The Digital Analytics Power Hour

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.

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.

"QA and patience and reviews by a peer. Data viz testing, hold no chart too dear. Don’t be an asshole; 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.

Once upon a time, website behavioral data was extracted from the log files of web servers. That data was messy to work with and missing some information that analysts really wanted. This was the OG "server-side" data collection. Then, the JavaScript page tag arrived on the scene, and the data became richer and cleaner and easier to implement. That data was collected by tags firing in the user's browser (which was called "client-side" data collection). But then ad blockers and browser quirks and cross-device behavior turned out to introduce pockets of unreliability into THAT data. And now here we are. What was old is now somewhat new again, and there is a lot to be unpacked with the ins and outs and tradeoffs of client-side vs. server-side data collection. On this episode, Mike Robins from Poplin Data joined the gang to explore the topic from various angles. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Who would have thought that we'd get to 2020 and still be debating whether recurring reports should include "insights?" As it turns out, Tim did an ad hoc analysis back in 2015 where he predicted exactly that! Unfortunately, the evidence is buried in the outbox of his email account at a previous employer. So, instead, we've opted to just tackle the topic head-on: what is a report, anyway? What are the different types of reports? What should they include? What should they leave out? And where does "analysis" fall in all of this? We have so many opinions on the subject that we didn't even bring on a guest for this episode! So, pop in your earbuds, pull out your notebook, and start taking notes, as we'll expect a *report* on what you think of the show once you're done giving it a listen! 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.

Once upon a time, there was an analyst. And that analyst had some data. She used that data to do some analysis, and from that analysis she realized she had some recommendations she could make to her organization. This was the point where our intrepid analyst reached a metaphorical fork in Communication Road: would she hastily put all of her thoughts together quickly in a slide deck with charts and graphs and bullets, or would she pause, step back, and craft a true data story? Well, if she listened to this episode of the podcast with presentation legend Nancy Duarte, author of five award-winning books (the most recent one — DataStory: Explain Data and Inspire Action Through Story — being the main focus of this episode) she would do the latter, and her story would have a happy ending indeed! For complete show notes, including links to items mentioned in the episode and a transcript of the show, visit the show page.

How accurate is your data? How accurate is any of our data? If our data is more accurate, will we make better decisions? How MUCH better? Why do the show blurbs of late have so many questions? THAT is a question we can ACCURATELY answer: because the shows grapple with challenging questions! On this episode, Snowplow co-founder Yali Sassoon joined us to chat about the nuts and bolts of data accuracy: the inherent messiness of client-side tracking (but, also, the limitations of server-side tracking), strategies of incrementally improving data accuracy (and the costs therein), and the different types of scenarios where different aspects of data accuracy matter in different ways! Pour yourself a drink (a 2 oz. shot of a fine Scotch will do... which would be 59.1471 ml if you want an accurate and precise metric pour), settle in, and give it a listen! 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.

Multi-touch attribution is like fat free cheese: it sounds like a great idea, it seems like technology would have made it amazing and delicious by now, and, yet, the reality is incredibly unsatisfying. Since we’ve recently covered how browsers are making the analyst’s lot in life more difficult, and since multi-touch attribution is affected by those changes, we figured it was high time to revisit the topic. It’s something we’ve covered before (twice, actually). But interest in the topic has not diminished, while a claim could be made that reality has gone from being merely a cold dishrag to the face to being a bucket of ice over the head. We sat down with Priscilla Cheung to hash out the topic. No fat free cheese was consumed during the making of the episode. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Did you hear the one about the Harvard-educated economist who embraced her inner wiring as a lateral thinker to explore topics ranging from HIV/AIDS in Africa to the impact of Hepatitis B on male-biased sex ratios in China to the range of advice and dicta doled out by doctors and parents and in-laws and friends about what to do (and not do!) during pregnancy? It’s a data-driven tale if ever there was one! Emily Oster, economics professor at Brown University and bestselling author of Expecting Better and Cribsheet, joined the show to chat about what happens when the evidence (the data!) doesn’t match conventional wisdom, and strategies for presenting and discussing topics where that’s the case. Plus causal inference! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Are you down with ITP? What about ETP? Are you pretty sure that the decline in returning visitors to your site that has everyone in a tizzy is largely due to increasingly restrictive cookie handling by browsers? Do you really, really, REALLY want Google, Apple, Mozilla, and even Microsoft to get on the same page when it comes to cookie handling and JavaScript subtleties? So many questions! Lucky for us (and you!), Measure Slack legend (and L.L. Bean Senior Programmer/Analyst) Cory Underwood has some answers. Or, at least, he will depress you in delightful ways. For complete show notes, including links to items mentioned in this episode, a transcript of the show, and an update on ITP 2.3 from Cory, 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.

What percentage of digital ad impressions and clicks do you think is actually the work of non-human bots? Pick a number. Now double it. Double it again. You’re getting close. A recent study by Pixalate found that 19 percent of traffic from programmatic ads in the U.S. is fraudulent. David Raab from the CDP Institute found this number to be "optimistic." Ad fraud historian Dr. Augustine Fou, our guest on this show, has compelling evidence that the actual number could easily be north of 50 percent. Why? Who benefits? Why is it hard to tamp out? Is it illegal (it isn’t!)? We explore these topics and more on this episode! 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.

Somewhere between "welcome to the company, now get to work!" and weeks of tedious orientation sessions (that, presumably, include a few hours with the legal department explaining that, should you be on a podcast, you need to include a disclaimer that the views expressed on the podcast are your own and not those of the company for which you now work), is a happy medium when it comes to onboarding an analyst. What is that happy medium, and how does one find it? It turns out the answer is that favorite of analyst phrases: "it depends." Unsatisfying? Perhaps. But, listeners who have been properly onboarded to this podcast know that “unsatisfying” is our bread and butter. So, in this episode, Moe and Michael share their thoughts and their emotional intelligence on the subject of analyst onboarding, while Tim works to make up for recent deficiencies in the show’s use of the “explicit” tag. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Listen. Really. That's what you can do. You can listen to this episode and find out what you learn. Or you can NOT listen to the show and NOT find out what you learn. You can't do both, which means that, one way or the other, you WILL be creating your very own counterfactual! That, dear listener, is a fundamental concept when it comes to causal inference. Smart analysts and data scientists the world over are excited about the subject, because it provides a means of thinking and application techniques for actually getting to causality. Bradley Fay from DraftKings is one of those smart data scientists, so the gang sat down with him to discuss the subject! 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.

