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:
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:
Attribution is like a box of chocolates. It can be really expensive, or it can be really cheap. It requires making a lot of decisions as to how you actually want to consume it. It may leave you feeling ill! Join the guys for a 45-minute walk across the attribution landscape. And back. And back again. Because mama always said you shouldn't stop at the last click.
What better time to ask Big Questions about analytics than the start of a new year? In this episode, Gary Angel from EY joins us to talk just a little bit about his new book, and to talk a lot about digital transformation: what it means, what's holding large enterprises back, where digital analysts fit in the effort... and a whole-whole lot of thoughts and ideas that aren't nearly as lofty and nebulous as the first part of this description sounds! This is our longest show to date. It's a power hour transformed into 59 minutes (or 39:20 if you play it at 1.5x speed).
People, places, and things referenced in this episode include:
One year of shows. It was our initial Big Hairy Audacious Goal, and we did it. We hoped you had as much fun this year listening as we did recording, and we'd like to take a chance to reflect. Did we hit our initial KPIs (because of course we had them)? Did we have a favorite show? Is there something we'd like to do next year? Tune in and end 2015 by listening to a podcast about a podcast. We think our navels look awesome. Come gaze with us!
We had a hypothesis that our listeners might be interested in hearing an expert on digital optimization. In this episode we test that hypothesis. Listen and learn as Kelly Wortham from EY runs circles around the lads, and brings them to an understanding of what digital testing means in 2015. In an hour so optimized it only takes 45 minutes, it's 2015's penultimate episode of the Digital Analytics Power hour.
People, places, and things mentioned in this episode include:
Have you noticed that neither Michael, Jim, nor Tim are women? They did! But that didn't stop them from taking on the subject of women in digital analytics (with diversions into the subjects of women and scotch, and women in professional poker). Joining them for this episode (because they may be a little misguided at times, but they're not absolute morons) was Krista Seiden from Google. Krista is a notable woman in analytics...but that is the LAST way she ever wants to be described. Luckily, she made an exception for us just this one time.
People, places, and things mentioned in this episode include: