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Once upon a time, there was some data. And that data cried out to be extracted and analyzed and packaged up like the most exquisite of gifts and then presented gloriously to an eager and excited group of stakeholders. But, alas! Will this data story have a happy ending? Perhaps. Perhaps not! And that's the subject of this episode. Sort of. Our intrepid hosts ask the question, "How can we communicate more effectively by applying the tricks of the data journalism trade?" To answer that question, Walt Hickey, late of fivethirtyeight.com and now the founder and curator of the daily Numlock Newsletter, joins the gang to chat about how he combined an education in applied mathematics with an interest in news media to become a data journalist. Along the way, the discussion explores how Walt's insights can be applied to business analytics. And there's a terrible analogy about meat that gets butchered along the way (thanks, Tim!).
For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Are you reading this? If so, then you are literate. But, are you (and are your stakeholders) data literate? What does that even mean? On this episode -- recorded in front of a live audience at Marketing Evolution Experience in Las Vegas -- the gang tackled the topic. Mid-way through the show, they were delighted to be joined on stage by Gary Angel (unplanned, but due to a series of unfortunate travel and communication mishaps -- recording with a live audience is exciting! He is officially over halfway to joining the podcast's Five-Timers Club)! It was an engaging discussion with some smart questions from the live audience.
For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Under the 'guise of a discussion about making the leap into a new technology, this bonus mini-episode (hopefully) clears up the on-going confusion about the Kiss Sisters. Moe sat down with her big sister, Michele, to chat about jumping into learning an entirely new skill when time is short, expectations are high, and the learning curve is steep. The specific example they chat about is Michele's dive into Google Analytics data in BigQuery using SQL, but the tips and thoughts are applicable to any new and intimidating platform.
Put this in your pipe and smoke it: all of the tracking we try to do of people is actually technology designed to track content. And, even that tracking of content was a hacked-together repurposing of a system designed to deliver content. In other words, we've got layers of fiction upon fiction that we're trying to muddle through (and, often, ignore) as an industry. The result? A ridiculous level of inefficiency whereby brands overspend to ineffectively reach their target audiences with direct response messages, and well-intended intermediaries grow their bank accounts. Ugh! On this episode, the gang invited Sergio Maldonado from PrivacyCloud (and, by day, from Sweetspot Intelligence) to chat about the broken environment we're operating in, as well as how GDPR and financial considerations may just force us onto a path of shaking it up!
For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Regression. Correlation. Normality. t-tests. Falsities of both the positive and negative varieties. How do these terms and techniques play nicely with digital analytics data? Are they the schoolyard bullies wielded by data scientists, destined to simply run by and kick sand in the faces of our sessions, conversion rates, and revenues per visit? Or, are they actually kind-hearted upperclassmen who are ready and willing to let us into their world? That's the topic of this show (albeit without the awkward and forced metaphors). Matt Policastro from Clearhead joined the gang to talk -- in as practical terms as possible -- about bridging the gap between traditional digital analytics data and the wonderful world of statistics.
For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Thanks for stopping by. Please get comfortable. We're going to be taking a few notes while you listen, but pay that no mind. Now, what we'd like you to do is listen to the podcast. Oh. And don't worry about that big mirror over there. There may be 2 or 3 or 10 people watching. Wow. We're terrible moderators when it comes to this sort of thing. That's why Els Aerts from AGConsult joined us to discuss user research: what it is, where it should fit in an organization's toolkit, and some tips for doing it well.
For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Bayesian vs. Frequentist. False Positive vs. False Negative. Truth vs. Uncertainty. It's the world of A/B testing! In this bonus mini-episode, Moe sat down with Chad Sanderson from Subway to discuss some of the pitfalls of A/B testing -- the nuances that may seem subtle, but are anything but trivial when it comes to planning and running a test.
If you have a smartphone nearby and you are not wearing a foil hat, chances are that some brand somewhere -- and probably several brands in many places -- know where you are. Is that creepy? Maybe. It's likely removing a few taps when you check what the weather will be like tomorrow, and there might just be a coupon for a discounted hamburger just waiting to pop up when you get near your favorite QSR around lunchtime! In this episode, James Fogelberg from Landmarks ID joins the gang to discuss the ins and outs of using the ubiquity of mobile to the advantage of both brands and consumers.
For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Have you ever walked out of a meeting with a clear idea of the analysis that you're going to conduct, only to find yourself three days later staring at an endless ocean of crunched data and wondering in which direction you're supposed to be paddling your analysis boat? That might not be an ocean. It might be an analytics rabbit hole. In this episode, the gang explores the Analysis of Competing Hypotheses approach developed by Richards Heuer as part of his work with the CIA, inductive versus deductive reasoning, and engaging stakeholders as a mechanism for focusing an analysis. Ironically, our intrepid hosts had a really hard time avoiding topical rabbit holes during the episode. But, acknowledging the problem is the first part of the solution!
For complete show notes, including links to items mentioned in this show and a transcript of the discussion, visit the show page.
That's right. We're trying to grow the reach of this podcast, so we figured we needed to do some growth h---...NO! No. No. NO!!! We're NOT going to use that term. But, it turns out that growth marketing has some interesting concepts. On the one hand, you may think, "Don't I already do that?" And the answer is quite possibly, "Yeah. Pretty much." On the other hand, you may think, "Oh, well that's an interesting lens through which to view the world." And, that is okay, too. Either way, check out this chat Moe had with Krista Seiden from Google on the subject.
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