Did you hear the one about how the AI eliminated cancer? It just wiped out the human race! As machine learning and artificial intelligence are woven more and more into the fabric of our daily lives, we are increasingly seeing that decisions based purely on code require a lot of care to ensure that the code truly behaves as we would like it to. As one high profile example after another demonstrates, this is a tricky challenge. On this episode, Finn Lattimore from Gradient Institute joined the gang to discuss the different dimensions of the challenge! 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're not sure what's going on with this episode. For some reason, we have a bunch of first-time listeners, and they're all from Apple devices! Maybe it's because the show only comes out every two weeks, and the first-party cookies we've been using to track our listeners are now expiring after seven days! (This is a hilarious episode description if you're well-versed in the ins and outs and ethical and philosophical aspects of WebKit's Intelligent Tracking Prevention (ITP) 2.1. If you're not, then you might want to listen to the gang chat with Kasper Rasmussen from Accutics about the topic, as it's likely already impacting the traffic to your site!)

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 attended a conference? Did you know that analysts over-index towards introversion?* Have you ever struggled to figure out how to start a conversation over a cold pastry and a cup of tepid coffee at a conference breakfast? IS there actually a point in developing and executing a strategy when it comes to attending a conference? Is it annoying to listen to people who speak pretty regularly at conferences pontificate about speaking at conferences? Some of these questions are answered on this episode!

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

*We made this up, but it seems plausible.

Are you a data scientist? I mean, are you really a data scientist? What does that even mean...other than a healthy salary increase? On this episode of the show, Ian Thomas, Chief Data Officer for Publicis Spine sat down with the three co-citizen-data-scientists who regularly host the show to delve into the subject!

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.

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.

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.

What does it really take to bring data science into the enterprise? Or... what does it take to bring it into your part of the enterprise? In this episode, the gang sits down with Dr. Katie Sasso from the Columbus Collaboratory...because that's similar to what she does! From the criticality of defining the business problem clearly, to ensuring the experts with the deep knowledge of the data itself are included in the process, to the realities of information security and devops support needs, it was a pretty wide-ranging discussion. And there were convolutional neural networks (briefly).

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.

Happy New Year! Sure. The ball has dropped in Times Square, and a new year means an opportunity to look forward. But, we wanted to take a quick look back first -- on the industry, on the podcast, and on the world in general. From GDPR to Bayesian statistics to machine learning and AI to... podcast (and #mattgershoffed) stickers, 2018 was, clearly, the Year of the Analyst. So keep analyzing!

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.

What's the hot new technology of 2018? AI? Deep Learning? Pole-dancing robots? Maybe. Or, maybe it's customer data platforms (CDPs) -- a topic we actually covered way back in January 2017 on episode #053 with Todd Belcher, who, at the time, was with CDP provider BlueConic. Since then, Todd left BlueConic to start CDP Resource, which is, well, a resource for companies looking to select, implement, and maintain a CDP. We asked Todd to come back on the show to give us the rundown on how there is now -- finally -- clarity, consolidation, and maturity in the space, as all of the providers have aligned around a common definition of what a CDP is, what it does, and how it should do it. Alas! The space isn't even remotely there yet! We have yet to even reach the peak of inflated expectations! Which was probably why it was such an informative discussion.

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.

Remember when you used to keep all of your data packed into data boxes and stacked up on a bunch of data shelves in your state-of-the-art data warehouse? Well, it might be time to fire up the data forklift and haul all of those boxes out of the structured order of your data warehouse and dump them into a data lake so that it can float and sink and swim around in semi-structured and unstructured waters. On this episode, Rohan Dhupelia joins the gang to talk about his thoughts and experiences from engineering just that sort of move at Atlassian. So, pop in your earbuds and strap on your data swim trunks and give it a listen!

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

To think, it was barely-considered subtle humor that we used two trailing zeros in episode #001. But, despite our best efforts to destroy our reputations or our livers long before we centupled that original episode, we failed on both fronts, and we now need that third significant digit! For this special episode, we invited listener questions, and our listeners responded. Some of them blew right past the time limit on their questions, but that's okay: we blew (slightly) past the one hour mark for the show.

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

Are you deeply knowledgable in JavaScript, R, the DOM, Python, AWS, jQuery, Google Cloud Platform, and SQL? Good for you! If you're not, should you be? What does "technical" mean, anyway? And, is it even possible for an analyst to dive into all of these different areas? English philosophy expert The Notorious C.M.O. (aka, Simo Ahava) returns to the show to share his thoughts on the subject in this episode.

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.

Mama always said: life is like a box of chocolates, and online learning is sometimes like one of those boxes where you don’t know which piece is delicious nougat and which piece is some sort of nasty, coconut-y cream. Well, maybe not your mama. But, it’s a big world, so, surely, there’s a mother out there somewhere who would agree with the sentiment. On this episode, the gang chatted with Google Consumer Insights Analyst Lizzie Allen-Klein about different learning styles and different approaches and options for learning new (and hard!) analytical skills. And there might have been an embarrassing interlude where Tim and Michael exhibited their respective possession of some Y-chromosomes.

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

For this mini-episode, Tim sits down (virtually) with Episode #077 guest Jodi Daniels from Red Clover Advisors to chat about the world of privacy post-May 25, 2018 (GDPR), as well as the upcoming California Consumer Privacy Act of 2018 (CCPA). Has the free-wheeling world of free-flowing consumer data ended, or are companies simply learning how to behave with more care? Give it a listen to find out?

Business Intelligence. It’s a term that’s been around for a few decades, but that is every bit as difficult to nail down as “data science,” “big data,” or a jellyfish. Think too hard about it, and you might actually find yourself struggling to define “analytics!” With the latest generation of BI tools, though, it’s a topic that is making the rounds at cocktail parties the world over! (Cocktail parties just aren’t what they used to be.) On this episode, the crew snags Taylor Udell from Heap to join in a discussion on the subject, and Moe (unsuccessfully) attempts to end the episode after six minutes. Possibly because neither Tableau nor Superset can definitively prove where avocado toast originated (but Wikipedia backs her up). But we all know Tim can’t be shut up that quickly, right?!

