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0:00:06.2 Announcer: Welcome to the Analytics Power Hour, analytics topics covered conversationally and sometimes with explicit language. Here are your hosts, Moe, Michael, and Tim.

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0:00:22.0 Michael Helbling: Hey, everyone. It’s the Analytics Power Hour and this is Episode 209. What a year, huh? The Analytics Power Hour is wrapping up 2022 and you know by now we always do the last episode of the year as the year in review. What were the highlights? Our favorite shows, the biggest trends facing our industry and what’s coming up from our vantage point as the number one explicit analytics podcast? So, let’s fucking go. Moe and Tim, welcome.

0:00:52.2 Moe Kiss: Hey, nice to see you, hear you.

0:00:53.2 Tim Wilson: Hey. This was Moe’s… I always gotta bring up, this was Moe’s least favorite episode until she started recording it, and now this is her favourite episode.

0:01:01.1 MH: What? Now come on, this is long past, long past…

0:01:04.0 MK: It’s not my favorite. Let’s be clear. We will get to my favorite.

0:01:08.3 TW: Okay. [chuckle]

0:01:08.3 MH: We all look forward to this episode because we also get to be joined by Josh Crowhurst. Welcome, Josh.

0:01:15.4 Josh Crowhurst: Hey, happy holidays.

0:01:19.9 MH: So excellent. So let’s kick it off maybe with some general notes. I mean, over the course of this year, we did experience some pretty cool things. We went over a million downloads, not according to the IAB standards. So we’re resetting to now go chase a million there because IAB dedupes some of the data, I would imagine. But our syndicator now added that this year so we can now apply an IAB standard, ’cause we know that’s so legit.

0:01:53.2 TW: Well, but it is. I mean, there’s a little bit of a microcosm there. Like we’ve been doing the podcast for long enough that when our hosts did their recalculating, it doesn’t go all the way back to the beginning. So, there is this kind of funny experience of like, “We don’t really know and it depends on how you count.” Like, I don’t know, there’s a whole sort of meta-pondering on how many downloads have you had? It’s like, “Well, step into my whiteboard and let me start explaining to you the complexities of counting a number like that.”

0:02:28.5 MK: Am I gonna be like the antithesis of data analyst by being like, “It’s close enough. Like, we don’t need perfection.”

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0:02:37.7 MH: I’m right there with you. I’m right there with you. You know, this year also saw us return to a live venue at Marketing Analytics Summit this past summer? That was outstanding to see people in person again.

0:02:52.0 MK: That was good fun.

0:02:53.8 TW: Although we missed Josh in North America by about two weeks.

0:02:57.4 MH: That’s true, he did.

0:03:00.5 MK: And I got COVID. So, that also sucked.

0:03:02.5 MH: Oh, yeah.

0:03:03.2 TW: Oh, oh, that’s right. Yeah.

0:03:06.6 MK: From Vegas and all of the people, yes. Yeah, it was…

0:03:07.8 MH: Luckily, Tim and I were still holding strong from, I think, getting super weak. [chuckle] So our vaccines plus natural immunity, I think, kept us both from getting it in Las Vegas. Anyway.

0:03:23.6 TW: And I would not want to wish this on you, Moe, but there was like a 48-hour turnaround for me flying back from Vegas and getting on a plane to fly to Europe for two months. So…

0:03:33.7 MK: Oh, I remember.

0:03:34.9 TW: If one of us was gonna get it in Vegas…

0:03:37.2 MK: You’re glad it wasn’t you. [chuckle]

0:03:38.8 TW: I wouldn’t always say…

0:03:41.1 MH: What? [chuckle]

0:03:41.1 TW: Better you than me. [chuckle]

0:03:47.3 MH: All right. Well, that’s very specific. Oh, anyway…

0:03:53.2 MK: It’s cool. I just missed my family holiday and seeing my relatives I hadn’t seen in years and years and years. It’s all good, Tim.

0:04:00.4 TW: I thought you had a partial recovery. Yeah. You didn’t completely miss everything. Yeah. Okay.

0:04:04.5 MK: Anyway.

0:04:05.6 MH: It’s never a good moment, that’s for sure. But yeah, we’ll…

0:04:10.2 MK: No.

