Pop psychology is fun, if not that useful. Pop analytics can be dangerous! What IS pop analytics? It's a term coined (as far as we can tell) by analytics legend Kevin Hillstrom, and we managed to get him on the show to chat about it! The fact that it turned into a therapy session for Tim was just an added bonus. NOTE: We hit a glitch with Kevin's audio 45 minutes into the episode and have done our best to work around it. It was especially painful, in that he had some very nice things to say about the show, but, alas, the choppy audio means we won't be able to repurpose the clip for marketing purposes! We apologize for the glitch. It was something we didn't recognize for what it was when it happened, but now we know!
See the show notes, links, and transcription at: http://www.analyticshour.io/2017/01/17/054-pop-analytics-with-kevin-hillstrom/.
Do you care about acquiring customers? Do you care about data? Do you like wearing shoes that have soles that are 2-3″ thick? Put those three things together and it means you care — or should care — about customer data platforms. On this episode, Todd Belcher from BlueConic joins us to explain what CDPs are and what they’re good for. Tune in to hear Todd masterfully steer clear of a sales pitch for his company…while Michael transitions on the fly from getting a basic understanding of CDPs…to installing BlueConic on this site…to pitching BlueConic himself!
For complete show notes, including links and the show transcript, go to: http://www.analyticshour.io/2017/01/03/053-customer-data-platforms-with-todd-belcher-2/.
2016 is almost in the books! In just over a week, we'll be ringing in the new year, and we have it on Very Good Authority that 2017 will be the Year of Mobile. But, this episode is as much about looking back as it is about looking forward -- looking back on how our industry has evolved, what product launches piqued our interest the most, and what Snoop Dogg-related stunt marketing occurred during the year. We even do a little navel gazing about the podcast itself: our favorite topics and guests (although we love ALL the topics and guests!), and a bit of news about what will be happening with the podcast in 2017. So kick back, bust open a few roasted chestnuts, spike your eggnog generously, and give it a listen! Technologies, services, and random items mentioned in this episode include: more past episodes than are worth linking to, RSiteCatalyst, Hidden Brain podcast: Can Social Science Help You Quit Smoking for Good?, SUPERWEEK, Matt Gershoff, Caleb Whitmore, Adobe Summit, eMetrics, MeasureCamp, Un-Summit, Digital Analytics Hub, Gary Angel / Digital Mortar, Paco Underhill / Why We Buy: The Science of Shopping, Jan Exner, Justin Cutroni, Kevin Hillstrom, Measure Slack, Lee Isensee, Tableau, Domo, the Domo stunt at the Tableau Conference, John Scalzi, Joe Haldeman, and Philip K. Dick.
Have you ever seen a one-man show in the theater? It's awesome. Unless it's terrible. The same can be said for one-person digital analytics teams. It can be awesome, in that you get to, literally, do EVERY aspect of analytics. It can be terrible because, well, you've got to do EVERYTHING, and it's easy for the fun stuff to get squeezed out of the day. On this episode, we head back Down Under for a chat with Moe Kiss, product (and digital) analyst at THE ICONIC. Whether you pronounce "data" as DAY-tuh or DAH-tuh, Moe's perspective will almost certainly motivate you find new ways to push yourself and your organization forward. People, places, things, sites, and doodads mentioned in this episode were many, and they include: R, Tableau, Snowplow, adjust, Datalicious, Moe's post on Analysis of Competing Hypotheses, Moe's post on getting started in digital analytics, Jeffalytics.com, RSiteCatalyst, The Millenial Whoop, Kabaddi, Michael Yates, ABC (the Australian Broadcasting Corporation), an Event Tracking Naming Strategy from Chris Le, Simo Ahava, Nico Miceli, and Towards Universal Event Analytics - Building an Event Grammar by Snowplow co-founder Alex Dean.
If you're in the U.S., happy election day! In the spirit of the mayhem and controversy that the political process brings, we're tackling a topic that is every bit as controversial: tag management. Does Adobe DTM gratuitously delete emails? Has GTM been perpetually unaware of when it is around a hot mic? What does Tealium have against coffee?! Is Signal broadcasting dog whistles to marketers about the glorious data they can collect and manage? What about Ensighten's sordid past where the CEO was spotted in public (at eMetrics) sporting a periwig? To discuss all of this (or...actual content), Josh West from Analytics Demystified joins us for a discussion that is depressingly civil and uncontentious. Many linkable things were referenced in this episode: Josh's Industry War starting blog post (from 2013), Adobe Dynamic Tag Management (DTM), Google Tag Manager (GTM), Signal, Tealium, Ensighten, Ghostery, Observepoint, Hub'scan, the Data Governance Episode of the Digital Analytics Power Hour (Episode #012), PhoneGap, Floodlight / Doubleclick / DFA, In the Year 2000 (Conan O'Brien), Bird Law, Adobe Experience Manager (AEM), Webtrends Streams, data management platforms (DMP), the Personalization Episode of the Digital Analytics Power Hour with Matt Gershoff (Episode #031), josh.analyticsdemystified.com, and Tagtician.
You know what season it is? Well, in the United States, we're closing out a 4-year, never-ending cycle of electing a president. The tweets are getting tweeted and retweeted, the Facebook posts are getting posted and reacted to, and the video! Oh, the video! So, what better time to dive into social media ANALYTICS than today? Join Michael and Tim as they dive into this topic -- which they both love to hate -- with Hayes Davis, co-founder and CEO of Union Metrics. You might even want to Snapchat a filtered picture of yourself listening to it to someone! Miscellany mentioned in this episode include: Union Metrics, Great Lakes Brewery Christmas Ale, The Innovator's Dilemma, Oreo's Super Bowl Blackout tweet, WhatsApp, Scott Brinker on People vs. Data/Strategy/Technology, csvkit, SQLite, medium.com, and Is this my interface or yours?
Have you ever read an analytics job description? Have you found yourself wondering, "Is it just me, or is there something fishy going on here?" Who better to verbally cogitate this question writ large than a couple of guys who haven't actually applied for a job in a few years? Join Michael and Tim as they dive into the world of analytics job descriptions and chat about the red flags they find...and the various tangential thoughts that the exercise itself sparks. Resources mentioned in this episode include: the Digital Analytics Association, Google Tag Manager Updates: Workspaces and User Manager by Amanda Schroeder from LunaMetrics, Revamped User Interface in Google Tag Manager by Simo Ahava.
Do you listen to podcasts? Well, of course you do! Are you working in or involved with analytics? If you listen to this podcast, you almost certainly are! Where do those two interests intersect? On this episode! Steve Mulder, Senior Director of Audience Insights at National Public Radio (NPR), joins Michael and Tim to discuss podcast measurement...and audience measurement...and the evolution of analytics...and standards (well...guidelines)...and more! Tim fanboys out in a way that would be embarrassing if he was sufficiently self-aware to be embarrassed. In other words, it's a rollicking good romp through public media. Resources and the like mentioned in this episode are many and varied: The User Is Always Right, Podtrac, Public Broadcasting Podcast Measurement Guidelines (bit.ly/podcastguidelines), Comscore, DFP, Splunk, NPR One, Panoply Network, Gimlet Media, IAB, MediaShift: Bulgarian Analytics Startup Aims to Fix How Publishers Use Data, Smart Choices: A Practical Guide to Making Better Decisions, the NPR Politics Podcast, and Planet Money #669: A or B.
The intro bumper for this podcast says "the occasional guest," and, yet, the last five episodes have had guests. That's hardly "occasional," so Tim and Michael had a choice: either change the intro or do an episode on a topic for which both of them have experience, interest, and, hopefully, at least modest authority. In this show, the guys dig into hypotheses: how to identify and articulate them, the pitfalls involved in *not* clearly stating them, and where they see organizations and analysts get tripped up. They have a hypothesis that you will get some value out of the show, and, if they're right, that you will share the show with a colleague and maybe even give it a positive rating on iTunes. People, places, and things referenced in this episode: Helen Hunt, Twister, Mythbusters, assumption governance, the Science Vs. podcast, and the Invisibilia podcast.
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.
Somebody wants to overthink their analytics tools? Tell 'em their dreamin'! We wanted to talk about open source and event analytics and Snowplow sits right at that intersection. Our guest Simon Rumble is the co-founder of Snowflake Analytics and one of the longest users of Snowplow. We wrap up the show with all the places you can find Simon and Tim in the next few months. Fun fact: You will also learn in this episode that conversion funnels go down the opposite direction in Australia.
Once upon a time, in an industry near and dear, lived an analyst. And that analyst needed to present the results of her analysis to a big, scary, business user. This is not a tale for the faint of heart, dear listener. We're talking the Brothers Grimm before Disney got their sugar-tipped screenwriting pens on the stories! Actually, this isn't a fairy tale at all. It's a practical reality of the analyst's role: effectively communicating the results of our work out to the business. Join Michael and Tim and special guest, Storytelling Maven Brent Dykes, as they look for a happy ending to The Tale of the Analyst with Data to Be Conveyed.
Tangential tales referenced in this episode include: Web Analytics Action Hero, Brent Dykes Articles on Forbes.com, The Wizard of Oz, Made to Stick, Data Storytelling: The Essential Data Science Skill Everyone Needs, The Story of Maths, and mockaroo.com.
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.
In this episode, we dive deep on a 1988 classic: Tom Hanks, under the direction of Penny Marshall, was a 12-year-old in a 30-year-old's body... Actually, that's a different "Big" from what we actually cover in this episode. In this instant classic, the star is BigQuery, the director is Google, and Michael Healy, a data scientist from Search Discovery, delivers an Oscar-worthy performance as Zoltar. In under 48 minutes, Michael (Helbling) and Tim drastically increased their understanding of what Google BigQuery is and where it fits in the analytics landscape. If you'd like to do the same, give it a listen!