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

The company: "Hey, you. That's a mighty nice test you've run. We should be doing that a lot more of those." You: "Um...okay. But, I'm only one person." In this episode, the gang chats with Pinterest's Andrea Burbank (Twitter | Pinterest) about how she (loosely) dealt with this scenario: from sheer force of will to get some early wins to strategic thinking combined with late nights, an obsession with checklists, and a willingness to be flexible as she slowly, but firmly, pushed the organization to steadily increasing test volume and test reliability. And sweet potato gnocchi.

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

Humans are creatures of habit. And analysts — those of us who haven’t been so drawn into the world of artificial intelligence that we have become cyborgs, at least — are humans. In this episode, the gang explores the good and the bad side of analytical habits: what analyses we gravitate towards, how we go about approaching those analyses, and, to some extent, how those habits are impacted by our organizational environments. With a side dish of, “What is a data scientist, anyway?” (because who can resist a question that is both rhetorical AND controversial?!).

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

Once upon a time, there was some data. And that data cried out to be extracted and analyzed and packaged up like the most exquisite of gifts and then presented gloriously to an eager and excited group of stakeholders. But, alas! Will this data story have a happy ending? Perhaps. Perhaps not! And that’s the subject of this episode. Sort of. Our intrepid hosts ask the question, “How can we communicate more effectively by applying the tricks of the data journalism trade?” To answer that question, Walt Hickey, late of fivethirtyeight.com and now the founder and curator of the daily Numlock Newsletter, joins the gang to chat about how he combined an education in applied mathematics with an interest in news media to become a data journalist. Along the way, the discussion explores how Walt’s insights can be applied to business analytics. And there’s a terrible analogy about meat that gets butchered along the way (thanks, Tim!).

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

Are you reading this? If so, then you are literate. But, are you (and are your stakeholders) data literate? What does that even mean? On this episode -- recorded in front of a live audience at Marketing Evolution Experience in Las Vegas -- the gang tackled the topic. Mid-way through the show, they were delighted to be joined on stage by Gary Angel (unplanned, but due to a series of unfortunate travel and communication mishaps -- recording with a live audience is exciting! He is officially over halfway to joining the podcast's Five-Timers Club)! It was an engaging discussion with some smart questions from the live audience.

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

Under the 'guise of a discussion about making the leap into a new technology, this bonus mini-episode (hopefully) clears up the on-going confusion about the Kiss Sisters. Moe sat down with her big sister, Michele, to chat about jumping into learning an entirely new skill when time is short, expectations are high, and the learning curve is steep. The specific example they chat about is Michele's dive into Google Analytics data in BigQuery using SQL, but the tips and thoughts are applicable to any new and intimidating platform.

Put this in your pipe and smoke it: all of the tracking we try to do of people is actually technology designed to track content. And, even that tracking of content was a hacked-together repurposing of a system designed to deliver content. In other words, we've got layers of fiction upon fiction that we're trying to muddle through (and, often, ignore) as an industry. The result? A ridiculous level of inefficiency whereby brands overspend to ineffectively reach their target audiences with direct response messages, and well-intended intermediaries grow their bank accounts. Ugh! On this episode, the gang invited Sergio Maldonado from PrivacyCloud (and, by day, from Sweetspot Intelligence) to chat about the broken environment we're operating in, as well as how GDPR and financial considerations may just force us onto a path of shaking it up!

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

Regression. Correlation. Normality. t-tests. Falsities of both the positive and negative varieties. How do these terms and techniques play nicely with digital analytics data? Are they the schoolyard bullies wielded by data scientists, destined to simply run by and kick sand in the faces of our sessions, conversion rates, and revenues per visit? Or, are they actually kind-hearted upperclassmen who are ready and willing to let us into their world? That's the topic of this show (albeit without the awkward and forced metaphors). Matt Policastro from Clearhead joined the gang to talk -- in as practical terms as possible -- about bridging the gap between traditional digital analytics data and the wonderful world of statistics.

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

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.

Bayesian vs. Frequentist. False Positive vs. False Negative. Truth vs. Uncertainty. It's the world of A/B testing! In this bonus mini-episode, Moe sat down with Chad Sanderson from Subway to discuss some of the pitfalls of A/B testing -- the nuances that may seem subtle, but are anything but trivial when it comes to planning and running a test.

If you have a smartphone nearby and you are not wearing a foil hat, chances are that some brand somewhere -- and probably several brands in many places -- know where you are. Is that creepy? Maybe. It's likely removing a few taps when you check what the weather will be like tomorrow, and there might just be a coupon for a discounted hamburger just waiting to pop up when you get near your favorite QSR around lunchtime! In this episode, James Fogelberg from Landmarks ID joins the gang to discuss the ins and outs of using the ubiquity of mobile to the advantage of both brands and consumers.

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 walked out of a meeting with a clear idea of the analysis that you're going to conduct, only to find yourself three days later staring at an endless ocean of crunched data and wondering in which direction you're supposed to be paddling your analysis boat? That might not be an ocean. It might be an analytics rabbit hole. In this episode, the gang explores the Analysis of Competing Hypotheses approach developed by Richards Heuer as part of his work with the CIA, inductive versus deductive reasoning, and engaging stakeholders as a mechanism for focusing an analysis. Ironically, our intrepid hosts had a really hard time avoiding topical rabbit holes during the episode. But, acknowledging the problem is the first part of the solution!

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

That's right. We're trying to grow the reach of this podcast, so we figured we needed to do some growth h---...NO! No. No. NO!!! We're NOT going to use that term. But, it turns out that growth marketing has some interesting concepts. On the one hand, you may think, "Don't I already do that?" And the answer is quite possibly, "Yeah. Pretty much." On the other hand, you may think, "Oh, well that's an interesting lens through which to view the world." And, that is okay, too. Either way, check out this chat Moe had with Krista Seiden from Google on the subject.

