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0:00:05.8 Announcer: Welcome to the Analytics Power Hour. Analytics topics covered conversationally and sometimes with explicit language.

0:00:14.0 Michael Helbling: Hi Val.

0:00:16.7 Val Kroll: Hey Michael.

0:00:17.5 MH: You know, this episode was something different and a little special. For episode 256, we went to Chicago to participate in MeasureCamp. Val, Chicago is your hometown, and you were very involved in the planning and execution of the event. Besides great pizza, what were we all doing in Chicago?

0:00:38.4 VK: I was so excited for all of us co-hosts to come together for the first time in my hometown where we did enjoy some great Chicago pizza. And we were able to participate in the Day of Chicago MeasureCamp, our inaugural Chicago MeasureCamp, and we were so excited. We had over 200 people come together. It really felt like a homecoming/a great meeting of a lot of analytics professionals in Chicago that I had never gotten to meet before. But the Analytics Power Hour had a special role in the day. So for each of the sessions at MeasureCamp and on the cards on the board, we had a question that we posed to our listeners, and we asked them to come to our recording room with us to hop on the mic with The Analytics Power Hour to share their responses to various questions about our industry and the way we work and think about our role. And we got to chat a little bit, which was super fun ’cause we don’t always get a chance to chat with our listeners, especially on the mic.

0:01:38.8 MH: Yeah. And some of the answers we got back were so great. And then at the end of the day, we got to do a quick get together with everyone to recap the day. And so without further ado, here is Episode 256.

0:01:53.7 MH: All right. Thanks for hopping on the mic. So what was one of your most embarrassing hashtag analytics fails in your career, and what did you learn from it? So maybe introduce yourself and then answer the question.

0:02:04.4 Pauline Gaynesbloom: Absolutely. Thanks so much for having me. So just as an introduction, my name is Pauline Gaynesbloom, I’m a Senior Manager of Analytics at Publicis Sapient, and I would say my most embarrassing fail was very early on in my career where I got pulled in to help with some BD work, and everyone else was out on vacation, literally my manager, all the senior analysts were out and they were like, who is left in the office to help us with this data question, and what they needed was a forecast. So I had to figure out how to forecast something. I don’t know, so I Googled it and came up with what I could, and at the end of the pitch or whatever it was, they kind of asked me to retrace my steps and explain my process.

0:02:51.5 MH: Oh no.

0:02:53.2 PG: Which is where I found I had hard-coded some numbers, no idea why I hard-coded them, but they were supposed to be dynamic, and I realized that the forecast was mainly junk, but they still used it and I don’t think they won the pitch, but it was a good learning experience for me to be able explain my process…

0:03:18.5 VK: There you go.

0:03:20.0 PG: And to double check for those little things like having a space in the wrong place or having hard-coded numbers where they’re supposed to be dynamic.

0:03:27.9 VK: Well. Hopefully, that was a learning for the sales team too, to make sure that there was someone available to do that before going on a vacation.

0:03:31.0 PG: And not the junior analyst on the team.

0:03:33.1 MH: Yeah. It does feel like there’s a tendency for BD to sometimes be like, oh, and Anything, sure, you can drop in to do anything.

0:03:40.6 PG: Yeah, we just need someone that looks ready.

0:03:42.0 MH: Just to fill the gap, yeah. I was gonna ask whether they won the pitch. I was gonna ask if you remember to who the pitch was too, ’cause I’m now cycling through a few where I got dropped in way over my head thinking yep, did not win. Did not win.

0:03:55.6 PG: Did not win that.

0:03:58.7 MH: Yeah, did not win that. Wow.

0:03:58.8 Merrit Aho: Okay, my name is Merritt Aho. I am a digital analyst at Breeze Airways. And I have almost too many to name, but we’ll start with the one that happened at MeasureCamp. So this was the first MeasureCamp in Austin, Texas. And shortly before it, I had started getting into simulation work with data, that was just a really good way, by the way, for anyone to learn about how test statistics work is by simulating actual data. Anyways, I was doing some specific research on false positives and I was uncovering some really interesting stuff to me, and so I decided to do a MeasureCamp session, this is my first MeasureCamp too. And I presented in front of a good audience and no one questioned anything, Matt Gershoff was even in there. No one said anything. I’m sure he was stewing, but long story short, it was wrong. What I presented was, it was like, damn wrong.

0:04:52.3 MH: So you’re here in Chicago to basically, this is your make amend this is your correction, likes your correction.

0:04:58.2 MA: Yeah, so I presented the wrong data, no one said, Matt didn’t even say it. Matt was probably being polite, he was probably restraining himself, but I didn’t realize it until I was going to publish a blog post that was based on the stuff that I presented and someone else corrected my work or pointed out a flaw, said that their simulations were different, and I went back and checked the math and yep.

0:05:21.7 MH: But can I ask you about, if I recall ’cause you’re kind of the person who… Not just to me, but to many people kind of… ‘Cause you use simulations when you’re trying to figure out understanding sequential testing, ’cause that now I see it coming up more and more often. Is that stuff still posted in various places somewhere.

0:05:42.4 MA: Probably. Yeah.

0:05:42.5 MH: I would challenge, yeah.

0:05:44.0 MA: I don’t know where, that one might… Yeah. I don’t know what… Still somewhere, maybe.

0:05:46.4 MH: Okay. I can’t remember exactly where you presented that they’ve been on…

0:05:51.9 MA: But I correct it before I went to publish.

0:05:53.7 MH: Okay, that’s good.

0:05:53.7 MA: And the lesson learned there is, have other people reviewed your work very useful, even though it sometimes it’s hard to expose yourself like that, especially there are some very loud critics out there, but it’s pretty…

[overlapping conversation]

0:06:10.4 VK: That’s a good one.

0:06:11.6 MH: That’s interesting. We’ve had another question that was a little bit of a… Another response that was kind of a get a.

0:06:19.3 VK: Second set of eyes.

0:06:19.4 MH: Get a second set of eyes on it. Is good I like it.

[overlapping conversation]

0:06:24.4 MH: Yeah. You’re looking for the blessing. Like that’s great, and more often than not they’re gonna be Well, that might have a problem. Small or large. So.

0:06:31.5 MA: What is it? Twyman’s law, where if it’s interesting, it’s probably wrong?

0:06:37.0 MH: I don’t know. I mean, I felt that. Twyman, Twyman? Okay.

0:06:41.8 Josh Silverbauer: Awesome. All right. Well, hello. I’m Josh Silverbauer. I’m the head of analytics at From the Future and just like musical analytics songwriter, dude, too. Yeah, like I’m thinking about the long history of failure in my career, and the one that just like I want to talk about today or came in and popped into my head is I was working on this very large, like one of the biggest museums, I’m not going to say the name of the museum, but one of the biggest museums was like one of my first clients in the United States.

0:07:13.2 JS: And I was in charge of basically updating their universal analytics. And I was relatively new to… Like I had learnt a lot about Tag Manager, but this was really my first client as my own agency. And I happenstanced into it through connections there. And I like built a whole strategy, a whole plan, built everything myself in Tag Manager. And then for two weeks, and I didn’t realize this, I said everything was good. It was good to go. I showed them all the tags that I had built, etcetera. For about two weeks, I had forgotten to publish in Tag.

0:07:56.8 MH: Oh, no.

0:07:57.8 JS: And so basically, I had… And I forget exactly how this occurred, but they had data, and then all of a sudden, it was a new Tag Manager that they put on there, right? Because I was like, yeah, to make sure that there’s consistency, we put the new Tag Manager on there, and it’ll have all the tags in there.

0:08:20.5 VK: Yeah, sure Josh we trust you.

0:08:20.5 JS: All you have to do is…

0:08:21.7 VK: We trust you.

0:08:22.4 JS: Exactly, they’re like, oh, yeah yeah, of course. We don’t know anything about analytics, so just do whatever you tell us. And so I said, switch out the Tag Managers, and everything will just start humming along, right? And I just didn’t publish the tags, right? And so for two weeks, their entire data dropped off, and they just had no data during that period of time. And then, but the funny thing about it was, I found this out. They didn’t find this out. So…

0:08:52.4 MH: That’s a little troubling.

0:08:53.6 VK: That looks great, Josh.

0:08:54.0 JS: Yeah I know, right? It’s like, they’re like, everything’s great now, I guess. But yeah, it’s just like, for me, it was a lesson in just QA-ing, because this is my brain in general, is like, I’m so excited about the project, and I wanna do the project, and everything about the project is fun and exciting up until QA, and then I’m like, oh it’s done, we’re good, it’s just that.

0:09:21.8 VK: All done.

0:09:24.1 JS: Yeah. And now I am definitely the first thing that I do at the end of a project, is just go into real time and just make sure it’s done. So when people are making fun of real time, and so many people are like, real time, la, la, la, it’s like…

0:09:36.0 MH: As a QA.

0:09:39.4 JS: It’s good for QA, as a QA, it’s very important. So that was definitely a humbling lesson in don’t get too cocky about the project, make sure that you’re really paying attention to the outcome and the end, but yeah.

0:09:57.0 VK: That’s a good one.

0:09:57.2 MH: That’s a good one. I am gonna throw, we got just a little bit left, so I would love for you to do a quick little background and plug for Universal Sunset.

0:10:06.3 JS: Yeah, okay, yeah, absolutely.

0:10:08.9 MH: Just for funsies.

0:10:10.7 JS: So those of you who know me, you know that I have created, probably the industry’s only rock opera, I would say.

0:10:21.1 MH: You’re coming on the industry’s only explicit analytics podcast to talk about it. It’s all about defining the size of the pond.

0:10:26.7 JS: Yeah.

0:10:27.2 VK: Johnny Power Awards.

0:10:27.9 MH: Yeah.

0:10:28.6 JS: It’s called User Journey Volume 1, and actually User Journey Volume 2 is 90% done. And we have, basically, just real quick while I have the time, we have a bunch of different veterans in the analytics industry who join us on this adventure about an alien named Cookie, who has to go find a new universe after his universe was Sunset. So the first album revolves around that. The second album revolves around him exploring new universes.

0:10:58.3 VK: Amazing.

0:10:58.7 MH: Which would have been awesome if you said that it was actually done, and then we actually found out in real time that you’d actually forgotten to publish.

0:11:03.0 JS: Oh, yeah, I forgot to press the…

0:11:05.6 MH: Yeah, there’s like nobody’s, I’m getting no feedback. It’s like, well, you listened to it then.

0:11:09.5 JS: I checked real time to know if it’s happening.

0:11:11.8 MH: Awesome. Well, thanks.

0:11:13.4 VK: Thanks for joining us, Josh.

0:11:14.3 MH: The twofer, yeah.

0:11:15.1 JS: Yeah.

0:11:15.6 VK: Good one.

0:11:16.5 MH: So Val, what’s one of your biggest analytics fails?

0:11:22.4 MH: It’s time to step away from the show for a quick word about Piwik PRO. Tim, tell us about it.

0:11:28.5 Tim Wilson: Well, Piwik PRO has really exploded in popularity and keeps adding new functionality.

0:11:33.8 MH: They sure have. They’ve got an easy to use interface, a full set of features with capabilities like custom reports, enhanced e-commerce tracking, and a customer data platform.

0:11:44.4 TW: We love running Piwik PROs free plan on the podcast website, but they also have a paid plan that adds scale and some additional features.

0:11:51.9 MH: Yeah, head over to piwik.pro and check them out for yourself. You can get started with their free plan. That’s piwik.pro. And now let’s get back to the show.

0:12:04.6 VK: Alright. Well, this pain is still real, even though it happened like 12 years ago. But when I was first getting into digital analytics, I wasn’t as business-focused or business-centric with what I was doing because I was so wrapped up in, like, are the tags perfect? Are we collecting all the data? Like, is the e-commerce store collecting all the events?

0:12:20.0 MH: Did we push the tags to production?

0:12:22.4 VK: Did we push the tags to production? Exactly. So I didn’t have the appropriate focus on what mattered most, but I would like go into my little cave and produce analyses of things that I found to be interesting. And there was one occasion where there was a lot of competition over who was going to get the homepage here on real estate or the first position for the menu on our corporate website. And one of the things that I noticed is the homepage wasn’t even in the top 10 pages for entries to the website. And so I was like, you know what I’ll do? I’ll call it a front door analysis. And these are the top 10 pages and here’s what people do when they arrive. And I thought this was like the hottest shit to hit, I don’t even know, the street. And so I thought I was going to like produce this and like shop it around to each of the content owners so that they could think about like, oh, imagine your experience is the entry point. What would you do differently about the way that this is constructed or thinking about the next experience?

0:13:14.6 MH: This is wild. This sounds so good so far so… I’m waiting for the turn.

0:13:20.6 VK: So I poured an exorbitant amount of time into this analysis and my team was really excited about it too. And so we go into these meetings thinking that people are going to be like high-fiving us, doing like cartwheels down the hallway, like, oh, thank you so much. What did we do before you shared this analysis? No one cared. No one cared. There was one meeting where I knew my stakeholder really liked printed materials. This was an association and it was about 12 years ago. So I printed the deck for everyone in the room and there was someone who actually said, when this meeting is over, can we just destroy all these and pretend we didn’t have this conversation ’cause I don’t plan on updating this content for the next five years. And I was like crushed, crushed, absolutely crushed.

0:14:03.6 VK: I was like, why isn’t everyone just like banging down our door for like, ’cause again, the beginning stages of our program, we were still trying to ramp up interest in how we use data to make better decisions. But I wasn’t being a really good partner in that scenario. And so thankfully I started going to some conferences and realized, oh, maybe if I recenter my priorities around what these people care about versus what I find interesting in my little cave when I come into work on Saturday morning when there’s no air conditioning, maybe then people will care. And so I started to make that pivot and just like never looked back because making the priorities of the business, my data work is what really opened the door to really enjoying my role in analytics.

0:14:41.8 MH: It does seem like, ’cause the idea doesn’t seem bad. So it seems like there’s a… Would have been, if you’d actually asked to gauge interest to see if somebody perked up and they might have if they weren’t already looking at the results so…

0:14:58.7 VK: The thing is that only one person really cared about the competition. Like everyone just felt like, oh, mine’s the most important. So like, I don’t really care anyways. Like I don’t… It’s no different to me if someone like thinks their content is more important because of course it’s mine. And so no one, I was trying to like use it as a way to like diffuse the number of meetings I was dragged into about who was going to get the homepage hero from Tuesday to Thursday ’cause we had to like rotate them. This is ridiculous. But yeah, so everyone just felt like, oh, I’ll just make sure that my boss has the squeakiest wheel and then I don’t have to worry about it.

0:15:28.4 MH: That’s awesome.

0:15:30.9 VK: But anyways, that was a big pivotal moment for me and quite a huge fail.

0:15:36.5 MH: But it’s a learning you’ve taken with you ever since.

0:15:37.4 VK: I sure have.

0:15:38.6 MH: Alright. Good one.

0:15:40.6 VK: Well, a lot of those are some good stories and reminders to make sure you are QA-ing your work and getting a second set of eyes, whether it’s tagging or even a model that you’re building.

0:15:50.8 MH: Here’s our next question. What’s a commonly held belief within analytics that you passionately disagree with?

0:16:00.0 Jessie Lin: My name is Jessie and I work for Wilson, their analytics manager on the e-com team. So I would have to say it’s persona development based on demographics.

0:16:11.4 MH: Oh, I love it. Okay. Yes. Yes.

0:16:13.9 JL: Yeah. I feel like now, like whether you’re doing analytics or you’re a marketer, like it’s like, okay, we need to develop this persona. Who are they? Female, male, age group we’ve got to know them so we know how to communicate with them. I feel that’s what everybody’s trying to do. But for me, I feel like it’s good to know the demographic you can refine your message, whatever. But then sometimes just based on my experience, there’s not a lot of like actionable things you can do. So for me, I think in addition to demographic for persona, well, “development”, it’s more important to look at kind of their purchasing behavior. So for, let’s say like, so my company, we’re trying to figure out who are the people buying pickleball, right? Because everybody’s playing pickleball right now. And then, so we’re trying to see like, okay, do they purchase like tennis before and then buy pickleball or, ’cause we’re trying to figure out if there’s any opportunity to cross sell them.

0:17:11.9 JL: ‘Cause in my company, we have like different line, like sportswear, tennis, and then we often see like cross out between those two, but not so much like other sports. Like for some people who buy baseball glove, just buy baseball glove. There’s not like really like transcending the sportswear. But then what we do from analyzing those like purchasing behavior, people who bought pickleball, we see that it’s really transcends like different sports, like people buying basketball actually also buy pickleball and stuff. So that’s kind of like, tell us like, if we want to talk to them, maybe, we can like cross promote like sportswear and then kind of see like, okay, do they buy sportswear? What’s the next thing they bought? Or like within pickleball, like category, what’s the first thing that drives like new purchases? Is it like paddle or footwear? It’s actually footwear. Like people buy footwear first. So I think it’s good to know the demographic.

0:18:07.1 JL: Like, of course, it’s gear to wear younger and also like older, and then like a little bit more like female then male. But then in addition to that, you also have to layer in a lot of like the purchasing behavior, especially like what they purchased together with like, what’s the next best thing to talk to them and then we can kind of like orchestrate a journey and so on and so forth. So I would have to say like, the thing that I disagree the most is to develop persona solely based on demographic. I don’t know it’s a really fancy wear, people want to do with persona, but you know, there’s so many things to like consider. Yeah.

0:18:45.3 VK: Absolutely. That’s a great one.

0:18:45.7 MH: I love that.

0:18:45.9 JL: Really? Thank you. Oh my god. I’m like so nervous ’cause I was like I love the podcast. I’ve never been in a podcast before.

0:18:50.7 MH: No, for years, Especially for just that example you provided. I was like, behavioral personas are so much more powerful than demographic personas. And so it’s sort of like, oh, don’t go looking at zip codes. Go look at other behaviors that are like this one. Like, so for example, like people who bought pickleball and basketball. Well.

0:19:10.1 VK: Who are these people?

0:19:10.6 JL: Right.

0:19:10.6 MH: You wouldn’t pick that up from whether they are soccer moms or drove this minivan or whatever the demographic information you have.

0:19:20.2 JL: Exactly. Yeah. No, for sure. Yeah. So it’s like interesting to me. Yeah. Especially looking at those like purchasing behavior.

0:19:26.1 MH: That’s Awesome. Any thoughts on that Julie?

0:19:29.4 Julie Hoyer: Have you gotten a lot of pushback on that opinion at work?

0:19:32.3 JL: Yeah, for sure. Especially like, talking to the, like our partner, like different business unit, ’cause they really love demographics data. So I think it’s good to kind of like show them the data and you know, kind of, okay, this is what we see from the data and then we just like saying just because we think. And so I think definitely walking them through the data, help them understand it’s definitely helped to have a smoother conversation and stuff. And we’re just, trying to evangelize more, like using the data with different, BU, for example, this is pickleball and then we also do some analysis on for some baseball glove, right? Like what are the person’s behavior? Do they buying in the same position, baseball glove? And then do they like buy more custom glove later. Like just trying to understand kind of the first, second, third purchase. And then we can like, again, like orchestrate the journey. But yeah, it’s never easy. Like, ’cause you know, like we talk about data, but then people like to believe what they think. So.

0:20:36.2 JH: Yeah. They have those assumptions and they expect people to behave a certain way or fit in a certain demographic and then you’re kind of like, let’s just see what they do. Which is awesome.

0:20:45.3 MH: That is Awesome. Well, Jessie, thank you so much.

0:20:50.0 JL: Yeah, thank you.

0:20:50.0 MH: For being on the show.

0:20:50.0 JH: It was so great to talk with You.

0:20:50.8 MH: It was awesome to have you.

0:20:52.7 JL: Thank you so much.

0:20:56.1 MH: Alright.

0:20:56.2 Jenn Kunz: I am Jenn Kunz. I am a principal analytics architect at 336. And I had written down a few because there are quite a few.

0:21:04.1 MH: Let’s get into it.

0:21:04.2 JK: So I am presenting later today partially because I just have some passionate feelings about the way the industry’s talking about cookies and consent and server side tag management. The language that we’re using and the expectations that we are setting are off. So I’ll save that for my presentation later. Tim reminded me that for a while I was the… It doesn’t matter which tool set you have, that if you have the right people and the right processes, you’re going to get value out of it. I’ll admit, I’ve walked back a little bit on that over the years as GA4 has gotten bigger and bigger that maybe the tool does matter it sound.

0:21:39.6 MH: Shots fired. The tool definitely contributes on some level. Not as much as most tool vendors would necessarily want you to believe it does.

