The B2B predictive analytics space is at a tipping point. Between all of the funding announcements, press and content, it seems that we may be eminently close to crossing the chasm of adoption where predictive analytics becomes more mainstream for B2B marketing and sales teams.
The problem I see, however, is that it’s still unclear what predictive analytics actually means for B2B companies. Until there’s a general understanding of what it is and the benefits users can see, we may continue to linger at the threshold of mass adoption.
In most cases, the term predictive analytics is synonymous with predictive scoring. We at Leadspace believe this undersells what predictive analytics can achieve. It goes beyond just scoring.
We worked with David Raab, a well-respected analyst covering the predictive analytics space, to dissect the industry and come up with a clean structure to understand the different business applications and ways to evaluate vendor offerings. This Buyer’s Guide to Predictive Analytics for B2B Sales and Marketing includes the following:
- Predictive Analytics 101
- Differentiators: data types, modeling and outputs
- Applications like predictive scoring, lead discovery and data enrichment
- Buying advice