If you’ve seen the massive MarTech supergraphic from Scott Brinker, you know there are more than enough marketing technologies to make anyone’s head spin. In the “Data” category alone, there 500+ companies in 9 verticals: Audience/Market Data, Marketing Analytics, Mobile & Web Analytics, Dashboards & Data Visualization, Business/Customer Intelligence & Data Science, Cloud/Data Integration & Tag Management, DMPs, Customer Data Platforms, and – Predictive Analytics.
And, to make things even more fun, predictive analytics includes a variety of capabilities and use cases, from predicting outcomes in healthcare, detecting possible fraud, or identifying which prospects are most likely to become your next customers.
We’re right there with you, trying to wrap our heads around what technology can do for marketers today. To that end, our MarTech Intelligence series of research reports looks a various types of software platforms – capabilities, pros and cons, trends within that software vertical, and selected vendors for that space. We’ve already covered such staples as paid media management, SEO platforms, and marketing automation.
Now, we’ve added another category for your digital bookshelf: Predictive Analytics software for B2B marketers.
Our latest report, B2B Predictive Marketing Analytics Platforms: A Marketer’s Guide, is now available free for download. (Yes, we do gather some data from you at registration, but it seems a fair exchange.)
The report focuses on the lead discovery, scoring, and enrichment category of predictive marketing analytics. It includes the latest trends in the particular category, as well as a deep-dive into the capabilities of this type of software.
Profiles of selected vendors are also included, as well as information on what to ask when you are doing your pre-purchasing due diligence. We’ve also included examples of use-cases, to give you an idea of how marketers are finding success when they deploy this software.
Thanks to David Raab, our advisor on this report, which was researched and written by Karen Burka.