0:21:49.7 JK: Yeah. Yeah. But I think these days, one of my biggest things is just we need to stop buying so many tools and focus on the ones that we already have and getting them working properly and getting value out of them, ’cause if you’re three analysts who are stretched between five tools that aren’t getting enough value, Buying the six tool that you think will be valuable is not going to make the difference. It’s just gonna stretch them thinner. So unless you have the resources for it, I think most people still need to work on building their strong foundation before they go onto the bigger fancier stuff.

0:22:23.6 MH: Yeah. It always shocks me how a lot of businesses don’t put the effort into mastering the tool sets they’ve actually invested in. And that serves both of us as consultants pretty well, in fact.

0:22:36.7 JK: Sure. Oh yeah.

0:22:37.3 MH: But realistically, when we walk into those organizations, what we want for them is the success of using this data effectively. And you just get presented with these challenges all the time where it’s like, well, yeah, I can show you how to do this, this, and this, but you’ve gotta wanna do this as well.

0:22:55.4 JK: Yeah. Yeah. Absolutely. And I think that it’s easier to throw money at a new tool than it is to solve the processes and problems and technical debts and all of the things with your existing tools. It’s easier to start with a blank slate when you have the naive vision of what you’re going to achieve with the tool before reality is set in. But yeah, I think we all need to be much more honest with ourselves.

0:23:19.8 MH: Yeah. It’s always more fun to be part of a rollout than a maintenance.

0:23:23.5 JK: Absolutely. Yeah. Yeah. Things haven’t been bogged down and ruined yet, so.

0:23:30.3 MH: Well, that’s a good one. I like that.

0:23:32.0 VK: Yeah, that’s a really good one.

0:23:33.6 JK: Vendors love me.

0:23:33.7 MH: Yeah, That’s right. Yeah. Hey, no vendors allowed, we talk about.

0:23:36.8 JK: That’s right. That’s right.

0:23:37.3 MH: The analytics not tools.

0:23:39.8 JK: That’s right.

0:23:41.3 MH: Oh, that’s awesome.

0:23:43.7 Matt Policastro: Hi, I am Matt Policastro, a colleague to several people who are on the podcast, previous guest to the podcast as well, but, just general analytics and data science person doing experimentation.

0:23:50.7 MH: Welcome back.

0:23:52.6 MP: Oh, I’m so excited. I heard you guys were asking this. Data does not speak for itself.

0:23:55.6 VK: So good.

0:23:57.4 MP: Yeah. Our job as data practitioners, analysts, data scientists, whatever, is that we are fundamentally storytellers. We have to be able to communicate what things actually mean to people and build narratives around those to get buy-in. You cannot just show someone the dashboard and expect them to be able to grok whatever you think that they should be getting from this. It is not self apparent. You need to sell your work.

0:24:18.2 MH: Wow. And you are a data scientist, correct?

0:24:22.7 MP: Yeah. A Little, have worn many hats, but yeah, I’ve been in a data science role and kind of.

0:24:24.8 MH: So that’s a challenging. Is it… Well, do you think that’s a challenging view for someone that’s coming from that Background?

0:24:33.2 MP: I think so. I mean, it pains me ’cause it feels like I have this conversation every time I go to a conference and talk with colleagues. But yeah, it’s just, it seems like over and over and over again, you run into folks who are like, I just don’t get it. Like we shared the Excel file with them, like, it should be clear what’s happening here. And it’s like, well, it is unfortunately we do have to be… We have to, bring ourselves down to the level of rhetoric. And actually how to win arguments ’cause, like we live in… We’re political animals. We live in organizations. We have to get… We have to work towards the things that we want.

0:25:05.7 VK: Yeah. And I think too, like what you said was you have to bring the story to the number. So just because you present a number, they may not understand what is the consequence of that number. And so I think it takes the practitioners with the data they have to step in and say, what does this mean for your problem? It takes that extra level of understanding. And if you’re really used to probably being really technical. It’s hard to probably step over that line and play the full game.

0:25:33.2 MH: Yeah.

0:25:36.1 MP: Totally. Totally.

0:25:36.2 MH: I thinking about it like the blood brain barrier, it’s like it doesn’t go through that. So you have to like find a way to jump across. Yeah. I don’t know if that’s a good analogy or not.

0:25:44.6 VK: What an analogy.

0:25:45.3 MH: I Don’t know.

0:25:45.4 MP: Well, I mean it’s like, it’s also fascinating ’cause it’s like, I mean, for many of us, we’re in the quantitative space. And we work extensively with quantitative data, but like, there are also like, there are many types of information that we can get access to. There’s qualitative data, there’s user feedback, there’s voice of customer stuff. And you can see situations where say rogue UX architect gets one piece of feedback somewhere.

0:26:07.4 MH: That’s right.

0:26:08.4 MP: And then three months later it’s like the CEO is like parroting this back and it’s like, what? Hold on. How did this get here? This is affecting like maybe three, four people like a quarter. And yet this is now something where it’s like, okay, well now we have a scope of work to actually go focus on this. And it’s like, how did we get here? And that’s… Again, it’s like that questions of scope and questions of severity, like that stuff doesn’t necessarily make it self apparent or self apparent.

0:26:29.2 MH: Yeah. Well, and qualitative data can be so powerful because it is a story in and of itself. If you watch a user struggle with something in a user study or something, it’s very powerful. You’re like, whoa, what is that? Like, Well, we should look into that. But that’s where I think as quantitative analysts, we can come back and say, okay, now let’s go look at our quantitative data set to see what is the size of that, versus sort of like, well, one person said it and we don’t need to change the entire website ’cause it’s literally like three people a quarter or whatever. So yeah.

0:27:01.4 MP: I mean, again, it can be a virtual cycle, which I feel like I’ve said, I may have even said it when I’ve talked to y’all before, but like, it can be a really beautiful feedback loop of, you can get those stories and then go and validate that with data, and then what does that uncover or make clear? And then how do you bring that back to the customer and bring that back to other people to get that additional information. So yeah, I can throw out more non-sequiturs non-consensus reality is broken, we have to adapt to the times. But, yeah.

0:27:26.8 MH: Outstanding.

0:27:29.8 VK: So good.

0:27:29.9 MH: Wow. Those responses couldn’t have been more different from each other and they gave me a lot to think about, especially Jessie’s persona, hot take. I mean, it’s so obvious now that she said it, but it’s definitely one that I think the whole industry hasn’t come around to yet.

0:27:45.0 VK: Absolutely. Awesome. All right, and here’s our next question.

0:27:48.8 JH: Can you please tell us about a book or a podcast that has nothing to do with data or analytics that’s had a profound impact on your career or the way you think about a problem?

0:28:00.8 Heather Gassman: Sure. So my name’s Heather Gassman. Interestingly, as a little tidbit, I am in a book club that reads like four books a month.

0:28:08.7 VK: Whoa.

0:28:09.1 HG: With Wendy Greco, Adam’s wife. But one of the books we read was called The Measure, which actually sounds like it might be a little analytical, it’s not at all. But it was really interesting in how I thought about my life because in this book, everyone starts receiving a piece of paper and it’s essentially a certain length. When you’re 21, you get this piece of paper and people are trying to figure out what is this strange delivery of piece of paper and what does it mean and what they come to mean, and I’m giving a little bit away, but is that it’s the length of your life.

0:28:49.6 VK: Ooh.

0:28:52.9 HG: So some people decide that they don’t wanna open the box because they turn 21 after this has been revealed as to what it is. Some people definitely wanna open the box because then they’re gonna decide well, how do I spend my life if I only have this much time, I need to live it to the fullest and others…

0:29:09.5 VK: So, you know what other people’s piece of paper sizes are as like a comparison.

0:29:13.5 HG: And they actually did all this scientific treatments on the thing to figure it out. And it really does come down to like, this is how much time you have. So I just think it’s a really, really interesting concept and a really great book to talk to others about in how would you choose, what would you do? Would you look in your box and what would you have done differently if you knew? Do you think like, I mean it’s, we only have so much time in this world. But it really helps you sort of like…

0:29:45.1 MH: Do you really wanna spend your time optimizing those paid search keywords.

0:29:50.6 HG: Absolutely. Absolutely. So I just think that’s a, it’s a good one to put on your to-read list, especially if you’re in a book club.

0:29:56.0 VK: I am in a book club and now I’m gonna have to look it up and make.

0:29:58.4 MH: Does your book club do four books a month?

0:30:02.5 VK: No, we do one a month. We’re normal.

0:30:03.1 HG: Not everybody does the four, but it’s just the really nerdy ones, So yeah.

0:30:11.3 VK: And then what’s your second book?

0:30:11.4 HG: The second book is, there was just a chapter related, and it was, I think I misread the topic when I came up with these books, but there’s a… The book called Wellness that’s actually set in Chicagoland. So that was kind of fun for me, to see the locations of Chicagoland and maybe would be fun for your fellow measure camp attendees.

0:30:33.3 MH: That’s like, What’s the white, what’s the one about the Chicago fair and the serial Killer?

0:30:35.8 HG: Oh, The Devil in the White City.

0:30:37.6 MH: Devil in the White City.

0:30:39.0 HG: Yeah. That’s another good one. Erik Larson.

0:30:39.2 MH: Can’t apply that to analytics, I don’t think, but.

0:30:43.9 HG: No, Probably not. But yeah, he does have a new one out. But anyways, the Wellness book is a really long one, so not for the faint of heart, but there’s a whole chapter that I thought was super interesting on the Facebook algorithm. So in the book, the character has a really terrible relationship with his dad and his dad starts getting all this Facebook stuff and essentially going down a rabbit hole of believing all sorts of things are gonna happen that really aren’t true but…

0:31:11.5 MH: So it’s total fiction, it’s not at all based on reality.

0:31:16.4 HG: Yeah, this is a fictional book, but actually I think the author did quite a lot of research and it was interesting to me. I mean, as all of us use Facebook and I personally have spent a lot of time in my measurement career in the world of search engines, and recommendations engines. So I thought that was a really fun way to kind of build it into a story that helps the common man, if you will, understand how Facebook decides to show one person one thing and how you can get like, really caught up in fake news if you will, if you’re… ‘Cause it keeps kind of feed you more and more of what you already looked at and already consumed. But it’s kind of interesting.

0:31:56.5 MH: Ah, Thanks so much for stopping by.

