Google bought Urchin in 2005 and, virtually overnight, made digital analytics available to all companies, no matter how large or how small. Optimizely was founded in January 2010 and had a similar (but lesser) impact on the world of A/B testing. What can we learn from ruminating on the past, the present, and the future (server-side testing! sample ratio mismatch checking! Bayesian approaches!) of experimentation? Quite a bit, if we pull in an industry veteran and pragmatic thinker like Ton Wesseling from Online Dialogue! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

It's the holiday season and, despite Tim's 27-slide deck making a case for why we should do an Airing of Grievances-themed show, we went in another direction. On this episode, we explore a delightful tale that exists at the intersection of "Giving Back to the Community" and "Growing the Analytics Talent Pool." Rob Jackson joined the gang to be peppered with questions about the what, why, and how of his digital marketing social enterprise: WYK Digital. It's an inspiring story of breaking down some of the barriers to digital-focused jobs for underserved youth. And doing so in the middle of a pandemic, no less! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Do you long for the days when your mother could ask you, "Now, what do you actually do for your job?" and "all" you had to do was explain websites and digital analytics? The "analyst" is now a role that can be defined an infinite number of ways in its breadth and depth. Is the analyst who is starting to do data transformations to create clean views still an analyst? Or is she a data engineer? A data scientist? On this episode, we explore the idea of an "analytics engineer" with Claire Carroll from Fishtown Analytics who, while she did not coin the term, can certainly be credited with its growth as a concept. And there is a brief but intense spat about the role of "analytics translator," which Claire sat out, but observed with bemusement. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Did curiosity kill the cat? Perhaps. A claim could be made that a LACK of curiosity can (and should!) kill an analyst's career! On this episode, Dr. Debbie Berebichez, who, as Tim noted, sorta' pegs out on the extreme end of the curiosity spectrum, joined the show to explore the subject: the societal norms that (still!) often discourage young women from exploring and developing their curiosity; exploratory data analysis as one way to spark curiosity about a data set; the (often) misguided expectations of "the business" when it comes to analytics and data science (and the imperative to continue to promote data literacy to combat them), and more! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Analytics is hard (so they say... but we're not going to open THAT can of worms). Do you know what's harder? Managing analysts! I mean, they're always asking, "Why?" Sometimes, they even ask it five times! They can wind up, you know, analyzing whatever you're asking them to do! On this episode, special guest Moe Kiss (you may know her as a co-host of this podcast) joined Michael and Tim to dig into the ins and outs of the analyst/manager relationship. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

No one has ever been disappointed by a sequel, right? Especially when the original was well-received both by the critics and at the box office. Well, Episode #134: "These Are a Few of Our Favorite (Analytics) Tips" scored an 83% Tomatometer with an audience score of 91% on Rotten Tomatoes. As it happened, those are the same scores that The Sound of Music achieved, and they're pretty impressive. Unlike The Sound of Music, we decided we'd give our fans what they clearly wanted and release another episode of our (just as favorite) analytics tips! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

A hallmark of the analytics community is the generosity with which ideas and wisdom are shared. One of the largest analytics conferences each year is Adobe Summit. One of the most followed Tims on the planet wrote a book called Tribe of Mentors: Short Life Advice from the Best in the World. Jen Yacenda and Eric Matisoff mixed all three of these truths together in preparation for an hour-long presentation chock full of excellent career advice. And then Adobe Summit went virtual, and their session got drastically shortened. On this episode, Jen joined the gang to talk through (some of) the 11 questions that they posed to 38 analysts, the responses they got, and how she and the hosts answered the questions themselves. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Have you heard the one about the four analysts who run a podcast who walked into a resort in Hungary? Well, now you can! Or, at least get a taste of that experience. Michael, Moe, Tim, and Josh headed to Superweek last month and, among other things, did a 12-hour audio livestream to try to give interested listeners a taste of the experience. On this episode, we're bringing you just over an hour (occasionally, we "power" right past the "hour" mark) of that livestream, centered around (but not limited to!) Michael's presentation on "the last mile of analytics," which is about the importance of self-awareness, communication, and interpersonal skills when it comes to putting analytics into action. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

"QA and patience and reviews by a peer. Data viz testing, hold no chart too dear. Don't be an a*e; automate 'til it stings. These are a few of our favorite things!" With apologies to Julie Andrews, on this episode, Moe, Tim, and Michael shared some of the tactical tips and techniques that they have found themselves putting to use on a regular basis in their analytics work. The resulting show: multiple tips, minimal disagreements, and moderate laughter. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

It's the end of the year, and we know it, and we feel fiiiiine. Or, maybe we have a little anxiety. But, for the fifth year in a row, we're wrapping up the year with a reflective episode: reflecting on changes in the analytics industry, the evolution of the podcast, and the interpersonal dynamics between Tim and Michael. From the state of diversity in the industry (and on the show), to the trends in analytics staffing and careers, to the growing impact of ethical and privacy considerations on the role of the analyst, it's an episode chock full of agreement, acrimony, and angst. And, it's an episode with a special "guest;" it's the first time that producer Josh Crowhurst is on mic doing something besides simply keeping our advertisers happy! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

READ ME!!! LISTEN!!! DO YOU KNOW WHY THIS IS IN ALL CAPS?! IS IT RAISING YOUR HEART RATE?! IS IT MAKING YOU A LITTLE IRRITATED?! IT MIGHT BE! IF IT IS, WE COULD MEASURE IT, AND MAYBE WE WOULD REALIZE THAT WE WERE INDUCING A SUBCONSCIOUS EMOTIONAL RESPONSE AND REALLY SHOULD TURN OFF THE CAPS LOCK! That's the topic of this episode: the brain. Specifically: neuroscience. Even more specifically: neurodesign and neuromarketing and the measurement and analytics therein. We're talking EEGs, eye tracking, predictive eye tracking, heart rate monitoring, and the like (and why it matters) with Diana Lucaci from True Impact. 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 noticed that 68.2% of the people who explain machine learning use a "this picture is a cat" example, and another 24.3% use "this picture is a dog?" Is there really a place for machine learning and the world of computer vision (or machine vision, which we have conclusively determined is a synonym) in the real world of digital analytics? The short answer is the go-to answer of every analyst: it depends. On this episode, we sat down with Ali Vanderveld, Director of Data Science at ShopRunner, to chat about some real world applications of computer vision, as well as the many facets and considerations therein! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

It's 1:00 AM, and you can't sleep. The paid search manager needs to know whether brand keywords can be turned off without impacting revenue. The product team needs the latest A/B test results analyzed before they can start on their next sprint. The display media intern urgently needs your help figuring out why the campaign tracking parameters he added for the campaign that launches in two days are breaking the site (you're pretty sure he's confusing "&" and "?" again). And the team running the site redesign needs to know YESTERDAY what fields they need to include in the new headless CMS to support analytics. You're pulled in a million directions, and every request is valid. How do you manage your world without losing your sanity? On this episode, analytics philosopher Astrid Illum from DFDS joins the gang to discuss those challenges. 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 thought it would be a great idea to have a drink or two, grab a microphone, and then air your grievances in a public forum? Well, we did! This episode of the show was recorded in front of a live audience (No laugh tracks! No canned applause!) at the Marketing Analytics Summit (MAS) in Las Vegas. Moe, Michael, and Tim used a "What Grinds Our Gears?" application to discuss a range of challenges and frustrations that analysts face. They (well, Moe and Tim, of course) disagreed on a few of them, but they occasionally even proposed some ways to address the challenges, too. To more effectively simulate the experience, we recommend pairing this episode with a nice Japanese whiskey, which is what the live audience did! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

What's in a job title? That which we call a senior data scientist by any other job title would model as predictively...  This, dear listener, is why the hosts of this podcast crunch data rather than dabble in iambic pentameter. With sincere apologies to William Shakespeare, we sat down with Maryam Jahanshahi to discuss job titles, job descriptions, and the research, experiments, and analysis that she has conducted as a research scientist at TapRecruit, specifically relating to data science and analytics roles. The discussion was intriguing and enlightening! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Remember that time you ran a lunch-and-learn at your company to show a handful of co-workers some Excel tips? What would have happened if you actually needed to fully train them on Excel, and there were approximately a gazillion users*? Or, have you ever watched a Google Analytics or Google Tag Manager training video? Or perused their documentation? How does Google actually think about educating a massive and diverse set of users on their platform? And, what can we learn from that when it comes to educating our in-house users on tool, processes, and concepts? In this episode, Justin Cutroni from Google joined the gang to discuss this very topic! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

A simple recipe for a delicious analytics platform: combine 3 cups of data schema with a pinch of JavaScript in a large pot of cloud storage. Bake in the deployment oven for a couple of months, and savory insights will emerge. Right? Why does this recipe have both 5-star and 1-star ratings?! On this episode, long-standing digital analytics maven June Dershewitz, Director of Analytics at Twitch, drops by the podcast's analytics kitchen to discuss the relative merits of building versus buying an analytics platform. Or, of course, doing something in between!

The episode was originally 3.5 hours long, but we edited out most of Michael's tangents into gaming geekdown, which brought the run-time down to a more normal length.

For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

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.

Do you know something that is really simple? Really Simple Syndication (aka, RSS). Did you know that RSS is the backbone of podcast delivery? Well, aren't you clever! What's NOT really simple is effectively measuring podcasts when a key underlying component is a glorified text file that tells an app how to download an audio file. Advertisers, publishers, and content producers the world over have been stuck with "downloads" as their key -- and pretty much only -- metric for years. That's like just counting "hits" on a website! But, NPR is leading an initiative to change all that through Remote Audio Data, or RAD. Stacey Goers, product manager for podcasts at National Public Radio, joins the gang on this episode to discuss that effort: how it works, how it's rolling out, and the myriad parallels podcast analytics has to website and mobile analytics! "For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

"Hey, Google! How do you measure yourself?" "I'm sorry. I can't answer that question. Would you like to listen to a podcast that can?" National Public Radio has long been on the forefront of the world of audio media. Why, you might even remember episode #046, where Steve Mulder from NPR made his first appearance on the show discussing the cans and cannots of podcast measurement! On this episode, Mulder returns to chat about how much more comfortable we have become when it comes to conversing with animated inanimate objects, as well as the current state of what data is available (and how) to publishers and brands who have ventured into this brave new world. "Alexa! Play the Digital Analytics Power Hour podcast!" For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

WHERE were you the first time you listened to this podcast? Did you feel like you were JOINing a SELECT GROUP BY doing so? Can you COUNT the times you've thought to yourself, "Wow. These guys are sometimes really unFILTERed?" On this episode, Pawel Kapuscinski from Analytics Pros (and the Burnley Football Club) sits down with the group to shout at them in all caps. Or, at least, to talk about SQL: where it fits in the analyst's toolbox, how it is a powerful and necessary complement to Python and R, and who's to blame for the existence of so many different flavors of the language. Give it a listen. That's an ORDER (BY?)! 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 had stakeholders complain that they're not getting the glorious insights they expect from your analytics program? Have you ever had to deliver the news that the specific data they're looking for isn't actually available with the current platforms you have implemented? Have you ever wondered if things might just be a whole lot easier if you threw your current platform out the window and started over with a new one? If you answered "yes" to any of these questions, then this might be just the episode for you. Adam "Omniman" Greco -- a co-worker at Analytics Demystified of the Kiss sister who is not a co-host of this podcast -- joined the gang to chat about the perils of unmaintained analytics tools, the unpleasant taste of stale business requirements, and the human-based factors that can contribute to keeping a tool that should be jettisoned or jettisoning a tool that, objectively, should really be kept! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Perspective is a good thing. We've all agonized about a misreported metric or an unsatisfying entry page analysis and had to remind ourselves that we're not exactly saving lives with our work. On this episode, though, the gang actually meanders into life-and-death territory by chatting about one of the uses of data outside of the world of digital marketing and websites and eCommerce: natural disaster preparation and response. Sherilyn Burris from Cascia Consulting joins Michael, Moe, and Tim to chat about her experiences in a variety of roles in just that area, how she uses data, how the data landscape has evolved over the past 15 years, and what she has learned about communicating data to politicians, to the media, and to the general public (which has some intriguing parallels to the communication of data in digital analytics!). For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

As the axiom goes: people don't leave companies; they leave their managers. And, good analysts are constantly being approached with new opportunities. So, what's the secret formula for hanging on to analytics talent? Assuming simply chaining them to their desks isn't an option, then the trick is keeping them happy and motivated. On this episode, the gang discusses their experiences and perspectives on the topic. Tim tried to quit the show just before recording, but he then discovered that Michael had chained him to his desk. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Tell me about a time you produced an amazing analysis. Please provide your response in the form of a Jupyter notebook that uses Python or R (or both!) to pull words from a corpus that contains all words in the OED stored in a BigQuery table. I mean, that's a fair question to ask, right? No? Well, what questions and techniques are effective for assessing an analyst's likelihood of succeeding in your organization? How should those techniques differ when looking for a technical analyst as opposed to a more business-oriented one? On this episode of the show -- recorded while our recording service clearly thought it was in a job interview that it needed to deliberately tank -- Simon Rumble from Snowflake Analytics joined the gang to share ideas on the topic. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.