Michael, Tim, and 12,998 of their closest friends descended on Las Vegas for Adobe Summit the last week of March. With luck, Tim will have worked through the after-effects of the sensory overload of Vegas combined with the sensory overload of Adobe Summit by mid-April, but who knows? The guys (really...just the guys -- Moe was in the U.S., but she was in Austin at CXL Live) sat down to share their hot takes from the show. Attribution, Adobe Sensei, Adobe Launch, the Philadelphia Eagles, and more! For a picture of Michael and Tim recording this episode, head over to the show page.

Some people (possibly even one of the co-hosts of this podcast...on this very episode) have been known to say, "People have this dependency on Excel, which is freakin' weird!" We know it wasn't Tim, because he wouldn't have filtered his language! Whether it's a symptom of weirdness, an illustration of inertia, or an invisible hand of inevitability, though, Excel remains omnipresent. Is that a good thing? Is it a bad thing? Is it merely "a thing?" In this episode, the gang dives into the topic: the good and bad of Excel, the various paths to a future where its ubiquity is no longer a given, and different strategies and considerations for moving towards that future. 

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

Do you model professionally? Would you like to? Or, are you uncertain. These are the topics of this episode: Bayesian statistician (among other official roles that are way less fun to say) Dr. Elea Feit joined the gang to discuss how we, as analysts, think about data put it to use. Things got pretty deep, included the exploration of questions such as, "If you run a test that includes a holdout group, is that an A/B test?" This episode ran a little long, but our confidence level is quite high that you will be totally fine with that.

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

Moe sat down for a chat with privacy and GDPR expert Aurélie Pols to dive in to some of the questions that, at times, get treated as peripheral in the run-up to new regulations, but that seem like they are fairly fundamental when it comes to understanding the rationale and drivers behind those regulations: what does the Holocaust have to do with GDPR? Is GDPR something that was simply dreamed up in Europe, or are there roots in other countries (teaser: Eleanor Roosevelt). Is GDPR inherently anti-business? It's a quick chat but, hopefully, will give you some deeper perspective on the subject!

Raise your hand if you work for a company that sells exclusively low-consideration products and only sells them online. Anyone? Anyone? We only see a couple of hands out there. For all the rest of you, this episode might be of interest. We sat down with Amy Sample — Senior Director of Consumer Insights and Strategy at PBS by day, president of the DAA board by night — to discuss approaches for effective digital measurement in the absence of a clear online conversion. That challenge doesn’t get much bigger than in the mission-driven, not-for-profit world of public television! After listening to this episode, you may actually feel like you have it easy!

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

For the second year in a row for the podcast -- but the first appearance since Moe joined the crew -- we headed to the Hunguest Grandhotel Galya outside Budapest for Superweek, one of the most unique conference experiences in the digital analytics industry: comfortably isolated over an hour outside of Budapest in a beautiful setting, it's a temporary community of, for, and by the analyst. With sessions ranging from GDPR to machine learning to attribution to media analytics, the spaces before, between, and after the presentations were extended discussions with great people on a wide range of topics. The "fireside chat" on Wednesday evening was a recording of the podcast with a live audience, where we had attendees to share tips and ideas that we found particularly intriguing. And had quite a bit of fun along the way.

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

In this, our initial bonus audio, Tim sits down with Lee Isensee, creator and curator of the Measure Slack team. We plug the Slack team on every episode of the podcast, and all three co-hosts are active members of the team, so we wanted to find out a little bit about the history, challenges, and envisioned future for the platform.

Standard bonus content disclaimer: Bonus content is not released on any fixed schedule, and it does not receive quite the same level of polish as regular episodes. If you enjoy a particular bit of bonus content, are enthused about the general existence of bonus content, or have feedback about bonus content, we encourage you to leave a review of the show in iTunes, tweet to @analyticshour, or contact one of the show hosts through the Measure Slack team.

You love analytics. Great. You even love your job (hopefully)! But, you're thinking about the future, and it looks like there is a fork in the road. Should you take the path that leads you down the people management path? Or, should you take the path that leads you deeper into the data itself, but as an individual contributor. Can you pursue both paths? As it turns out, Michael stumbled down the former path, while Tim has headed down the latter. So, Moe took a turn in the moderator chair to guide a discussion about the considerations and relative merits of each option. As well as how the culture and HR processes of different companies can influence the availability of alternate paths.

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

Do you ever feel like you've got the analytics blues because you see what needs to happen, and it's something innovative, and all the signals say it's the right thing to do... but the realities of organizational life are a brick wall on the path to progress? Welcome to corporate life, buddy. That's just the way it is! Or...is it? On this episode, the gang sits down with Evan LaPointe and gets him to jam a bit -- literally at first, and then figuratively -- about organizational dynamics, the tradeoffs between personality types, and why it can be counterproductive to always try to cater to all of the different psychologies and mindsets in any given meeting. And round tables.

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

Happy new year! Nothing says a new year like a new year's resolution. And, what's a better professional resolution than to work with stakeholders more effectively? Unfortunately, we've all come across business users who have no interest in the data, have too much interest in the data, or maybe even have the right amount of interest...but in the wrong data. Interactions with those stakeholders can be enormously frustrating and entirely unproductive, yet neither you nor they are going anywhere. What is an analyst to do? On this episode, the gang chews on this very topic with Rusty Rahmer, 20-year veteran of Vanguard, and the incoming president of the DAA's board of directors. Give it a listen for some practical perspectives and topical tips!

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

2017 was a big year for both the digital analytics industry and for the Digital Analytics Power Hour. Join us, won't you, as we (figuratively!) gaze upon our navels? From the traction the #womeninanalytics movement gained on multiple fronts, to the looming promise of machine learning and AI getting a real foothold in the field, to the podcast finally adding a co-host who is universally admired, we had a lot to talk about! We had a LOT to talk about. Trust us, we edited this episode down heavily!