0:32:00.6 Prolet Miteva: Hello, my name is Prolet Miteva and I am currently what I call a world explorer, as I am taking up extra long sabbatical from working in analytics, which I was in for over a decade. So I have a book suggestion that had a very, very big impact on me personally. And I will tell you also how it’s relevant to analytics in kind of like adjacent manner. So the book is, Die with Zero, and I should have been more prepared. I did not get who the author is, so just Google it, it’s like, it’s there. It’s available as an audio book if you’re too lazy to actually read it. And it made a very, very big impact on me personally more from the perspective of kind of evaluating your life and your life choices and how that should be affecting what you do right now in your life.

0:32:54.3 PM: From the perspective of the high level, hey, like really what you can do in your 20s, you probably cannot do in your 70s. So if you go and decide to jump off a parachute, you probably wanna do that in your 20s, 30s or early 40s and not when you’re in your 60s, 70s or 80s. So the book does a very good job in really helping you evaluate what you’re doing with with your life now and, what you should do now versus later. And how it made an impact on my analytics.

0:33:28.6 MH: Is the Die with Zero, like no regrets or no, you can’t take.

0:33:31.0 VK: Zero things left on your list, maybe.

0:33:34.6 HG: No, it’s zero money.

0:33:35.2 MH: Zero, okay.

0:33:36.9 PM: Because it actually.

0:33:37.7 MH: You can’t take it with you. Okay.

0:33:38.0 PM: Yes, it’s also very connected to the whole idea of financial independence and where you should be, but also not that you should just be saving, saving, saving forever. You should live now, you should live for the moment, and you should be spending at different decades or kind of like in a bundle of five to 10 years together. How it’s relevant to analytics, I would say, is, it also gave me a very different perspective of work and working with people within the company. So I was in the corporate for the longest time, basically pretty much my whole life, and just reading the book, getting to the point where I was also closer to my own financial independence gave me the perspective of just like really not caring as much and not being as committed and kind of giving crap about what other people are thinking. So actually in my last job in my analytics work, a lot of what my team heard from me often was kind of what are they gonna do, fire me? And just from that perspective and being able to kind of push in different directions, push for what I wanted, push for what I thought was right for my team was very, very valuable.

0:35:00.6 PM: Basically becoming braver and becoming more focused on things that I really liked, the things that I knew that my team liked, and pushing in that direction and not just blindly following. It’s like, oh, I’m told to do this, so I should, and I should execute exactly how I’m being told. And pushing that boundary was really, really helpful because in a way it opened up my career, my opportunities to actually speak up, and my opportunities to teach my teams to speak up.

0:35:37.3 VK: My girlfriend and I have post-its on our computers that say chutzpah, and chutzpah is about that, right? It’s about doing the brave thing that feels intuitive to you, but sometimes the consequences might have held you back, or trying to think about what those consequences are versus actually being brave to do the right thing.

0:35:55.5 MH: I’m wondering when you read the book, ’cause I feel like as long as I’ve known you, I can’t imagine anyone actually telling you what to do, or at least not doing it twice but.

0:36:03.9 PM: Believe it or not, it got even worse after.

0:36:09.3 MH: Awesome. I like that. That was a great, great answer. Moe, I’m gonna take this opportunity. You’ve brought it up many times, but I’m gonna challenge you to actually equate it to why it’s useful for analytics. The Acquired podcast, which is long form and talking about businesses, and you’re sucked into it, and you’re constantly referencing it, can you tie it to how it’s…

0:36:31.4 Moe Kiss: Data and analytics?

0:36:32.2 MH: Yeah. Which I think could be the management or the management of teams and/or.

0:36:37.8 MK: Okay. So the reason I like it is because it’s almost like a book. Because the podcast episode’s like three to four hours. You are really delving deep. I think what I get the most value out of it is seeing about company cultures, which is something that’s really important to me. Like how do you drive high performance? How do you move fast and not like burn everyone out? Like how do you… I guess what makes great companies great, but then at the end there is also… There’s like obviously the stories of when companies IPO and I find that really interesting, like the whole how they got investment when they go to IPO, what was like… They know the stat about everything, about how many shops they had, what their CapEx was like. Like they just know every single detail. And so they go through that and then at the end they analyze the company and they analyze, like they have a whole framework for it, which someone else will know that off the top of their head that I don’t. But what sets that company apart, like in terms of either their financial performance or the factors that differentiate their brand from their competitors and that sort of stuff.

0:37:47.0 MK: So I think the thing is, as I’m growing in my career, the reality is, I definitely do less data work, but you’re actually having strategic discussions a lot more. And so it’s more about, what are ways of thinking that can help me with those strategic discussions? I obviously still want to use data to inform those decisions, but there are often things we can adopt, right?

0:38:10.3 MH: Well, it seems like also, ’cause you’re at a… How much has Canva grown since you’ve been there? That’s putting you on the spot, but…

0:38:17.7 MK: 10 X.

0:38:19.1 MH: 10 X. Yeah.

0:38:20.6 MK: Exactly 10 X. It was 500 people when I started.

0:38:21.6 MH: I haven’t listened to as many episodes of it, but they kind of go through the, I mean like the Nike ones, one I listened to in video where it’s like, they go through sort of the growth and evolution that like, sometimes I feel like we treat, we think like right now, our company is gonna be very similar tomorrow as they were yesterday as they are today. But recognizing that there’s an evolution. There’s not one magical path. There are decisions that don’t work out. It seems like, I mean, I’m not… I wasn’t seeding that. As you were giving that answer, I was like, oh yeah, but she’s like living through one of the stories that very much could be an acquired episode at some point down the road. But where you kind of ended with the… What they do is they talk through and think about the company and the operating environment and the competitive environment and what they did and what worked and what didn’t. And I’m like that for analytics, like that’s the way we should be somewhat taking a longer view. Not ’cause if somebody needs their weekly report, it’s not saying, no, let’s talk about the overall evolution. But I did not know what your answer would be to that. And I wasn’t sure what a good, but as you were talking, I was like, that’s what as a hook.

0:39:43.0 MK: The great thing about a measure camp and all coming together, especially the Chicago measure camp, is that everyone seems to have brought their spouses. So I got to have a good old chat with Julie earlier, which was delightful. And I think when I described this about you, she would probably agree in terms of being incredibly well-read across what’s happening in the industry. Probably so much so that you don’t have enough time for all of the other stuff. In addition to all of the crazy things you do, volunteering and running things and all of that stuff.

0:40:17.3 MH: Parenting, spousaling.

0:40:18.4 MK: Parenting. Yeah.

0:40:19.0 MH: Okay.

0:40:19.2 MK: Yeah. All the things. So you’re a man that probably has strong views on non-data and analytics books and podcasts that have changed your career.

0:40:26.9 MH: Yeah. This is one. I mean, I think I might have contributed to this question. I had in a very short period of time read Stumbling on Happiness.

0:40:38.6 MK: Sorry, Stumbling on Happiness.

0:40:41.0 MH: Stumbling on Happiness, which I think is Dan Gilbert. And I think it’s actually in like the self-help section.

0:40:45.5 MK: Of course it is.

0:40:48.9 MH: I read Blink by Malcolm Gladwell. And I read Brain Rules by John Medina, who’s like a neuroscientist. And to the life of me, I think many of them said some of the same things. They were all basically about the brain and how we don’t… Stumbling on happiness that we think something’s going to make us happy and then we get there and it’s not. And Blink, our intuition can be very trusted and amazing. We don’t fully understand why, but it also can not be. So like those three, and I just read them at a time when I was starting to dig into data visualization and becoming more aware of the need for communication. And somehow I just read all of those and I was like, oh, there’s a whole aspect of the way that we bring things in. We’re trying to analyze how customers are gonna behave, but customers are human beings and they’re messy.

0:41:41.0 MH: There’s not a magic formula, probably more so on the when communicating effectively to stakeholders, trusting people’s intuition. The kicker is that I will remember anecdotes like one of them, I think it’s maybe Blink, where somebody sees somebody across the street and their memory is super clear. They see, I don’t know, Queen Elizabeth or something. Clearly my brain doesn’t remember enough of it and just swears that she was wearing something. And there’s like photo evidence that they weren’t. So the same sort of thing that goes on with unreliable eyewitnesses in crime, but like the various anecdotes from those like crop up all the time when it comes to, okay, you’re trying to communicate this. Don’t just think that because here’s this messy heat map and you figured out what it means that you can just flash it up. And it will work. So, and they’re bigger. Like, I’m not comfortable, like, buying a book in a self-help section just ’cause I’ve got whatever various forms of…

0:42:40.2 MK: So did you just buy it online then and send it straight to Gladwell?

0:42:43.4 MH: I don’t know. I’m not sure where I got it. I had a physical. I mean, I think I actually did buy it, but I couldn’t find it ’cause somebody had recommended it. And I was like, why isn’t it in a section that I would go to?

0:42:50.8 MK: And you’re like the section that you probably should go to.

0:42:53.4 MH: Probably the section that I should probably constantly spend a lot of time in. But so, yeah, so it was kind of like a three, ’cause I just can’t keep straight which ones were which. And it’s interesting. Gladwell’s starting, people either like him or don’t like him. And I was a big fan for years. But I’m starting to get a little sycophantic on some of his podcast stuff. So, but it’s always a great…

0:43:18.0 MK: I feel like a couple of those books I have in audible ready to go and haven’t started them for various reasons. Like, I do feel like you need to kind of be in the right headspace too.

0:43:26.4 MH: Yeah. What’s your point about, to your answer on the Acquired podcast, thinking of that as a book that it goes for, that’s a good, like that can be the intimidating, like, I don’t wanna start it ’cause it’s like three or four hours. Like, yeah, you can stop it and you can pick it up later. Just like a book. So cool.

0:43:43.8 VK: So Michael, after listening to those responses, do you feel like you understand Tim a little better?

0:43:48.1 MH: Absolutely not. No.

0:43:55.4 VK: No, those are definitely some good, interesting read ideas I’ll have to add to my either listen or read list. I especially wanna check out that recommendation from Prolet, Dying with Zero. That’s a really novel concept. I’ll have to look into that one for sure.

0:44:06.1 MH: Yeah, for sure.

0:44:09.5 JH: So, thank you for joining us. We would love to hear your thoughts on what function or feature you get most excited about when you get to use it in things like Google Sheets, Excel, Power BI, or anything you use in your day-to-day work, and why.

0:44:23.0 Ken Williams: My name is Ken Williams. I’m the founder of Dive Team. And my answer is hopefully one you haven’t heard, which is that I really get excited about SQL orchestration tools. The biggest ones are DBT and Dataform.

