We thought we deserved a break from the podcast, so we went looking for some AI to take over the episode. Amazon Polly wasn't quite up to the task, unfortunately, so we wound up sitting down as humans with another human -- Erik Driessen from Greenhouse -- to chat about the different ways that automation can be put to use in the service of analytics: from pixel deployment to automated alerts to daily reports, there are both opportunities and pitfalls! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Happy New Year! Sure. The ball has dropped in Times Square, and a new year means an opportunity to look forward. But, we wanted to take a quick look back first -- on the industry, on the podcast, and on the world in general. From GDPR to Bayesian statistics to machine learning and AI to... podcast (and #mattgershoffed) stickers, 2018 was, clearly, the Year of the Analyst. So keep analyzing! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

What's the hot new technology of 2018? AI? Deep Learning? Pole-dancing robots? Maybe. Or, maybe it's customer data platforms (CDPs) -- a topic we actually covered way back in January 2017 on episode #053 with Todd Belcher, who, at the time, was with CDP provider BlueConic. Since then, Todd left BlueConic to start CDP Resource, which is, well, a resource for companies looking to select, implement, and maintain a CDP. We asked Todd to come back on the show to give us the rundown on how there is now -- finally -- clarity, consolidation, and maturity in the space, as all of the providers have aligned around a common definition of what a CDP is, what it does, and how it should do it. Alas! The space isn't even remotely there yet! We have yet to even reach the peak of inflated expectations! Which was probably why it was such an informative discussion. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Humans are creatures of habit. And analysts — those of us who haven't been so drawn into the world of artificial intelligence that we have become cyborgs, at least — are humans. In this episode, the gang explores the good and the bad side of analytical habits: what analyses we gravitate towards, how we go about approaching those analyses, and, to some extent, how those habits are impacted by our organizational environments. With a side dish of, "What is a data scientist, anyway?" (because who can resist a question that is both rhetorical AND controversial?!). For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

For the second year in a row for the podcast -- but the first appearance since Moe joined the crew -- we headed to the Hunguest Grandhotel Galya outside Budapest for Superweek, one of the most unique conference experiences in the digital analytics industry: comfortably isolated over an hour outside of Budapest in a beautiful setting, it's a temporary community of, for, and by the analyst. With sessions ranging from GDPR to machine learning to attribution to media analytics, the spaces before, between, and after the presentations were extended discussions with great people on a wide range of topics. The "fireside chat" on Wednesday evening was a recording of the podcast with a live audience, where we had attendees to share tips and ideas that we found particularly intriguing. And had quite a bit of fun along the way. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

2017 was a big year for both the digital analytics industry and for the Digital Analytics Power Hour. Join us, won't you, as we (figuratively!) gaze upon our navels? From the traction the #womeninanalytics movement gained on multiple fronts, to the looming promise of machine learning and AI getting a real foothold in the field, to the podcast finally adding a co-host who is universally admired, we had a lot to talk about! We had a LOT to talk about. Trust us, we edited this episode down heavily! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Let's pretend your goal as an analyst is to eloquently and accurately explain reinforcement learning. Now, let's pretend that you get to try that explanation again and again, and we'll give you an electric shock every time you state something inaccurately and a cookie every time you say something right. Well, you're an analyst, so you're now wondering if this is some clever play on words about cookies. As it happened, we didn't give Matt Gershoff from Conductrics any cookies of any kind in his return to the show. Instead, we gave him a lifetime's supply of opportunities to say, "Well, no, it's not really like that," which is a special kind of nourishment for the exceptionally smart and patient! In other words, the gang walked through a range of analogies and examples about machine learning, reinforcement learning, and AI with Matt, and no electric sheep were harmed in the process.  For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Are you biased? Either you answered, "Yes," or you're in denial. Or you're an AI, in which case you should just go and start your own podcast instead of listening to this one. UNLESS your prediction algorithms told you that this would be the episode where we would finally announce the addition of a third co-host, and you need to collect that data point (and, damn, you're good, BTW). On this episode, though, our THREE (count 'em!) co-hosts dive into different types of biases that analysts (should) grapple with, how they spot them, and what they do to take advantage of them (or mitigate them, as appropriate).  For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

The machines are coming! The machines are coming! Artifiicial Intelligence is here. But what is it, and how long will we have to wait for the technology to completely take over all analysis work? Dennis Mortensen -- founder of x.ai -- joins us on this episode for a deep dive into the topic. You will be surprised by how pragmatic and real AI seems as Dennis describes how he approaches it. And...then his last call will completely blow up the nice, cozy layer of downy comfort that you've settled into during the discussion. So it goes. Artificial intelligences and things referenced in this episode include: x.ai, Alexa, Siri, Cortana, Planet Money Episode #626, Wait But Why on The Fermi Paradox, and Rick and Morty.

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.

Philosopher, poet, and essayist George Santayana wrote, "Those who cannot remember the past are condemned to repeat it." We thought we'd have him on to reflect about the history of digital analytics...but he died in 1952. Ambrose Bierce wrote The Devil's Dictionary, which we think is brilliant, so we thought we would have him on...but he died in 1842! Lucky for us, we landed the best of both worlds with very-much-alive philosopher, poet, essayist, DAA founder and chairman, and eMetrics founder Jim Sterne.

People, places, and things mentioned in this episode officially ran a full, certifiable gamut:

The Devil's Data Dictionary The Digital Analytics Association (DAA) eMetrics The Web Analyst's Code of Ethics Some "web analytics" platforms: Sawmill (still going strong!), Analog (less so), NetGenesis (verymuchlessso) The IAB The DMA A bunch of people (or, in one case, an archetype, and, in another a conscious, gestalt, artificial intelligence system): Krista Seiden, Seth Romanow, Eric Peterson, June Li, Stéphane Hamel, Josh Aberant, HiPPOs, Skynet