I am very sceptical the approach which i think larger, older companies are more prone to take. I feel like there's something missing that makes it a practic to get to a practical reality. Identity is a real, tough, tough nut to crack because you need some way of identifying who customers are. So when you start typing custmer intelligence on scale, i thinkthat the one one issue you run into real fast is how you work with un premised data and cloud data. Data ta no that e clinis is feels comfortable keeping in e cloud, and for how long, and how you do it.
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.