0:44:35.8 JH: Yep.

0:44:39.9 KW: I’ve heard, Moe, you talk about DBT before.

0:44:43.5 MK: We’re like DBT’s biggest user, I think, at Canva.

0:44:47.8 KW: Yeah, I started in DBT. And then when Google Cloud acquired Dataform, started using Dataform. And now I’m in it very deep. And for me, the reason that I find it so exciting is because there are problems that I find difficult to solve with raw data because I spend so much time in my role working across a lot of clients. I spend so much time doing the same thing over and over again, writing queries to get data in a certain format so that I can use it. And with Dataform, I just, I do it once, I schedule it, I copy and paste it across clients. It makes just getting data organized and set up in a templated way that I can use it so easy. So I have been very deep into using it with Google Analytics like a lot of people. But what we’re doing with the group that I work with in my daily life is expanding it across lots of data sources. So we’ve got this library we’re building of off-the-shelf models that we can just plug in.

0:45:52.2 MK: Oh, that’s cool.

0:45:53.3 KW: Yeah. So if somebody’s like, I use meta ads and Google Ads and Google Search Console and Google Analytics, it’s like, well, obviously everybody does. So I’ve got all those things, plug them in, five hours later, I’ve got like a really robust data warehouse. And it’s all possible.

0:46:06.2 JH: Damn. That’s fucking genius. I told you. This is the most interesting questions of the day. Okay. So what is the primary difference do you find between that and a DBT? Are there differences you’ve noticed or things that have made you prefer it?

0:46:20.6 KW: When your day-to-day use of Dataform and DBT is super similar. DBT has a few features that Dataform doesn’t. It doesn’t document your models quite the same way. Although BigQuery has a lot of built-in documentation. I think that Google Cloud probably wants you to use that instead of replicating DBT’s models. And there are some little functions. Like if you want incremental tables, it’s kind of manual with Dataform. It’s really out of Bosch and DBT. You can do everything. It’s just a little different.

0:46:50.9 JH: Oh, I feel that’s a sticking point. I feel incremental tables is like…

0:46:55.6 KW: It is a whole thing.

0:46:57.4 JH: The most important use case.

0:46:57.9 KW: It is there in Dataform, but you have to write a little block of JavaScript.

0:47:05.7 VK: Okay, it’s just a bit nigglier, like it’s harder to do.

0:47:06.7 KW: Yeah, exactly. And it’s harder to do in like five lines of JavaScript. It isn’t that hard to do. But it’s, you have to know what you’re doing. To me, though, the big difference is with DBT. And the reason I switched is because with DBT, I was almost always using DBT core, which means you have to spin up a server to host it or run it locally. Whereas Dataform just runs in BigQuery. So you don’t have an application. And it’s just one less thing to monitor and that might go down at some point. So almost everything I do is in BigQuery typically, unless a client really insists that I use Snowflake or something else. So it’s just very convenient. If I’m already in BigQuery, I might as well just spin up Dataform. So that’s my answer.

0:47:51.3 VK: Yeah, that’s a good productivity one. And you don’t find that you have to customize it very often? Like the sources, your library of is pretty robust now where you really are like, I’m just pulling things off the shelf or?

0:48:00.9 KW: I wouldn’t say we’re there yet. Okay. That’s hopefully. So we have found that if we spend a lot of time in a data source, it gets more mature over time. And so the way that we… Like Google Analytics is really complicated. And there are a lot of people who have built models and made them open source. And we’ve learned a lot from different people. But we’ve kind of taken other people’s ideas and put it into a format for us that’s very easy to edit the things that need editing. So like different people track different custom dimensions. So we’ve made that as easy as possible. Like we’ve pulled that out in a separate thing. You don’t have to get in and. You can modify the core code when you want to change that. It’s like a separate thing. So stuff like that. But it’s not, it always, it gets you 80% of the way there. It doesn’t get you 100% of the way there.

0:48:55.7 VK: I mean, 80% is big.

0:48:56.9 KW: 80% is a lot. And in the world that we’re talking about, too, we used to charge lots of money for lots of time to do lots of custom work. And we can do things super quick now.

0:49:07.7 VK: Nice. Well, thanks for sharing the tips with us.

0:49:10.7 KW: You’re welcome.

0:49:11.9 Adam Bowker: Cool. So yeah, my name is Adam Bowker. I’m a director at Ricoh Digital Analytics. And one of the hacks that I’ve found to be really useful is if you’re dealing with a mix on your team of very technical people, there’s often a gulf between people who are either end users or fairly technical end users that might know some Excel or maybe a little bit of SQL but not a lot, versus the very technical people in R or Python or SQL. And often you have needs for the less technical people to still be able to interact deeply with tables in your data warehouse or something. And one way that we found that was really helpful for that is to just use Google Sheets into BigQuery because you can just use those as tables. So you can put line level data security on it.

0:49:57.9 AB: You can do a little bit of that. But if you want, end user marketers who are dealing with campaign codes or they have a specific list of things they wanna analyze in some other table. A lot of BI tools aren’t good at integrating lists of 20 or 100 or 1000 values into something else. So it’s a really easy way to quickly get friendly user data into BigQuery in this case. But I think there’s probably other connectors too. So it’s just been a nice way to just get from a spreadsheet to SQL and allow your SQL engineers to then do your actual functionality.

0:50:32.0 JH: And is this something you’re doing from the sheet side to say, hey, push it into BigQuery…

[overlapping conversation]

0:50:35.9 AB: You can do it both ways. You can do it both ways.

0:50:38.0 MH: Oh, okay.

0:50:38.6 AB: So you can have a table or a query that just populates into sheets. Or you can just say to BigQuery, this sheet is a table. And then anything you change in the sheet will be updated in the table. So you don’t have to give them insert or update privileges for them to be able to do that.

0:50:54.1 VK: And the bit that I actually love the most about this is the opposite of what you’ve said.

0:50:58.0 AB: Okay.

0:51:02.1 VK: So you’ve talked about basically making the data that’s in the sheet available to your engineers, right? I actually think it also provides a gateway for your less technical data team to get an introduction to BigQuery and to be like, oh, this is a familiar setting. This is what it looks like here. Okay. And the funny thing is, like, I know so many people that are like Excel gurus. And I’m like, you can do SQL. Like, if you are very good at Excel, SQL is the thing you should learn because it will be very intuitive to you, I think. And that is creating a bridge for someone to be then like, okay, I’m gonna learn BigQuery. I’m gonna start learning some SQL, which I think is so cool.

0:51:42.0 AB: I found that to be generational too. Like a lot of the people who are 30 or 40 and up learned in Excel. All the newer people are learning R or Python. So we found if you take the Excel concepts and bring them into SQL, then that’ll work for some people. Having clause, aware clause, that’s what this means. This is how you would even have pivot table. But if you know Python first, then that’s not going to make any sense.

0:51:58.1 VK: Yeah, totally. Totally.

0:52:04.3 AB: Yeah.

0:52:05.1 Brian Howkins: So Brian Hawkins here. I’m head of optimization technology at AtSwerve. To answer the question, this is a feature related to GA4 where when they deprecated, optimized their internal testing solution, rather than put a new testing solution in place, they opened up a new service, a new utility, a new API. Where any third-party testing solution can natively integrate with GA4. Which is pretty cool.

0:52:31.6 VK: That’s actually fucking cool.

0:52:36.2 BH: Yeah, very cool. And so now everyone assumed you need Adobe Analytics to use Adobe Target. And so what we built is, and it opened the door wide open for me at Prova to support any testing solution with native APIs, the ability to create audiences. And so what this service that Google does is basically creates a special API where you can pass an event, and then you can automatically create audiences within GA4 via programmatically. And so this is my favorite, most exciting thing, because now anyone that’s using GA4 can use Adobe Target and just out of the box turn key. And it’s very similar to what Adobe Target and Adobe Analytics have, where there’s like a native integration, basically stitching and aligning visitor IDs. But it’s also cool from my standpoint, because Mia Prova has always been, we’ve got lots and lots of Adobe customers, but now we have several GA4 customers. And now, folks are coming to us talking to us like AB Tasty or other testing solutions that’s using GA4 as a native reporting or so.

0:53:43.8 JH: And so it sounds like you’re really taking advantage of this feature. Do you feel that others in the industry know enough about it or do you feel like it’s not, like it’s kind of… Is it a known known or is it still a little unknown?

0:53:55.9 BH: I think it’s a little still unknown because it’s really got opportunity way beyond testing. So this was something that Google did with Optimizely, with Convert, and I think AB Tasty. AB Tasty initially, before releasing it open to everyone. So those three vendors had it, but a lot of companies are still relying on the handoff from the testing solution client sites of this, whereas this integration service basically automates audiences. As soon as it sees an event, it creates the audiences in GA4 for analysis, and it flows in a BigQuery.

0:54:29.3 JH: Oh, that’s nice.

0:54:31.2 BH: Which is really slick.

0:54:31.5 JH: Yeah.

0:54:36.3 BH: And so the Adobe Target community, because it creates audiences automatically within GA4 and then in a BigQuery. Those in the Adobe community can use those audiences in advertising, which that’s an activation layer that the Adobe Target community hasn’t historically had.

0:54:51.3 JH: Amazing. Such a good one.

0:54:52.1 Krista Seiden: Hey, everyone. I’m Krista Seiden from KS Digital. So I’m going to talk about Google Analytics 4. And the thing that I find most exciting about GA4, I probably say that all the time. I love this. It’s my favorite feature. But I think the thing that I find most exciting is the ability to customize any report you want and then customize your left nav to meet your business’s reporting needs. So you can never do that before in GA. And now you can, for example, if the primary metric of an out-of-the-box report is not what your company looks at, you can change that primary metric or you can make a whole new report collection that is just a regional-based or a team-based type report collection in your left-hand nav. So I think it’s really flexible, really cool.

0:55:36.9 KS: So previously it was all like preset and you had to choose like from boxed up solutions versus like now you literally make your own kind of navigation.

0:55:48.5 KS: Exactly. Yeah. So you still have the out of the box thing that’s like set up when you install Google Analytics, but you can totally change it and customize it and make it your own or make it you know what’s going to be the best solution for your organization.

0:56:01.9 JH: Nice. That feels like You can probably make it a lot lower pressure, too, for newer people to the tool. It’s probably a lot less overwhelming to be like, I have to look through the whole list and know what I need to pull out.

