The Analytics Power Hour

Hey there, mister. That's a mighty nice multi-touch attribution model you're using there. It would be a shame to see it get mixed up with a media model. Or... would it? What happens if you think about media mix models as a tool that can be combined with experimentation to responsibly measure the incrementality of your marketing (while also still finding a crust of bread in the corner for so-called...

What does neuroscience have to do with the work of the analyst? It turns out that neuroplasticity is to the modern analyst what plastics were to Benjamin Braddock, and it all comes down to Hebb's Law. Or, put another way, successfully working with peers and stakeholders can take some focused effort, some feedback, and some practice, and that's what "coach" James Hayes joined the episode to discuss...

One of our KPIs for the show is to keep the Topic Repeat Rate (TRR) below 1.2%. From carefully monitoring our show dashboard, we had an actionable insight: we could finally revisit episode #002. Conveniently, the topic of that show was dashboards, which explains the self-referential stemwinder of a description of this episode. That show was "a long, long time ago. We can still remember… when the d...

What is a system without empathy? What is a show summary without an attempt to overly distill the discussion to the point of sounding like nonsense? On this episode, Hilary Parker (who you may know from the Not So Standard Deviations podcast or elsewhere) joined us to discuss what we can learn from the design process (as in: actual designers) when it comes to analytics and data science. Among othe...

Stop for a minute and think about the highest stakes campaign or test you've ever run. Were you nervous? Now, instead, imagine that you're on an aircraft carrier with a few thousand people on board whose safety you are responsible for, and your team is about to watch 40,000 tons of ordnance detonate (in an environmentally friendly way) right next to the ship... so you can collect data to verify th...

As analysts, it can be easy to get so focused on the data that we lose sight of the imperative that we answer meaningful questions (aka: validating relevant hypotheses). On this episode, we sat down with Wil Reynolds , co-founder and accidental lead generator for SEER Interactive , for a discussion that turned out to be about curiosity and the power of trying to prove yourself wrong (and being wil...

Have you ever worked in a large organization where the data team(s) are perfectly structured to deliver efficient, harmonious, and meaningful results to the business with 'nary a gap nor a redundancy? If you answered "yes," then we'll go ahead and report you to HR for being a LIAR! From high growth startups to staid enterprises, figuring out how to organize the data and data-adjacent teams is alwa...

Have you ever thought, "you know, it would be interesting to take my analytical knowledge and just totally run an organization based on what the data says?" Yeah. Us, either. That's terrifying! But, that's exactly what our guest on this episode did. Ben Lindbergh , along with his stathead-in-crime (aka, co-author) Sam Miller , took over the management of a minor league baseball team in 2015, and t...

Data is everywhere and it's simply not going away. Plenty of people do seem to ignore it to their peril, but if we are trying to make sense of the world, making good sense of data is absolutely critical. In business we call it data literacy, and, truthfully, it is a mandatory skill set for almost anyone. Data and understanding data might have a set of rules, and it seems like not everyone is commi...

We're baaaaaaack…! Shorter show name, a rebrand, some minor formatting and structural updates, but still "Moe Kiss with a couple of guys who listeners can't keep straight." On this episode, we talk for a little bit about what we've been doing while we were on hiatus and then dive into a topic that only Cassie Kozyrkov has dared to deeply explore before: the distinction between analysts, statistici...

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...

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. A...

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...

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 sh...

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...

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  ( @faderp ) from  The Wharton School  and Zodiac Metrics, about putting customer lifetime value (CLV) front and center when i...

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...

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...

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...

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 a...

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)...

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 t...

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...

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...

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...