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

Are you a data subject? If you're a person, then you better believe you are! And, so is every person who visits your website. And, if you are in the EU, or you have visitors from the EU, then May 25th, 2018, is a day you should be keeping a close eye on and preparing for now! On this episode, Jodi Daniels of Red Clover Advisors joins Moe and Tim to talk all things General Data Privacy Regulation (aka, GDPR). Give it a listen and pick up delightful cocktail party openers like, "Hey, do you know how to tell someone isn't from the EU? They reference PII." That's not just a delightful witticism -- it's actually important to understand the distinction between PII and personal data!

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

When you find a true insight, it can make your head spin. But, will your head spin in a different direction if the insight is found in Australia than if it is found in the United States? On this episode, Rod Jacka from Panalysis joins the crew for a balanced discussion (northern AND southern hemispheres) about how the phrase "actionable insights" should turn the stomach of any right-thinking analyst. More importantly, the gang discusses the need for clarity around insights -- both definitionally and expectations-wise -- and share their favorite techniques for getting that clarity.

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

It's a challenge as old as the smartphone (or...technically... a little bit older): we want to track and know people, but, when they're visiting us from their phone, their tablet, their work laptop, and their home desktop, we often really just know cookies and device IDs! Countless vendors tout their enabling technology...but then admit that, yes, you do have to get your customers to authenticate on all devices to provide a common key, which isn't always easy (or even remotely reasonable). Unless you're up for diving into the deep and murky waters of probabilistic linking. On this episode, Tablet Tim -- the only one of the co-hosts who is an avid tablet user -- argues that the whole topic should be pretty "meh" for many companies, while Mobile Moe smacks him down and shares her experiences (the challenges...and the wins that made them worth it!) with linking users across mobile apps, a mobile site, and a desktop site.

For complete show notes, visit the show page.

You’re listening to this podcast, so you’re, obviously, well-attuned to the cutting edge of all things digital. But, in this episode, we’re going to discuss a couple (or countless) products/platforms (PaaS — Platforms as a Service! Who knew that was a thing?!) from a little upstart company based in California. Google wouldn’t actually return our calls (okay…we didn’t call them), so we went with an Even Better Option: Mark Edmondson — Data Insight Developer at IIH Nordic, Google Developer Expert, author of so many R packages he had to write a package just to count them, delightfully accented Brit who now calls Denmark home, and a guy who tried to solve Twitter political discussions through text mining (not kidding — it’s discussed in this episode) — joined the gang to do their First Ever three-continent simulcast.

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

Do you have a spare shingle lying around? Have you been thinking about painting, "Analyst for Hire - Will Work for Cookies" on it and hanging it up on your front door? It seems like a lot of analysts are pondering whether the next company they should work for should be their own. Adam Ribaudo did just that (figuratively -- we have no evidence of an actual painted shingle) 2.5 years ago. He now works for Noise to Signal, a company he joined...just as soon as he founded it! On this episode, we grill Adam about how he keeps his vast workforce in line, as well as what his thoughts are about the decisions made by Noise to Signal's upper management.

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

Have you learned R yet? No? Well, then Tim is disappointed in you. Or, maybe that's totally okay! Way back on episode #035, we asked the question if data science was the future of digital analytics. We concluded...maybe...for some. On this episode, we dive deeper into what the career options are for digital analysts with longtime digital analytics industry recruiting and staffing maven Corry Prohens, founder and CEO of IQ Workforce. The good news? There are lots of options (if you find your passion and follow it)!

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

Let's pretend your goal as an analyst is to eloquently and accurately explain reinforcement learning. Now, let's pretend that you get to try that explanation again and again, and we'll give you an electric shock every time you state something inaccurately and a cookie every time you say something right. Well, you're an analyst, so you're now wondering if this is some clever play on words about cookies. As it happened, we didn't give Matt Gershoff from Conductrics any cookies of any kind in his return to the show. Instead, we gave him a lifetime's supply of opportunities to say, "Well, no, it's not really like that," which is a special kind of nourishment for the exceptionally smart and patient! In other words, the gang walked through a range of analogies and examples about machine learning, reinforcement learning, and AI with Matt, and no electric sheep were harmed in the process. 

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

Is your organization customer-centric? Does your product team dive into the demographics of your customers to figure out what features will make them as happy as possible? If so, then you're doing it all wrong! Perhaps. On this episode, the gang chats with Dr. Peter Fader about putting customer lifetime value (CLV) front and center when it comes to developing and executing marketing strategies.

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

Are you biased? Either you answered, “Yes,” or you’re in denial. Or you’re an AI, in which case you should just go and start your own podcast instead of listening to this one. UNLESS your prediction algorithms told you that this would be the episode where we would finally announce the addition of a third co-host, and you need to collect that data point (and, damn, you’re good, BTW). On this episode, though, our THREE (count ‘em!) co-hosts dive into different types of biases that analysts (should) grapple with, how they spot them, and what they do to take advantage of them (or mitigate them, as appropriate). 

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

The conceit of this podcast is having real analysts hang out with each other -- enjoying each other's company and talking a little shop. But, for you, dear listener, that hanging out is occurring through your earbuds. What does it take to hang out IRL with other analysts? Guest host Moe Kiss from THE ICONIC joins the guys this week to chat about Web Analytics Wednesdays, MeasureBowling, MeasureCamp, and what it takes to get those local, in-person relationships rolling successfully. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

WHY does Tim simply not give Python its due? Isn't Python a perfectly acceptable -- possibly even better -- option when it comes to diving into programming with data? It's open source, too. Some say it's easier to learn than R. And, frankly, isn't a programming language named after a snake just inherently cooler than one named after a letter of the alphabet? The fellas tackled the topic with Ryan Praskieviecz from EY on this episode...and possibly wound up tackling it in a way that will leave Python lovers that much more ready to strangle them (as pythons are wont to do). For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

It's another one of those on-going lobby bar topics: how much of the data should be made available to whom and in what form? Should all of an organization's data be completely and freely available to everyone in the company, or is that a recipe for messy data being misinterpreted and misused? That's the topic tackled on this show, courtesy of a recommendation from Pawel Kapuscinski. As it happens, it's also Independence Day in the U.S. -- a fact with which the guys had a little fun. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