0:56:11.6 KS: Yeah, totally. I think there’s positive and negative to it, right? You can do almost anything you want, so you can make the reports that you want to need. But first, you have to know that you can do that, which not everybody knows. And then second, it’s not an insignificant amount of work to completely customize your account. But if you’re… Especially if you’re a larger company and you want to set up reports for various groups and whatnot, if you have that kind of like admin function, you have somebody you’re kind of responsible for really setting it up and making it the most useful for your company, you can totally do that.

0:56:45.6 VK: That’s so cool.

0:56:47.8 JH: And you obviously are seeing like what different companies are doing through your work. What are some of the main things that people customize? Like what are you seeing happen?

0:56:58.9 KS: Yeah, so I think one of the biggest complaints people have about GA4 is that there are no views like we had in Universal Analytics. So you used to be able to have like a view for your European traffic, a view for your US traffic, a view for your product team, a view for your marketing team. So we don’t have that in GA4 anymore. Everything is property based, but you can make collections of reports that are filtered down or edited to just be for certain use cases. So you can kind of back your way into that use case to have certain areas of the UI that are dedicated to different teams or different needs.

0:57:29.7 Fred Pike: So, my name is Fred Pike. I’m a managing director at Northwoods, an agency in Milwaukee, and I lead the GA and GTM practice area. And my favorite tip is about GTM, which is my fricking favorite Google product ever, so hands down. So the thing… There are two things I do. I know you said only one, but two is better than one, right? Yeah.

0:57:48.4 JH: Yeah. And we also, we love an extra.

0:57:49.9 MH: We love a twofer around that.

0:57:51.9 JH: We love a twofer in analytics.

0:57:53.1 FP: So, one thing is every time I create a tag, I create a custom parameter called tag_name, and then include the name of the tag. And the reason that’s useful, you look at that, you look skeptical.

0:58:09.3 JH: I’m like, it’s been a while since I’ve been doing GTM, so I’m like, why is he going with this?

0:58:11.1 FP: Yeah, okay. We’re gonna cut this guy.

0:58:12.9 MH: No, no, I think that’s where you’re going. Sorry.

0:58:14.8 FP: So the reason it’s useful is ’cause when you’re debugging and you’re looking at an event name, you don’t know where that’s come from unless the tag name is associated with it. So, so many times, I’m trying to figure out where the heck did this tag come from, or did this event come from? And if I see the tag name, I know it’s mine. If I don’t see the tag name, I know it’s some other source. And there can be… There’s like five or six different ways that events can get sent to GA 4, but at least I can try to figure out where that event came from. And once I know that, then that helps me down the troubleshooting line.

0:58:49.1 MH: Yeah. Big time.

0:58:49.3 FP: So the bad thing about the tag name is that there’s no way that I have found so far to do this automatically. Yeah. So you have to remember, okay, I’m gonna add it. I’m gonna copy the name of the tag and I’m gonna paste that in my parameter field, my value field. And so if you don’t do that, then you’re gonna get bad information ’cause it’ll default to the Google config tag if you don’t give it the proper name. So that’s the downside of it. But if you’re consistent, it’s really helpful.

0:59:20.8 JH: Now, for the people like me who haven’t used GTM or even GA in a very long time, have I got it right that, so you’re putting it in the custom dimension ’cause the tag, there could be multiple tags that fire for each event, or if I… Like, I’m trying to figure out how you wouldn’t know the tag’s name and how it relates to the event.

0:59:41.2 FP: So that’s a great question. You would think that the tag name would relate to the event name. So like add to cart, and the tag name says add to cart. But for add to cart, that’s probably the case. But many, many times people say, oh, the tag name is, we’re going to do the dog conversion or something, and the event name is something totally different. Form submission or whatever.

1:00:00.6 MH: It’s a real lack of taxonomical control sometimes in creating implementations.

1:00:05.8 FP: And that happens a lot.

1:00:09.4 MH: And especially if you walk into an implementation that’s not your own, right?

1:00:10.7 FP: Exactly.

1:00:11.1 MH: So you walk in as a consultant and you start fixing stuff, and one of the first things you’re doing is trying to figure out how is this event even firing? You can go back in and dig it out at GTM.

1:00:24.5 FP: Yeah. And one of the things you can do in GA4 is in the admin section, you can modify or create events based on other events coming in, and I hate that. It works at the browser level. It doesn’t work on the server level. And so there’s all types of problems with that. But you can get such confusing tags in that modifying event. Modify and create events section. So I always, once I see that, if I can’t convince a client to get rid of it, I put a GA4 admin event as a tag name. So at least I know it’s where it’s coming from. So that’s one of the things.

1:00:58.0 MH: That’s a nice tip.

1:01:00.1 FP: And I promise you too, right?

1:01:00.2 MH: All right.

1:01:01.1 JH: Oh yes.

1:01:01.5 MH: There you go.

[overlapping conversation]

1:01:04.9 JH: Lucky Second.

1:01:06.4 MH: All right. Yeah.

1:01:06.5 FP: Okay. So the second one is related to notes. And in tag manager, you can add a note to anything, a variable, an event, a trigger, a tag, whatever. Use it, fricking use it. So tell people, tell yourself six months from now, what was I trying to do with this? Or if you’re copying from somebody, if you’re copying something from somebody’s blog, include the link to that, so you know where that came from. So again, six months from now, you’re not figuring out why am I doing this? Where the heck did this come from? So that has been really helpful to me too.

1:01:40.2 MH: That’s awesome. Yeah. ‘Cause yeah, a lot of times you’ll be like, I need to find an answer for this. And you find a good solution on like some blog post, but then a couple months later you’re like, where did I find that? And you’re Google searching all over again.

1:01:54.0 FP: And that happened ’cause I took over a client years ago and one of the notes said, Larry found this in a blog. And it’s like, oh my God, who the heck is Larry, and what blog? So it’s like they documented it, but it was worthless. So that taught me to back that up.

1:02:08.8 MH: You can go down your list of usual suspects. There’s not that many good quality GTM blogs out there.

1:02:15.4 JH: I’m like, there’s also not that many Larry’s at the company, surely Well, unless it’s a 50,000.

1:02:17.0 FP: Who’s big hospital there?

1:02:18.4 JH: Okay. All right. There was a lot.

1:02:19.0 FP: It was a new client. So I got to know Larry over the years, but…

1:02:22.6 JH: Well, those were some great tips. Thanks so much for coming along.

1:02:25.6 MH: Yeah. Thank you Fred.

1:02:26.4 FP: Absolutely. My pleasure.

1:02:27.7 VK: So those responses all just happen to be very Google ecosystem heavy, but these are some really great ideas, I think for folks to try out inside of their own work and organizations.

1:02:39.0 MH: Yeah. Absolutely. All right, jumping into our last and final hop on the mic question from MeasureCamp Chicago.

1:02:47.0 JH: All right, well thank you for joining us. The question that we are interested in your response to is, when interviewing an analytics candidate, what is your favorite question to ask and why?

1:02:54.4 Adam Greco: My name is Adam Greco, and I’m a product evangelist for Amplitude. I’ve been in the digital analytics space for, oh, 25 years. Early employee of Omniture. Been a consultant, been on lots of different sides. So.

1:03:08.7 VK: You’ve seen some shit.

1:03:08.7 AG: Yeah.

[laughter]

1:03:09.2 AG: You said I’ll have a lot more hair. So I kind of look at this question two ways. So you phrased it as if you’re interviewing someone, what is a question you ask them? And I actually use the same question whether I’m interviewing someone or if I am interviewing for a position. My big thing, and it’s actually something I just talked about at Measure Camp, I did a session how to turn analytics from a cost center into a profit center. And so the question that I like to ask an interviewee or if I’m interviewing is to basically say, can you show me examples of where you have turned data, not just into insights, but can you point to specific things that have changed on the website or mobile app that wouldn’t have changed unless someone had figured that out through data?

1:04:02.6 AG: So as an interviewer, I wanna understand, does a person who I’m interviewing really have experience, not just running reports, but actually saying, here’s a way I could show you that I found data, I figured out an insight. We decided this is a change to make, and six months later here was the cost that we either saved the company or the incremental revenue we drove. And if I’m interviewing for a company, which at my age I don’t do as much, I wanna ask the team that I’m interviewing into, are you a cost center or a profit center? And if you say you’re a profit center and everyone loves our analytics team, then show me examples of where you have done the same thing.

1:04:37.3 VK: I love that. I love that.

1:04:38.9 MH: That’s nice.

1:04:42.2 VK: One of my first roles in digital analytics, we were like beg, borrowing and stealing resources from other teams to run experiments and things like that. So one of the ways that we really got the UX designers and some of the graphic designers really excited is to add onto their portfolio some, of the outcome numbers. Some of the like, but what did this do for the business? And so it was like, sure that was beautiful imagery, like those fonts like Chef’s Kiss however what did it do for the business? And that’s what actually got them really excited to partner with us. So I think that question where they’re asking on either side really inspires something that’s very insightful about the experience you or that candidate is about to have that organization.

1:05:15.5 MH: Yeah. And then I like that you bring it to the interview when you’re looking for a job because that says so much about the company you’re thinking about joining, as opposed to maybe other companies you might have an option of working with, which is a big determining factor in kind of the quality of life you’ll have inside of that company, ’cause it’s…

1:05:37.4 AG: Yeah, exactly. And when I worked at Salesforce, I’ll tell you the team that I took over, they weren’t super happy at first, because they were just running reports. And I basically either once a month or once every two weeks, I said, listen, I know this is gonna sound crazy, but I actually want you to work at home and this is way before COVID. I want you to work at home for one day and I want you to just turn everything off and I want you to go use salesforce.com, find something that you think stinks, and then go into the data and see if your theory is supported by data. And then I want you to go work with a couple of designers or a couple of people the company say, what would we do to fix this problem?

1:06:16.4 AG: And every month I had like five or six people on the team. I got five or six really interesting ideas. I would go to my boss’s name was Kendall, he was a CMO. And I would run them by him and we would try a couple of these and to tell you the look on an analyst’s face when the CMO says, I wanna try your idea. And then we try it. And if that turned out to either save us a bunch of money or make us a bunch of money, I used to joke with my wife, I said, that employee of mine locked in for a year because at what other company are they able to say that they had a direct impact? They could say I impacted salesforce.com, and that is such a powerful thing to do for employees. And if you are an employee at a company and your company… If you can’t prove that everything that you do every day is leading to the bottom line or helping the company in some way, why do you wanna work there?

1:07:07.5 AG: And so go find another job and find a company that would value enough to really give you that empowerment. And I think that’s what makes the digital analytics field really exciting is there is an opportunity to have an impact, but I think we get a little bit lazy sometimes and it’s hard and I don’t think we try hard enough. And I always tell people like, try harder. If your company’s not doing this, go to another company or make a change. Push them to do this. And if your boss doesn’t get it, then there’s other bosses who will.

1:07:39.8 Sam Samantha Burge: Hi, my name is Sam Burge, and I’m senior manager of data science and analytics. So a little bit of background. We have done a lot of college hires in the past and a lot of times there’s a lot of nerves in it. There’s a lot of pre-prep and training. So they go through a very specific format to answer a question. So over the years, I’ve actually picked two questions, if that’s okay.

1:08:00.5 VK: Yes. We’ll allow it.

1:08:02.1 JH: No, thank you.

1:08:05.9 MH: No.

1:08:06.6 SB: Because one is more at the beginning of the interview to break the ice, which is like, tell me something you’re really proud of. It can be in your school life, it can be in your work life, philanthropy, a project that got you really excited and can you just walk me through that?

1:08:17.4 VK: Nice.

1:08:18.8 MH: I like it.

1:08:19.6 SB: So just opening up and like…

1:08:22.2 VK: Getting them comfortable.

1:08:22.5 MH: Getting them comfortable, getting them to talk to about something that is really great. And then if they continue to interview and I’m like on the fence, the interview is a little stilted, you know they’re going through a process, you’re not getting all the detail, and I hit him with a curve ball. And I either ask them about Halloween or I ask them about like one of their favorite sports or holidays.

1:08:47.3 VK: So what’s the actual question you asked about Halloween?

1:08:49.8 SB: So for example, somebody I asked before, I was like, so tell me how do you celebrate Halloween, and do you enjoy dressing up, going in the office or outside? Do you like trick or treat with the family? And I feel like it kind of diffuses the moment for a second, and they get excited and they talk about this or I ask them like, what’s your favorite holiday and what do you really love about it? Like what makes this the time of year that you enjoy the most? And I take it away and then I try one more on point question about the job. And then I usually have the lay of the land if it was nerves or something else, or if it was really just…

1:09:22.6 VK: Not a good fit.

1:09:23.5 SB: Yeah, not a good fit.

1:09:24.7 MH: I love that. I love the first question, ’cause a lot of times in an interview process, I’m really looking for what I call is like watching people spark. So like what pops? And so if I can get that moment in that interview, I’m like, okay, I finally learned something about you and it’s so valuable. So that first question is I think a really great one for that.

1:09:45.0 VK: Great way to open.

1:09:46.3 SB: Right. And you learn so much. So if they pick a project right, and they walk you through it and you can see that they’re taking certain steps or the way they talk about their private life and that spark comes out, but you can also tell is that the right fit for this position? It sounds a little horrible but like, oh, is it more technical? Is it more strategic?

1:10:04.2 MH: That’s right.

1:10:04.9 SB: Which role did they take on? What did they do? So that’s why I really like it and people get excited and they feel a little more comfortable I feel like.

1:10:11.5 MH: Yeah. I love to see people share their passion and sometimes when they’ve worked it really hard on something, it really comes through.

1:10:18.8 SB: Yeah. And it’s lovely. And you learn so much, like it’s so much fun and or you find common ground and you can really start getting into a really great place of a conversation.

1:10:27.7 MH: Yeah.

1:10:27.9 VK: I like that. It’s good culture fit stuff comes outta that too.

1:10:31.5 MH: Yeah. Well the Halloween question is also really good for culture fit, right? We dress up in this office, so.

1:10:38.5 SB: I was asked, I actually stole this. I was asked in an office before, ’cause that’s what they did. They went all out on Halloween and everybody’s listening, who knows which company that was, but yeah, they went all out on Halloween. They’re like, can you come with us? We have one multiple years in a row.

1:10:54.1 VK: Very fun.

1:10:57.3 MH: Oh wow.

1:10:57.4 VK: Very fun. I like it.

1:10:57.5 MH: No pressure.

1:10:57.6 SB: No pressure at all. But then when we went remote, I adjusted it and I asked about the holiday or something else to just like get that feel because that question diffused me in that interview and I’ve used it since then. And it’s like a good figuring out at the end if this is the right thing.

1:11:13.0 VK: Love.

1:11:16.0 Ying Liu: My name is Ying Liu. I am the senior digital analytics manager for Adobe’s Experience League website. So I typically asked this question in the last, ’cause usually you go through and introduce yourself or do you do challenges, etcetera. That’s normal. But I really wanna get out of the candidate is how do you improve your analytical skills? So typically, that’s how you can ask an open-end question and then you can say if this person has a fixed mindset or a growth mindset.

1:11:44.9 VK: I like that.

1:11:46.1 MH: I like that a lot. I’ve asked similar questions over the years too. I’ll ask people like, how do you gain new information or build your skill sets in the analytics space?

1:11:55.4 YL: Yes.

1:11:56.4 MH: I remember I hired an analyst just ’cause they mentioned…

[overlapping conversation]

1:12:00.0 VK: I was just gonna say that. Sorry. Although you’re like, check, check, check.

1:12:00.9 MH: I was like, perfect.

1:12:03.0 VK: You’re in the right head space if you’re… Yeah.

1:12:05.3 MH: Everything else. I’ll do it.

1:12:06.6 VK: So what are some of the things that someone could say like, oh I take Coursera courses or I go to conferences. Like what are the things that when you hear it, you like really light up, like you get really excited, ’cause you can tell that they’re very eager and proactive and like really passionate about this industry.

1:12:21.6 YL: Oh yeah, a great tick for me is if people listen to podcasts like, analyst Paul Hour.

1:12:29.4 VK: Oh I’ve heard of that.

1:12:30.5 YL: There you go. Right. Podcast.

1:12:31.6 MH: Please tell us more about…

1:12:33.5 YL: Yeah. That’s what really good thing about. And also people go to conferences such as MeasureCamp Chicago as we are here today. Or if they go other things like, I don’t know, Adobe Summit, they go to super week in Budapest.

1:12:46.7 VK: Nice.

1:12:47.3 YL: So those are the opportunities you can network with people and also grow your industry knowledge. As we are digital and fixed professionals, things change so much and so quickly here, so I need to really absorb all the opportunities you have to upskill yourself.

1:13:02.6 MH: I have noticed, I wonder if your experienced, you’ve seen this at all, is there are some people who are like not as outgoing or don’t learn in the same ways. And so like I’ve always tried to leave open sort of like, okay, well maybe you don’t wanna go to a conference ’cause that’s not your style or like you’re a senior, kind of more introverted or whatever. But like do talk about the ways that you do that. But yeah, like people read books or take courses or collaborate on like projects with others or take on little projects. Like those are the things I often look forward to.

1:13:35.0 YL: Yeah 100%. Yeah. And you mentioned about the blog before, right? And also even the traditional media, like read a book. We still refer to Web Analytics 2.0 that’s 10 plus years, but still the Bible in the industry, right? So if that person say, yep, I read books and I try to upscale myself through that channel, that’s totally fine.

1:13:53.5 MH: Yeah. Yeah.

1:13:54.8 VK: Yeah, or if they get fired up on Measure Slack, that’s another good one.

1:14:02.3 MH: Being participating in communities like that is really helpful.

1:14:03.5 VK: Yeah. I like that.

1:14:05.9 YL: And also depends on your industry knowledge, right?

1:14:07.5 VK: Sure.

1:14:09.2 YL: For instance, if you are more towards Google Analytics, perhaps you read more about that or you go through Google trainings or if you use Adobe products, you go to Experience League or you use Adobe training materials on the website. So those are great examples candidates can show their desire to learn.

1:14:25.3 VK: I like that. I like the way that, ’cause there’s like… And to your point Michael, there’s like something for everyone, but like show us you’re in it, right? Like what’s your thing? And so yeah, it’s a good question. I might pick that one up permanently as well.

1:14:37.9 MH: I remember ’cause when I started out I was like, well I want everyone to be like me. And then as time went on it was like, well Michael, unfortunately that’s just not gonna happen. So maybe you should be open to other perspectives.

1:14:48.2 VK: Yeah, that’s good.

1:14:49.7 YL: And the other thing we didn’t talk about is social media as well, right?

1:14:52.3 MH: Oh yeah.

1:14:54.3 YL: So for instance, if you follow people on Twitter/X, or if I see the candidate has mutual connections in the industry, so you can see how many connections they have on LinkedIn, for example. Yeah. How many of those are mutual connections that you know really well in the industry? So that can be also a good indicator, not necessarily a question you ask during the interview process. But it’s a great indicator that this candidate is eager to learn, which is what I looked for the most.

1:15:21.5 VK: Love it. Awesome.

1:15:24.5 MH: Oh, those were so good. Which one do you think you’re gonna steal when running your next interview?

1:15:29.0 VK: If it wasn’t obvious, it’s absolutely gonna be the Halloween question. I think that that’s like a great way to open it up.

1:15:33.2 MH: I know. It was really good. All right, well we had so much fun asking these questions, but we also had a great time doing the live show recap at the happy hour. So we’ll transition over to that.

1:15:44.5 MH: Hi everybody. Welcome. It’s the analytics Power Hour.

[applause]

1:15:50.0 MH: This is MeasureCamp Chicago. Thank you so much for having us. I wanna introduce you to my co-host. Moe Kiss, all the way from Australia, right?

[applause]

1:16:03.3 MH: And Tim Wilson, all the way from Columbus, Ohio.

[applause]

1:16:07.7 MH: Julie Hoyer from Cleveland, which rocks.

[applause]

1:16:11.6 MH: Val Kroll from right here in Chicago.

[applause]

1:16:16.5 MH: And I’m Michael Helbling. Alright, we also wanna give a here shout out to also all of the sponsors that made today possible. That is Tealium, Amplitude, [1:16:27.3] ____. Of course, Ken Riverside and the whole Four For productions crew, doing great things for our podcast.

1:16:37.3 MH: Alright, we just wanna share a couple of thoughts from today. We had a great time hanging out everybody, but what were some of the highlights of today for all of you?

