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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.

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.

Sometimes, the best way to get alignment, generate new ideas, hash out different perspectives, or just effectively collaborate is to shift a gathering of peers from being a "meeting run by the organizer" to a "workshop run by a facilitator." Both meetings and workshops should have clear objectives, but workshops, when planned and run well, shift the mindset of the participants even before they arrive in the meeting room (which may make sense to have as a room at an off-site location). On this episode, we chat with master facilitator Jody Weir from THE ICONIC about her experiences, tips, and techniques for running an effective workshop. If you haven't committed to run one by the end of the show, then Michael failed in his role as podcast facilitator. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

These are interesting times in which we work, are they not? For many analysts, "remote work" is what they call "every weekday" or, for those who don't have things fully figured out, "every day that ends in 'Y.'" For other analysts, the current pandemic has forced them into being an unplanned — and not necessarily desired — full-time remote worker. Juggling kids, silencing pets, finding a horizontal work surface, and grappling with which pair of sweatpants to don are all the sorts of challenges (opportunities?!) that remote working can bring. On this show, we explore our experiences and thoughts and tips on the topic. Except for Tim, who thinks remote work is like in-office work: "Leave me alone, and just do your job!" For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Did you know that there were monks in the 1400s doing text-based sentiment analysis? Can you name the 2016 movie that starred Amy Adams as a linguist? Have you ever laid awake at night wondering if stopword removal is ever problematic? Is the best therapist you ever had named ELIZA? The common theme across all of these questions is the broad and deep topic of natural language processing (NLP), a topic we've been wanting to form and exchange words regarding for quite some time. Dr. Joe Sutherland, the Head of Data Science at Search Discovery, joined the discussion and converted many of his thoughts on the subject into semantic constructs that, ultimately, were digitized into audio files for your auditory consumption. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

For our special International Women's Day episode, we committed a type one error and peeked at our results, so we are releasing this winner three days early. As good analysts, we set out to optimise the podcast by swapping out Tim and Michael for two guests (it's rare for Tim to be in the control group, but he's an outlier either way). Unfortunately, it turns out we confused testing with personalisation, so we invited along a family member, Michele Kiss, as well as CRO expert Valerie Kroll, to talk about the evolution of the space from conversion rate optimisation (CRO) to experimentation. In Val's words, good experimentation programs are all about optimising to de-risk product feature roll-outs and marketing tactics, all the while learning about our users and prospects. Stay tuned for the three tips from our guests on how to set up the best version of an experimentation framework, as well as the stats on the show's gender breakdown since our start in 2015! 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.