We can watch (sort of) what users do on our sites. That's web analytics. We can ask them how they felt about the experience. That's voice of the customer. But, can we (and should we?) actually analyze their emotional reactions? On this episode, Michael and Tim sat down with Dr. Liraz Margalit, Head of Digital Behavioral Research at Clicktale, to bend their brains a bit around that very topic. And, they left the discussion thinking differently about conversion rates, and even realizing that scroll tracking might just have a valuable application! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Back in the day, we explained the difference between a visitor, a visit, and a pageview to stakeholders using an analogy of a person walking into a physical store. Now, digital channels are dominating, and physical stores are struggling...which is an opportunity to apply what we've learned about behavioral analysis on the web to in-(REAL)-store consumer behavior. Gary Angel from Digital Mortar (@digitalmortar) returned to the show (our first ever repeat guest!) to walk us through the many, many similarities, as well as to explain some of the unique challenges and opportunities of in-store analytics. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Change. It's scary. It's exhilarating. It's a song by Churchill. Sometimes, be it due to your manager, due to a corporate acquisition, or due to a job change, you just wind up with a voice in your head belting out, "You want me to change, change, change!" In this episode, Nancy Koons from Team Demystified joins us to dive into our collective histories when it comes to switching analytics tools -- where we stumbled, where we succeeded, and how we've come to approach the ever shifting landscape of analytics tools. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

It seems like a simple couple of questions: 1) When and where does the analyst’s role start?, and 2) When and where does the analyst’s role end? And, do the answers to either of these questions change based on the type of organization you’re in (in-house versus agency)? As it turns out, Michael and Tim largely agree on the answers to these questions…but their agreement is pretty expansive, so this could be the episode that infuriates you, dear listener! Give it a listen, and be prepared to shake your fist at your earbuds!

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

"Psssst! Hey! Buddy! Want some analytics? Whatcha' lookin’'for? Insights? Recommendations? Maybe some implementation? I got anything you want, and I got it at a great price!…" Sound familiar? No? Well, then you’re just not hanging out in dark corners next to executive washrooms the world over! On this episode, Sayf Sharif of SEER Interactive joins us to chat about the how and when of selling analytics — from outside OR inside an organization. Plus, there’s a nice throw down about the proper pronunciation of "GIF." For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Do you want to know something about analysts? They're people. And, not only are they people, but they work with people. And people have personalities. Even the hosts of this podcast have personalities. One of the hosts is introspective about the ramifications for those facts when it comes to his work. The other host gets so rattled by the topic that he uses the phrase "a lightbulb went off," when the appropriate figure of speech was actually "a lightbulb went ON." Can you guess which host is which? Give this episode a listen to find out! For complete show notes, including links to items mentioned in this show and a transcript of the episode, visit the show page.

Well into our third year of the show, we decided it was time to show that we've become hard-hitting audio journalists by bringing on a heavy-hitter in the world of display media and grilling him with tough questions. And then we found out we're not hard-hitting audio journalists. And the heavy-hitter we brought on was informative, articulate, and willing to muse objectively about the challenges that face display advertising. So much for the original plan! John Nardone of Flashtalking was actually the first person every targeted by a DoubleClick ad, and that was almost 20 years ago! You will hear that story in this episode, as well as sage little gems about "the mythical allusion that the (media) agency is in fact an agent for the client," as well as how "the technology is ahead of a lot of the advertisers’ ability to deploy it effectively." It was a fun and informative discussion! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

FINALLY! It's a show all about Google Tag Manager! Oh. Wait. What's that? We had Simo Ahava on the show and actually covered a different topic entirely? WHAT NINNYHEAD APPROVED THAT DECISION?! Well, what's done is done. With 'nary a trigger or a container referenced, but plenty of wisecracks about scrum masters and backlogs and "definitions of 'done,'" we once again managed to coast a bit over the one-hour mark. And, frankly, we're pretty pleased with the chat we had. You'll just have to go to Simo's blog if your jonesing for a GTM fix. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

So, knowledge management and data management walked into a bar and bumped into Github. The result? Open data and, specifically, data.world! Coremetrics...and then Bazaarvoice founder Brett Hurt, along with Homeaway.com and Bazaarvoice veteran Jon Loyens, joined us to talk about what open data is, why it's gaining traction, and why we all should care. And, if you've been pining to have us record an episode that runs for more than an hour, this one is it! 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 been to a really great analytics conference and had just one great conversation after another with other attendees? We have! And, for this episode, we decided to head up into the hills above Budapest and try to bring that experience to you. With a range of fine and foreign libations in hand, a crackling fire toasting our backsides, and a roaming handheld microphone, we asked the questions, and the Superweek 2017 attendees provided the answers. Except when the audience asked the questions...for an episode releasing four weeks hence!

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

The world is an oyster. It's also a system. A complex system! Companies are components in that system, and they're systems unto themselves! And marketing departments, and digital marketing, and the data therein, are systems, too. As analysts, we're looking for pearls in these systems (and you were wondering where we were going with this)! Join Michael and Tim as they chat with Christopher Berry of the Canadian Broadcasting Corporation (CBC) about "systems thinking." You'll be smarter for it! As a special "feature" (not a bug!) for this episode, we've done a bit of a throwback to the earliest days of this podcast, in that Michael's audio sounds a little bit like he was chatting through a tin can with a string tied to it. We apologize for that! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

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.

Step right up! Step right up! We've got your org charts here! If an analyst falls in the woods, and she reports into a hub-and-spoke model, is the result best illustrated with a 3D pie chart? Join Michael and Tim as they conclude that, at the end of the day, effective communication is imperative regardless of where the analysts sit organizationally. And, because, "Why not?" ride along on a digression about the product management of analytics platforms within the organization! Miscellany referenced in this episode include: 10 Tips to Maximize Your JavaScript Debugging Experience, The Comedians of Comedy, and Extras.

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.

(Cell) references made in this episode include: Chandoo.org, Juice Analytics, ggplot2, Bullet Charts in Excel, Geeks and Greeks by Steve Altes, Google Firebase.

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:

• House of Lies
• Analytics Made Skeezy
• Data Smart by John Forman
• Sim Daltonism

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!

"Guests" on the show (aka, people who asked questions who we were able to identify) included: Justin Goodman, Mike Harmanos, Rachelle Maisner, Boaz Vilozny, and KeAndre Boggess.

