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. This episode originally aired on May 8, 2018.

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. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page. This episode originally aired on December 6, 2016.

In recognition of International Women's Day, and because it's a really important topic, this is a very special episode. The two straight, white, cisgender male co-hosts of this podcast sat this episode out, while Moe took over the mic for an in-depth discussion with Alison Vorsatz from Fairygodboss and Aubrey Blanche from Atlassian about diversity (a term they both try to avoid) in the workplace. If this episode doesn't change your perspective and compel you to action, you are almost certainly not a human being. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page. This episode originally aired on March 7, 2019.

As analysts, we often have unique knowledge of the data, specialized responsibilities for data-related deliverables, and an expectation that we'll be at the ready to dive into high priority requests. What happens, then, when we're out of the office, be that for a planned vacation, for an unexpected illness, or for bringing a new human being into the world? And, what happens if it's that last one and you're also the most beloved co-host of the top-rated explicit analytics podcast? Tune in to this episode to find out, as we used Moe in a dual role of being both a co-host and a guest (again!) to explore the challenges (and opportunities!) of being out of the office. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

You know that sinking feeling: the automated report went out first thing Monday morning, and your Slack messages have been blowing up ever since because revenue flatlined on Saturday afternoon! You frantically start digging in (spilling your coffee in the process!) while you're torn between hoping that it's "just a data issue" (which would be good for the company but a black mark on the data team) and that it's a "real issue with the site" (not good for the business, but at least your report was accurate!). Okay. So, maybe you've never had that exact scenario, but we've all dealt with data breakages occurring in various unexpected nooks and crannies of our data ecosystem. It can be daunting to make a business case to invest in monitoring and observing all the various data pipes and tables to proactively identify data issues. But, as our data gets broader and deeper and more business-critical, can we afford not to? On this episode, we were joined by Barr Moses, co-founder and CEO of Monte Carlo to chat about practical strategies and frameworks for monitoring data and reducing data downtime! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

As we put the awfulness of 2020 in the rearview mirror, we thought it might be fun to look back to another bleak period: the 2007-2008 financial crisis! Why? Because Tim hasn't stopped talking about Subprime Attention Crisis — the Tim Hwang book that draws a parallel between the digital advertising ecosystem and the subprime lending crisis from a decade ago — we decided to all give it a read and then sit down for a discussion with the author. From the opacity brought on by the many moving parts to misaligned incentives to the fact that, well, even more than just the internet is built on digital advertising dollars, it was a fascinating discussion! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

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.

As unlikely as it seemed at many times throughout the year, 2020 actually IS finally drawing to a close, and that means it's time for our annual look back on the year: what happened with the podcast, what happened with the industry, and what happened as the entire world caught fire by way of wood-fuelled, climate-assisted combustion and by virus-induced fevers. In hindsight, there were faint hints of what the rest of the year would bring when our co-hosts and producer were together in person at Superweek in late January, but exactly how upside-down the world went still took them by surprise. One thing stayed constant, though: Tim and Moe continue to be able to talk past each other and violently argue about something about which they, basically, agree. On this episode: cover letters! 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.

Cookies are getting aggressively expired or blocked outright. Referring site information is getting stripped. Adoption of Brave as a browser is on the rise! Yet, marketers still need to quantify the impact of their investments. What is an analyst to do? Does the answer lie in server-side technical solutions? Well, it's not a bad idea to consider that. But, it's almost certainly not "the answer" to the multi-touch attribution question(s). Arguably, a better solution was one proposed by Jan Baptist van Helmont in 1648: randomized controlled trials. On this episode, data scientist Dr. Joe Sutherland returns to the show to talk about the ins and outs of problem formulation, experimental design, the cost of data, and, ultimately, causal inference. This is one of those rare shows where there actually IS a solution to a problem that vexes analysts and their stakeholders. The trick is really just getting the industry to understand and apply the approach! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

We didn't want to have a discussion about Netflix's The Social Dilemma, but, somehow, we just felt compelled to do so. It was almost like we had a generally unlikable character from a TV series about advertisers' attempts to manipulate consumer behavior in the 1950s and 1960s transplanted in triplicate into an AI that was optimizing Netflix's reach and engagement by getting us to talk about the movie. OR, it addresses a very real issue (a...dilemma, even?) in an approachable manner that, if you're like us, has alarmed your friends and relatives. It certainly seemed worth a discussion, so we had one about it! 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 someone who works remotely? Wait. What's that? Oh. It's 2020. I guess a better question would be: do you know any analysts who are NOT working remotely? But, that's not the question we ask on this episode. Some companies—and we're thinking agencies and consultancies here just to have a little focus—were corporate office-less from their founding, and those are the sorts of companies we interrogate on this episode. Laura Stude co-founded one such company—surefoot—so we sat down with her to explore the why, the how, and the opportunities and challenges therein. Employee-led remote dumpling-making lessons, anyone? Tune in to hear a lively discussion from many angles, many (most?) of which made Tim very uncomfortable. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

What is data culture? And, more importantly, what is the optimal ratio of agar and the ideal temperature of the corporate petri dish to make a data culture thrive? Moe, Michael, and Tim put their various experiences under the organizational microscope and examined various solutions in the name of (data) scientific discovery! If only organizations were as controllable as a chemistry lab! 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.

