- Those with blindsight can detect and respond to visual stimuli around them, but they’re not aware of and can’t really know what they’re seeing
- Without advanced analytics, b-to-b professionals receiving information still don’t really know what works and what doesn’t
- Advanced predictive analytics is the part of the b-to-b brain that turns sensory data into usable information to drive high-functioning businesses
Picture a person (we’ll call him by his initials: LB) seated at a table. LB is unsighted. Since suffering a traumatic brain injury many years ago, he has been completely blind. LB’s world is in darkness, and he requires assistive devices to navigate his surroundings.
In the experiment in which he has agreed to participate, a researcher sitting across from LB holds up her hand with three fingers extended and asks LB to tell her how many fingers she’s holding up. At first, LB pleads ignorance. “How could I possibly know?” he asks. “Just guess,” the researcher says. They go back and forth in this vein a couple of times until LB finally sighs and says, “OK, fine. Three.”
“Correct!” the researcher shouts. They try it again. Again, LB gets it right. They try the experiment in another way – the researcher places three objects on the table. “Please reach out and pick up the cube,” she says. Once again, he objects that he can’t see anything; again, he is successful when he finally tries. As they repeat the experiment in other forms, LB isn’t successful every time, but he’s clearly not just guessing, either.
This ability to “see” is called blindsight, and it occurs in people who have suffered damage to their brain’s visual cortex whose eyes are still taking in data from the world around them. When asked how he determined the answer, LB would respond that he just had a “gut feeling” about the things he reported on correctly, but he didn’t know what he was seeing.
The stunning insight for researchers was that people (and other animals) can see and use information that enters through their eyes, without actually “knowing” they can see. Without knowing, they think and behave as if they’re not taking in any visual information. For a fully sighted person, seeing is equated with being aware of what one sees. For someone with blindsight, it’s not necessarily the seeing that’s lacking, but the awareness of seeing.
Blindsight Is Still Not Seeing
Having an accurate gut feeling is certainly better than nothing at all, but researchers have so far failed to convince people with blindsight that they can use these feelings to navigate their world effectively. It’s one thing to act on hunches about how many fingers a researcher is holding up – but quite another to cross a busy street or figure out what’s on a computer screen. To be confident in going about typical daily activities, simply receiving visual stimuli is not enough. People must be aware of seeing for the information to be useful.
Many b-to-b organizations are suffering from a form of blindsight. In this analogy, our customer-facing systems – sales force automation, marketing automation, content management, product – are our eyes, interacting with the world and taking in stimuli. In most cases, however, either we don’t have a functioning visual cortex, or the connections between the cortex and the eyes are broken. We have gut feelings about who our best customers are, which are our best leads, which demand creation tactics are engaging prospects, who we should call next and who should be included in nurture programs – but we’re not using the information that’s streaming into our organizations to actually know for sure.
Those who have been on the front lines of b-to-b marketing and sales for the past decade or so have powerful and valuable instincts about what works. But instinct and gut feelings are not the same as facts. Navigating an increasingly complex and competitive business environment effectively requires real knowledge. The good news is that the part of the b-to-b brain that can supply that knowledge – data science and statistics – is finally available to all of us. Over the past two years, we’ve published a vast array of research pieces and publicly available blog posts and webcasts, and given several talks at SiriusDecisions events covering the advanced (predictive) analytics space and how it can benefit b-to-b professionals. Below is a compendium of these resources, and we urge you to bring your organization’s visual cortex up to its full functionality – to add real knowing to those gut feelings.
Attend my presentation on analytics at SiriusDecisions Technology Exchange in Austin this November!
6Sense: Finding In-Market Buyers With Predictive Intelligence
6Sense: SiriusDecisions: Predictive Intelligence for Sales Development
An Introduction to Propensity Modeling
Applying Predictive Analytics
Considering a Predictive Lead Scoring Vendor?
Has Your Hot Prospect Well Run Dry?
How to Evaluate Predictive Lead Scoring Vendors
I’m a Mac...I’m a PC: Using Predictive Analytics to Differentiate Between Your Buyers and Their Buyers
Leveraging Predictive Technologies for Account-Based Marketing
Mintigo: Demystifying Predictive Lead Scoring
Mintigo: How to Be a Data-Driven Marketing Powerhouse With Predictive Analytics & Big Data
New Predictive Analytics Announcements
New Relic: Advancing the Use of Predictive Analytics
Optimizing Personas With Predictive Analytics: From Cluster to Buyer
Predictions Really Do Come True
Predictive Analytics Applications: Predictive Prospect Sourcing
Predictive Analytics for Demand Creation and Account Based Marketing
Predictive Analytics for Lead Generation: Implementation Considerations
Predictive Analytics: Can We Handle The Truth?
Predictive Lead Scoring: Questions to Ask Vendors
Predictive Segmentation: To Lump or to Split?
Predictive: “Ride-Sharing Solution” for Marketing
Radius: Go Beyond Lead Scoring: How Analytics Power Outbound Marketing
Radius: Go Beyond Lead Scoring: How to Leverage Predictive Analytics
Radius: SiriusDecisions Presents: A Buyer’s Guide to Selecting the Right Predictive Marketing Vendor
SiriusDecisions Marketplace: Predictive Lead Scoring Vendors
The Account-Based Marketing Technology Ecosystem
Use Cases for Predictive Analytics
Using Predictive Segmentation to Achieve Demand Creation Precision and Scale
Using Propensity Modeling to Identify Account Risk and Upsell Opportunities