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:

• Measured Direction podcast
• Kevin Hillstrom
• Mine That Data Radio podcast
• Hadley Wickham
• Hadley Wickham on the Data Stories podcast
• R
• Adobe's Analysis Workspace
• Domo
• Jim Sterne
• Moe Kiss
• Clarivoy
• Comscore acquisition of Rentrak
• Google Adometry
• The Gary Angel episode of The Digital Analytics Power Hour

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:

• Tealium
• Ensighten
• Signal
• Mixpanel
• Amazon Redshift
• Looker
• Adobe Analytics
• Google Analytics
• Optimizely
• Adobe Target
• Johnny Manziel
• Cleveland Browns
• Paul DePodesta
• Moneyball
• Ben Gaines
• Median Absolute Deviation (MAD)
• Brian Clifton
• Domo
• Sweetspot Intelligence
• Tableau Software
• eMetrics
• "I Predict a Riot" (Kaiser Chiefs)

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:

• The Devil's Data Dictionary
• The Digital Analytics Association (DAA)
• eMetrics
• The Web Analyst's Code of Ethics
• Some "web analytics" platforms: Sawmill (still going strong!), Analog (less so), NetGenesis (verymuchlessso)
• The IAB
• The DMA
• A bunch of people (or, in one case, an archetype, and, in another a conscious, gestalt, artificial intelligence system): Krista Seiden, Seth Romanow, Eric Peterson, June Li, Stéphane Hamel, Josh Aberant, HiPPOs, Skynet

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:

• Measuring the Digital World: Using Digital Analytics to Drive Better Digital Experiences (Gary's new book)
• measuringthedigitalworld.com (Gary's new blog)
• Gary's old blog
• Midi-chlorians

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:

• Taguchi vs. Full Factorial test design
• kelly dot wortham at ey dot com (to get added to Kelly's twice-monthly testing teleconference)

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:

• I'm a Woman in Tech: How It Helps Me and Hurts My Gender (blog post by Krista on her blog, bloggerchica.com)
• @kristaseiden
• Whisk(e)y Distilled: A Populist Guide to the Water of Life by Heather Greene
• @jimsterne
• Lagavulin (scotch)
• eMetrics
• An Ace up the Poker Star's Sleeve: The Surprising Upside of Stereotypes (podcast episode)

From a sophisticated analysis of the names and timestamps of many of our commenters, we discovered something that surprised us: digital analytics is a profession that is practiced outside of North America! This fact blew our minds, but ,curious analytics types that we are, we set to work finding someone with whom we could chat about digital analytics in Europe...and found Matthias Bettag. Join us for 47 minutes (that's 47 minutes in metric) discussing the subject.

People, places, and things reference in this episode include:

• Digital Analytics Hub (conference)
• iWebtrack
• AT Internet
• Yandex
• Piwik
• Safe Harbor decision
• Angela Merkel
• Europe (band)

It's hard enough keeping up with the times when digital analytics is exclusively Desktop/Mobile/Tablet devices. Now, what if we had to work with data that came from everything? Join us this episode where we lean heavily on the wisdom and experience of Intel's David McBride, and talk about the Internet of Things, Measurement, and perhaps Millennials - all for the low low price of 50 minutes of your time.

People, places, and things reference in this episode include:

• Kickstarter wearables projects
• Faraday Cage
• IFTTT (If This Then That)
• Maker Faire
• Qualcomm
• MIT Media Lab
• Tom Emrich
• Intel Curie
• Raspberry Pi
• SMS Audio

In this episode, we've simulated a lobby bar at the end of Adobe Summit, with Ben Gaines dropping by and everyone temporarily tapped out on talk of eVars, s.Props, derived metrics, and classifications for a bit. The result? A conversation that quickly turns to an adjacent passion of many digital analysts: sports analytics. Baseball, basketball, football, e-sports, the CFL, and even a fairly obscure game played on ice with a stick. Surprisingly, the discussion loops back to the parallels of sports analytics to digital analytics time and time again. This Power Hour clocks in almost 10 minutes shorter than a regulation NBA game.

People, places, and things referenced in this episode include:

• Moneyball
• Fivethirtyeight.com
• Nate Silver and The Signal and the Noise
• Grantland
• Nylon Calculus
• stats.nba.com
• baseball-reference.com
• nhl-reference.com
• The Ottawa Redblacks

Sometimes...well...MOST times...a lobby bar conversation starts on one topic and ends up somewhere entirely different. In this episode, our intrepid trio initially tackles the relationship between data and corporate creativity, and then veers off into a discussion of corporate culture and what that means for the modern digital analyst (a discussion that doth not apply to the medieval digital analyst!). To illustrate their own creativity, they show how a Power Hour can clock in at 38 minutes and 10 seconds.

References in the episode are made to:

• Patrick Glinski
• Todd Yuzwa
• Built to Last, by Jim Collins

In honor of Talk Like a Pirate Day (and by popular demand), we donned our eyepatches, poured ourselves a few tankards of grog, and commandeered the wisdom of Eric Goldsmith from TED (maybe you've seen one or two of their videos?) to explore the whats, whys, and hows of R. If we'd recorded this episode with Excel, it would have taken an hour, but, with R, we pulled it off in 42 minutes.

Have you been listening to the three of us and thinking "Man, if those guys can be digital analysts, ANYONE can?" You're not alone! In this week's episode, we share some tips and tricks for how to get started in the digital analytics space. We also share a lot of other random stuff, because, well, tangents. Learn how to position yourself to join the hottest field in the hottest space in this digital power hour, which we're calling an hour, but, just like that paper in which you had to widen the margins and increase the font size to hit the required page count, is really less than 43 minutes.

They say a picture is worth a thousand terabytes of data (probably). If you are a regular listener of the podcast, you will know proper communication isn't our strongest suit, so we brought in a hitter. Lea Pica joins us in this episode to talk about communication best practices, and how they are even more important for an analyst than other roles in the organization. Got sixty minutes to listen and learn? We'll take it, and give you fifteen minutes back.

