It's a specialized solution, but if you want to derive more value ot the data you already have, this is one way of doing that. D and the added benefit of doing i think, is that it also, it, i don't t say diintermediates the marketing stack, but it kind of sits right on top of that stack, right? So in addition to your ecommerce layer and your crem lator, your webon later, whatever, ou know, if you have a customrn intelligence layer that is able to consume those ntosdiferent data sources, and do so repeatedly and scalebly. That case is closer to what we callo,
What IS customer intelligence? What is a customer? Is the customer best understood by breaking the word down into its component parts: "cuss" and "tumor?" Would that be an intelligent thing to do? Will these and related questions some day be answered by self-aware machines? Will any of *these* questions be answered on this episode? Give it a listen and find out!
The mish-mash of companies, products, and miscellany mentioned on this show include: Adobe, Oracle/ATG, SAS Customer Intelligence, Salesforce.com, Scott Brinker (Chief Martec), Domo, Data Studio 360, Tableau, iJento, Netezza, SPSS, Unfrozen Caveman Lawyer, Eight Is Enough, Legend of the Plaid Dragon (and the Slack version), Office Vibe, p-value article on fivethirtyeight.com (and the p-hacking app), and the "AI, Deep Learning, and Machine Learning" video.