How does a Bayesian tell what time it is? She starts with an estimated time as her prior and then makes a video for TikTok. If you've ever made a joke like that and then realized your audience might need a little statistical education in order to appreciate how hilarious it is (or, perhaps, what the probability is that it's hilarious), then this episode is for you. The Chatistician (and the creator of the #statstiktok hashtag), Chelsea Parlett-Pelleriti, joined the show to talk about tactics for making statistics accessible, both to ourselves and to others! Humor and thoughtfulness were both normally distributed throughout the discussion. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Once every four years in the United States, there is this thing called a "presidential election." It's a pretty boring affair, in that there is so much harmony amongst the electorate, and the two main candidates are pretty indistinguishable when it comes to their world views, policy ideas, and temperaments. But, despite the blandness of the contest, digging in to how the professionals go about forecasting the outcome is an intriguing topic. It turns out that forecasting, be it of the political or the marketing variety, is chock full of considerations like data quality, the quantification of uncertainty, and even () the opportunity to run simulations! On this episode, we sat down with G. Elliott Morris, creator of The Crosstab newsletter and a member of the political forecasting team for The Economist, to chat about the ins and outs of predicting the future with a limited set of historical data and a boatload of uncertainty. 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 someone who always seems to have read the latest books and can cite concepts and ideas and authors and titles in any situation? Do you hate that person? Honestly, so do we. But that didn't stop us from recording an episode that, potentially, will grate on your nerves in such a way that you have to draw on your inner grit (Grit: The Power of Passion and Perseverance by Angela Duckworth) to get through it. But, with luck, there will be some good ideas that make it into your long-term memory (Brain Rules: 12 Principles for Surviving and Thriving at Work, Home, and School by John Medina), and it will be information delivered in a gender-neutral manner, unlike so much of the world (Invisible Women: Exposing Data Bias in a World Designed for Men by Caroline Criado-Perez). Give it a shot, though. It may help you become a better leader in your organization (Dare to Lead by Brené Brown).

Unfortunately, we lost some of this episode (even our recording platform was tired of hearing about books?). We know what we talked about then, even if we have no audio record, so we've included those books in the show notes as well. 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.

A wise man once said, "All forecasts basically assume that tomorrow is going to be very similar to today, just with an adjustment or two." That wise man was Gary Angel from Digital Mortar, and he said that on this very episode as we explored the ramifications for the analyst when the historical data is not at all a proxy for the near-term and medium-term future. What is the analyst to do when her training data has become as worthless as a good, firm handshake? If your prediction—based on listening to past episodes—is that Gary and our intrepid co-hosts might actually have some sharp ideas on the subject, well, give this show a listen and see how well you did! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Remember back when the global economy was booming and analysts were both in the sexiest job of the century and on the favorable side of the supply-demand curve for talent? Those were the days! On this episode, we sat down with Ollie Darmon from Canva to get his perspective, as an in-house recruiter, on what candidates can and should do to not only get in the door, but to actually close the deal and get hired. 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.

It sometimes seems like there must be a Moore's Law of marketing technology (or "martech," as the cool kids call it, and our site is on a .io domain, so we're definitely the cool kids) whereby the number of platforms available doubles every 6 to 8 weeks. And, every couple of months, it seems, a whole new category emerges. From CMS to DAM to CRM to TMS to DMP to DSP to CDP, it's an alphabet soup of TLAs that no one can make sense of PDQ! On this episode, Michael, Moe, and Tim sat down with the man who coined the name for one of those categories back in 2013: David Raab, the founder of the CDP Institute! It was a lively chat about the messy world of vendor overload and how to frame, assess, and successfully manage martech stacks. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

The promise of digital—and the steady shift of consumers' interactions with brands to that medium over the course of the past two decades—is that we can now see so much more of what our customers and prospects DO. But, how much does that tell us about who they really are, why they do what they do, and how they feel as they do it? What are they thinking and feeling as they cross between channels, task shift to and from interacting with your brand, and try to move their lives forward in whatever way that matters to them? Customer journey mapping tries to answer those questions: establishing different archetypes and mapping journeys through a combination of qualitative research and quantitative analysis. Would you like to journey further into the topic? Then give this episode a listen as we explore the subject with Dr. Monica Weiler from Stratos Innovation Group! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.