Technologies, books, and sites referenced in this episode were many, including: Google BigQuery and the BigQuery API Libraries, Google Cloud Services, Google Dremel, Apache Drill, Amazon Redshift (AWS), Rambo III (another 1988 movie!), Hadoop, Cloudera, the Observepoint Tag Debugger, Our Mathematical Universe by Max Tegmark, A Brief History of Time by Stephen Hawking, and a video of math savant Scott Flansburg.
As Dr. Phil says, "Never put more into a relationship than you can afford to lose." Not sure what that has to do with Excel but it sounds vaguely wise, which is the whole point. Tim and Michael try to be your relationship coach for Microsoft Excel. Despised by data scientists, but used by everyone else, where are the boundaries and who has what it takes to enforce them. Join us in an exploration of our digital analytics love/hate affair with that most ubiquitous of analytics tools.
To outsource or not to outsource -- that is the question:
Whether 'tis more efficient to tap
The skills and talents of those who bill by the hour,
Or to bring resources inside as full-time staff,
And, by doing so, manage them.
To contract, to outsource -- No more -- and by outsource to say we get
Our insights and our implementation work
Managed by others -- 'tis a scenario
Devoutly to be wished. To contract, to outsource --
To outsource, perchance to analyze. Aye, there's the rub.
Besides ignoring iambic pentameter in the process of butchering a Shakespearean reference, this episode, perchance, also makes reference to the following:
If you're like most analysts, you've probably changed jobs since the last episode of this podcast hit your earbuds two weeks ago. Or, if you haven't actually changed jobs, then you've at least been hounded by recruiters who wish you would. No matter how you look at it, digital analysts have lots of opportunities to bounce between companies at a frequent pace, and many analysts do just that. On this episode, we talk with Dylan Lewis, who has been doing digital analytics at Intuit since before there were federal taxes (give or take a few years). Give it a listen. You just might decide you need a personal board of directors!
If nothing else, this episode might inspire you to check out http://careers.intuit.com, which would be ironic given the topic, but definitely understandable!
Back by popular demand: attribution! This time, we brought in an adult on the subject: Jim Novo of The Drilling Down Project. A lot of questions get tackled in this episode: Should "gut feel" ever trump "the data?" Which is a better analogy for attribution: PV=nRT or the distillation of bourbon? Will this podcast *ever* have flawless audio quality? These questions and more definitively answered. All in under 52 minutes.
Are you a data scientist? Have you pondered whether you're really a growth hacker? Well...get over yourself! Picking up on a debate that started onstage at eMetrics, Michael, Jim, and Tim discuss whether a fundamental shift in the role (and requisite skills) of the web analyst are changing. You know, getting more "science-y" (if "science" is "more technical and more maths"). all in 2,852 seconds (each second of which can be pulled into R and used to build a predictive model showing the expected ROI of listening to future episodes; at least, we assume that's what a data scientist could do).
I know what you're thinking: they're world-class podcasters when they hide behind editing tools and autotune, but can they do it LIVE? This special recording from the final keynote spot at eMetrics has the three amigos of insight taking questions from Twitter and a live audience. There was bourbon, Jim Sterne, and a disagreement over the future of the industry - all in under 45 minutes. So, turn up the volume (seriously...because the sound levels were low and we did the best we could with a short-turnaround edit) and give it a listen!
You know what it's time we do? It's time we make analytics great again. How can we do that? With three guys who know about winning. Maybe not winning with real estate. Or with steaks. But winning with analytics. Are these three guys winners? Well, for the sake of 40 minutes of audio, let's say they are. And then we'll let you, the people, decide.
Gratuitous pop culture references in this episode include: DJ Khaled, Larry David (on SNL), and Louis CK.
What is life but a series of questions? Does that question even make any sense? We'll never know, as this wasn't a question that got asked on this episode. Instead, Tom Miller, co-host of the Measured Direction podcast, joined us to give us a taste of the format of his show: user-submitted analytics questions asked and answered on the fly. What do you do when you lose a room of executives 15 minutes into your presentation? What does the future hold for digital analytics? Will we ever be able to measure the impact of TV? Who would win in a bar fight between Robocop and the podcast hosts? Find out the answers in a mere 45 minutes of audio (30 minutes if, like our guest, you listen at 1.5X speed).
People, places, and things mentioned in this episode include:
We've got the technology. We've got the behavioral data. We've got the content (or at least tell ourselves we do). We're all set to develop personalized experiences that knock consumers socks off and leave them begging us to take their money. Is it really that simple? If it is, why aren't more companies realizing the dream of 1-to-1 marketing? Matt Gershoff joins us to discuss how the pieces of the personalization puzzle often don't quite fall into place like we wish they would. Matt's also written a post that overlaps with our discussion: http://conductrics.com/complexity.
As an analyst, it's never a good idea to make predictions without data. With that said, for our first predictions episode, we've chosen to make some big and small predictions for the digital analytics space for the remainder of 2016 -- using only experience and intuition! Join us in Episode 30 as we rely solely on intuition to predict the next 9 months of a multi-billion dollar industry - all in under 45 minutes. Note: Due to the lag between recording and release, our prediction during the episode about a certain Heisman Trophy winner actually came true...before this episode launched.
People, places, and things mentioned in this episode: