The Analytics Power Hour

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.