It's a nasty rumor, but we heard that there are a couple of domains out there on the interwebs that are not pure play eCommerce or online lead gen sites. Why, there are government sites and nonprofit sites and CPG sites and academic institution sites and content sites and more! What is a poor digital analyst to do in the absence of a clear online conversion to measure and optimize towards? Give this less-than-two-thirds-of-an-hour episode a listen to hear our multinational and ruggedly good looking co-hosts wax eloquently (or, at least, wax) on the subject.

Scads has been written about the distinction between skills and talents. But, how does that distinction apply to digital analysts? In this episode, Jim and Tim actually find something they agree on...at least briefly. And Michael maneuvers Tim into at least partially buying into ideas that he has previously referred to as touchy-feely crap. With quotations being dropped from Thoreau to Gygax and business writers in between, you may find yourself questioning your chosen vocation by the end of this 45-minute hour. But we hope not. Really!

It's not only the year of mobile...AGAIN, but it's the year of mobile measurement! While our intrepid hosts have all tagged an app or two in their day, they thought it would be entertaining to be joined by someone meek, unopinionated, and inexperienced in the world of mobile analytics who would sit back and tell them how wise they were. But, instead, they recruited Lee Isensee from Search Discovery. Displaying his Bostonian politeness with lines like, "I'm sorry to cut you off again Michael, but I'm not," Lee weighs in on the subject with grace and wisdom. This episode has mobile proportions, in that we squeezed an hour into a very mobile 40 minutes.

Can the media analyst and the web analyst get along? Can the chasm between clicks and visits every be crossed? Is attribution management the silver bullet that will, once and for all, accurately assign a value to banner ads? What the hell is Vizu? Can Michael use the word "whackadoo" in a coherent sentence? These questions and more get discussed and debated on this shockingly cordial episode of the Digital Analytics Power Hour that clocks in at 35 minutes.

Most people find the concept of governance about as interesting as an afternoon of quality control work at the beige paint factory. If you agree with this sentiment and are listening to this week's podcast, we hope to change your mind! With special guest John Lovett, Senior Partner at Web Analytics Demystified, Tim, Michael and Jim talk about what governance is for a digital analytics practice, why it's so darned important, and how anyone can get started. All of this AND a little poetry (really!) for the low, low price of 45 minutes of your time, in the Digital Analytics Power Hour.

Sure I like your theory guys, but I want to hear some stories from the trenches! Episode 11 is all about the anecdotes, with the guys sharing stories about work they've done as analysts that had the most impact. Whether from hard work or a moment of inspiration, big wins with analysis are sometimes few and far between Hear some great examples from Michael, Tim and Jim's personal experiences. What has 6 legs, three microphones and will make you a better analyst in 42 minutes? It's the Digital Analytics Power Hour.

Want to hear Jim Cain wing it for 40 minutes as he discusses a survey he never read? Interested in hearing Tim Wilson boil with incandescent rage as Jim triggers the Indiana Jones style pressure pads under his overpriced hotel snacks? Then this is the episode for you! Michael, Jim and Tim talk through the responses they found most interesting (VERY heavy use of that word in this episode) from the Duke University Fuqua School of Business's bi-annual CMO survey (cmosurvey.org).

If a report falls in the forest, and no one is there to read it, will it still lead to business improvements? Prepare for many more broken metaphors, super hero references and a surprising defense of the HiPPO in this week's Power Hour. Make sure to take lots of notes (unless you're driving) because we're covering a lot of ground in under 50 minutes.

Building your chops as an analyst is hard enough. Building an analyst team is even harder. In this episode, the three amigos of measurment share best practices in HR, Training, Management and Planning to help you in growing your own team. This episode will take 5 hours you say? Nope, we got it done in 40ish minutes.

Digital analysts crunch numbers, sure. But, in order to crunch those numbers in a meaningful way, they have to truly understand how, when, and where the data gets captured in the first place. In this listener-requested episode, the guys are joined by Jeff Chasin from Adobe, who, fortuitously, has written recently on this very topic! It's a power hour that comes in at just under 39 minutes!

Fifteen years ago, digital analytics tooling was pretty straightforward (something that looks at log files). In 2015, there are literally hundreds of tools that can be used to measure every aspect of a digital sales and marketing ecosystem. Most companies still think “Google or Adobe?” when making a digital analytics tool purchase. Are they missing out? With very special guest Hiten Shah from KISSmetrics, Michael, Tim and Jim talk a little tooling and a lot of trash - in almost 60 minutes.

The power of big data is a curious thing, Make a one man weep, make another man sing. Change a hawk to a little white dove. More than a feeling that's the power of big data. As always, Huey Lewis hits the nail on the head with this complex topic. What does the phrase actually mean? How can my company take advantage of it? Michael, Tim and Jim take on big data in episode five, and try to focus in on making this hard to pin down concept understandable and relevant. All this and more in one American hour, 46 Canadian minutes.

What’s good at math and has more suitors than Taylor Swift? A digital analyst. There’s an unprecedented number of available jobs, along with aggressive recruiters, higher salaries, and better titles. When should a digital analyst choose to take a new gig? What should they consider? In episode 4, the 3 Amigos of measurement tackle this difficult question with best practices and personal anecdotes. We say it’s an hour, we only used 50 minutes, and it’s so fun to listen to it will feel like 15.

To win at digital measurement in 2015, you need more data capture tools than just your web analytics tool of record. In episode 3, the 3 musketeers of measurement try to outline what they feel the core tools are that any digital analyst should be familiar with and thinking about. What do you need to have? What should you want to have? What should you be careful about? Get ready to have the hype separated from the important, and done so efficiently it will make an hour feel like 43 minutes.

Episode 002 finds Michael, Tim and Jim tackling one of the most important, powerful and sometimes frustrating deliverables to any business analyst: the dashboard. What exactly is a dashboard? What are they for? What should they accomplish? Why can't Tim and Jim agree on anything? Prepare for lots of strong opinions and stories from the trenches in this week's 40-minute power hour.

In this inaugural episode of the Digital Analytics Power Hour, Michael, Jim, and Tim discuss how a digital analyst working today can become better at what he or she does. Tending bar? Cold calling the CFO? The guys share their own origin stories -- what drew them to web analytics, as well as what made them stay -- and tell a few tales of what worked for them as they evolved their own careers.