1:16:47.0 Speaker 22: Highlight for today, I mean, I didn’t get to go to as many sessions, I would have. Actually, one of the highlights is like the needing to in your hands as to which session to go to, ’cause every single slot had really tough choices, but I did go to John Luvitz’s custom GPT, which I’ve seen him talk about it. I’m intrigued with what he’s done. It was fun, kind of engaging, building a custom GPT on the fly, so that’s gotten me that much closer to actually trying that out. And then I’ll say… Because Josh Silverbauer, I got your last name right, didn’t I? I just had one of those moments and I’m like, shit, did I just…

[laughter]

1:17:26.1 S2: The parody song writing about analytics, which was like.

[applause]

1:17:30.0 S2: 30-minutes and we had more songs than we could review to go through, so that was like to me, it felt like the spirit of like an afternoon that needs to be an afternoon session forward, so that was another great one.

1:17:43.0 MH: Nice.

1:17:45.1 VK: That’s a good one. Fun.

1:17:48.5 VK: [1:17:48.6] ____ go down the road, I guess. Alright, so I guess…

1:17:50.8 TW: Because Michael really, really guiding the flow of the…

[laughter]
[overlapping conversation]

1:17:55.1 MH: I did my job.

[laughter]
[overlapping conversation]

1:18:00.2 VK: So I went to a couple of sessions. One, I think he’s still your Alexia session on third party cookie strategy. Just kidding, I was like, your closing slide. So no, that wasn’t his actual talk. It was server side, the good, bad, the ugly, and I’ve never seen a presentation that kinda walked through all the different players and the pros and the cons, and it led to a really good discussion, so kudos on that one. And there was another session that I didn’t go to, but I ended up talking to multiple people about…

1:18:25.7 MH: Are we going to serve side tagging on the analyticshour.io site or you’re running with that now?

1:18:30.1 VK: Yeah, yeah, yeah. It’s on my to-do list.

1:18:30.2 MH: Cool. Awesome.

1:18:31.0 VK: So to be little, I learned everything I need to know in your session, so I’ll set.

1:18:34.6 MH: Good.

1:18:35.9 VK: Bing, bang, boom. So I didn’t actually go to this one. It was by Florent doing vendor evaluation without losing your head, and there was a pro tip in that one that I thought was really cool. We’re all familiar with RACI, responsible, accountable, consulted, informed, but he added a B to the top for budget and to be thinking about the person who sets the budget. And I was like, That’s fucking gold. So, I can’t wait to do that.

1:18:55.7 Speaker 23: Did you go do it.

1:18:57.5 VK: I did… I was doing Mike session at the time, so.

1:19:00.2 MH: But you have…

1:19:00.9 MK: Where did you get the protest?

1:19:01.8 VK: Yeah, I got a hot tip from your wife.

[laughter]

1:19:08.4 MH: Or those…

[overlapping conversation]

1:19:11.8 VK: It was good. I was like…

[overlapping conversation]

1:19:13.6 MH: There’s a lot going through here that I should say that probably does not need to be on the mic.

1:19:18.2 VK: Julie almost did a session today, I don’t know if you guys, but the board…

1:19:20.5 MH: Thank you to everyone who filled up the boards.

[laughter]

1:19:23.5 VK: If the board didn’t get filled up by the end of the second session, she has the card to prove it, she’s pulling it out, it was gonna be called…

1:19:31.1 JH: Married Tim Wilson for 30 years, ask me anything.

[laughter]

1:19:36.2 TW: I would like to point out…

[applause]

1:19:37.6 TW: I’ll go ahead and give you the feedback now.

[applause]

1:19:40.7 TW: Honey, we’re recording this, you’re not on the mic, so…

1:19:44.0 MH: Married to Wilson for 30 years, ask her anything.

[overlapping conversation]

1:19:47.7 VK: So the topic was, I’ve been married to Tim Wilson for 30 years, ask me anything. And so, in the description was, if you know, you know.

[laughter]

1:19:57.7 TW: Next year it might be, well, I was married to Tim for 30 years.

[laughter]

1:20:01.6 MK: Oh my God. So good. So good. So for me… Look, I have a really bad habit. I have been to many, many Measure Camps. Actually, I hop on the one in city, there’s as a whole crew of us organizing it coming up.

1:20:14.1 MH: No sales pitches.

[laughter]

1:20:19.1 MK: We do events. Anyway, I love measure camp, but I actually just like, this is kind of why I’m part of the podcast, love hanging out and not always going to sessions. You will normally find me just hitting people up, mainly asking for career advice or hitting people up with my work problems, but to be honest, just the nicest bit is, it felt like a reunion. There are so many people far and wide that I have met across the industry or spoken to and never met, and it has honestly just been incredible. And as someone who has been to lots of MeasureCamps Chicago’s first year, shit hot. You guys nailed it. Such a great vibe.

[applause]

1:21:00.2 MK: So yeah, just loved all the breakout sessions and by tabs and drinks, and then we can really talk about the good stuff.

[laughter]

1:21:07.6 Speaker 24: Can you translate that…

[overlapping conversation]

1:21:11.0 MK: Sorry. Shit hot is good in Aussie. Like, real good.

[laughter]
[overlapping conversation]

1:21:17.1 VK: Yeah, yeah, we flip it.

1:21:18.8 MH: Yeah.

1:21:18.8 MK: Okay, good.

[laughter]

1:21:21.3 PM: Alright, so can you guys hear me okay [1:21:22.7] ____.

1:21:22.8 MH: Yeah.

1:21:23.5 PM: Okay. So I got to go to two sessions and between our recording, which I’m really happy with the ones I got to attend. There were so many I wanted to try to get to. The first one I went to was human-centered, designed for AI with Gina Grant, and it was so good. I feel like we talk about ethics and AI a lot and the biases that we know are there, but I felt like this presentation was so good at giving a tactical way of trying to get there, we always talk about the outcome of being ethical and not bias and understanding, and making sure we use it responsibly, and starting with the human-centered design, it was understand, IDA, synthesized, prototype, implement, and it was all about reflecting on your assumptions ahead of time, saying, what was the outcome you wanted, who do you need to design it for and think of the people that you didn’t say you wanted to design it for, and would they still be involved, talking about how it’s an iterative process. And I just thought the examples that were given too were so great.

1:22:16.0 PM: There were projects that she did with students, some of them were really cool apps about for lawyers and things, and it was just really inspiring what they were able to do with AI and the way that they actually approached thinking through designing these AI tools and agents and things like that. So I thought it was a really, really great and inspiring session. And then the other one that I was able to go to and loved was the emperor has no clothes on, which I…

1:22:43.1 VK: I wanna do that way.

1:22:45.4 PM: It was wonderful. It’s one of those talks too, I felt like you have that wiggling feeling at the back of your head when you talk about those topics, and then when she started, it was like, Oh yes, that’s exactly how I would describe it. It’s kind of all this wishy-washy and nothing’s really clear, but it’s really important. And it seems so obvious now, but when she said, cookies don’t equal tracking, it was very much like a light bulb moment. I’m like, I can’t wait to use. That is so simple. So good. So that was the other one that I loved.

1:23:13.5 TW: You took notes?

1:23:14.4 PM: I did.

1:23:15.2 TW: Did you take them on your phone?

1:23:15.5 PM: Yeah.

1:23:16.1 TW: Fucking millennials. How do you do that?

[laughter]

1:23:18.9 PM: I don’t know. I listened to it and typed.

1:23:21.7 TW: Yeah.

[laughter]

1:23:23.3 MH: I have two things.

1:23:24.8 TW: But Mike…

1:23:26.2 MH: Two things. Hold your fire Tim.

1:23:28.2 TW: Okay.

1:23:28.3 MH: There’s many generations for you to be mad at. So first, I got to attend Moe’s session today, which I really enjoyed, and especially there was a section there, were Moe talked about how important it is to be delivered feedback and delivered directly as a people leader, and I thought that was just a really great and underrated point. And so I really appreciated hearing that. The other thing I will say is, it’s about the people in this room and kind of tagging on to what you said, Moe. There’s so many people in this room that I’ve met before. And so many people I met today for the first time, but I’ve interacted with on Measure Slack or on Twitter or LinkedIn or whatever. And I don’t know if other industries have this kind of stuff, but it’s too late, I’m not switching, I’m staying in this industry. It’s so much fun to be part of communities like this and get a chance to do that. And I’m mentally grateful and thank you and MeasureCamp Chicago for putting such an amazing event together where we could all be here and do that.

1:24:29.3 MH: And it was so cool to see… I, so didn’t expect to see so many people in so many different places. Come to Chicago, I guess it’s an easy flight, so we’ll see you again here next year.

[applause]

1:24:42.9 MH: And of course, no show would be complete without a huge thank you to Josh Crowhurst, our producer, who’s in Hong Kong, but we’ll get him here eventually and thank him for all he does for the show.

1:24:55.4 VK: And all he’s about to do for all…

1:24:57.0 MH: Yeah. That’s right.

[overlapping conversation]

1:25:01.7 MH: No shortage of good outtakes. And of course, I think I speak for all of my co-hosts when I tell all of you in Chicago, eat deep dish pizza, keep analyzing.

[applause]

1:25:16.0 Announcer: Thanks for listening. Let’s keep the conversation going with their comments, suggestions and questions on Twitter at Analytics Hour on the web, at analyticshour.io, our LinkedIn group and the Measure Chat Slack group. Music for the podcast by Josh Crowhurst.

1:25:33.0 Charles Barkley: So smart guys want to fit in, so they made up a term called Analytic. Analytics don’t work.

1:25:40.5 Michael Wilbon: Do the analytics say, Go For No matter who’s going for it, so if you and I want to feel the analytics that go for, it’s the stupidest laziest, lamest thing I’ve ever heard for reasoning in competition.

[background conversation]

1:25:57.6 MH: Enjoy the rest of Measure Camp and try to share accurate information.

[laughter]
[overlapping conversation]
[music]

1:26:05.1 TW: Do we have time for me to grab some water?

1:26:08.7 MH: Sure.

1:26:09.3 TW: Are you sure?

1:26:09.4 VK: Yeah, but why don’t I get one of the girls to get it for you.

1:26:10.5 TW: Okay. Thank you.

[background conversation]

1:26:37.4 TW: May I have your attention? Thank you. I love attention. All right. We’re just going to do a really quick thing and thank everybody for holding on through all the little hiccups we’ve had with the audio. It’s totally normal for podcast to do this. And…

[overlapping conversation]

1:26:55.9 TW: If everybody could come back tomorrow same time, we’ll have this…

1:26:58.5 MH: Yeah. We’ll redo this whole thing.

[music]
[applause]

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