashboard, which Saima describes here. One of the key benefits of using 6sense Revenue AI […]
The Guide to Account Identification
Introduction How do you identify your target customers? Do you use data, or rely on generalized personas and guesswork? (Spoiler alert: Data gets better results.) In this guide, we’ll explain how identifying accounts effectively can provide actionable customer insights, reduce sales and marketing waste, and activate more personalized engagement. It’s hard to take an account-based […]
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.