0:04:11.2 MH: Josh, have you…

0:04:11.3 TW: Have you gotten?

0:04:11.4 MH: You’ve gone through it too, right?

0:04:13.0 TW: Have you gotten COVID?

0:04:13.9 MH: Yeah, Josh has.

0:04:15.5 JC: Yeah. I just got COVID like two weeks ago. Yeah. It really knocked me on my butt, actually.

0:04:21.4 MH: All right. Well…

0:04:22.6 JC: It’s hopefully good once it’s a bit easier to travel in Hong Kong. Hopefully, I can start attending some conferences early next year once I’ve… Still on my natural immunity.

0:04:31.6 MH: Yeah. Well, it does apparently wear off over time, but that’s where the boosters and whatnot come in, I suppose. All right. Let’s stop talking about COVID. Let’s talk about episodes, shows that we did this year that we really liked. Because I think there was… I mean, we had some amazing guests this year. It’s pretty incredible. Honestly, some of the people we had on the show this year… I don’t know. Does anybody wanna start with an episode that really stood out to them?

0:04:57.4 MK: Absolutely. I’m going to…

0:05:00.6 TW: Go for it.

0:05:01.3 MK: Tim actually asked me before the show if I had my favorite picked out. And every year, I sit on the fence and I have like five favorites. But I was actually having breakfast with someone this morning and they quoted this show, which given that the International Women’s Day episode is so early in the year, I was very impressed that they could remember any quotes from Stacey Vanek Smith. But definitely, Machiavelli for International Women’s Day with Stacey Vanek Smith was my… It could potentially be my career highlight. Like I actually think personally about that episode a lot. So, if we had to do an all-time favorite, I’d be a basket case. But I think just the amount of practical advice in that episode really, really helped me. And I know lots of other women have reached out and had the same experience listening to it.

0:05:52.7 TW: And I hope that guys listen to it as well. I will say that’s one from the book, and then listening to her as well. I have found myself… I feel like it’s just kind of helping with some additional empathy ’cause there were some very specific things where she’s like, “Yeah, until the system changes, this is going to absolutely suck.” And so from a, I mean, I’ll say the ally word, but it’s like I have had colleagues who have been experiencing exactly the things that she listed in the book. Some of them, it’s been… I have bought the book for them. I have suggested it. I haven’t been… I’ve tried to not mansplain to them what they’re going through. But I mean, the book and then the discussion with her, which was definitely one of my favorite episodes, and I wasn’t on it. So it was you, Moe, and Julie Hoyer, and yeah, it was… That’s a top one on my list.

0:06:58.3 MH: Nice. Who else?

0:07:00.7 MK: What about you, Helbs?

0:07:02.3 MH: You know, I was going through the list too and coming up with sort of the ones I really liked. And I won’t take one of the ones… I think, Tim, you and I had a crossover, so I won’t take that one. But I will talk about the episode we did with John Wallace on media measurement. That episode has been very useful this year, because there’s been a lot of conversations and we’ve been doing a lot of work with a lot of companies on trying to progress attribution and trying to handle some of the things going on and being able to give better guidance to, “Okay, here’s how we’re going to actually do this,” or “Here’s a way or here’s someone you can partner with.” So it’s been very, very helpful. That episode has come up multiple times for me. So, like in terms of utility, and it was fun to talk to him, but I think in terms of utility, that one was very useful to me this year. And honestly, I feel like it also helps sort of dispel some of the… I don’t know the right word for it. Like, I tend to not be like… Well, I’ve never been super into advertising analytics, generally. And so this helped me have sort of a way to talk about it that I didn’t feel weird about, ’cause attribution or multi-touch attribution and stuff like that, the way it’s historically been done where there’s sort of always a little bit of a thumb on the scale type of thing going on.

0:08:27.5 MH: I’ve always felt real awkward about that historically and I’ve not liked it. And I don’t like walking into things and being like, “Yeah, we’re lying to you with this data, but just believe us.” [chuckle] It’s never been something I enjoy.

0:08:40.3 MK: I would say that’s a fairly big leap, but look, I’m lucky enough that I’ve also had the opportunity to sit with John and discuss some of the thoughts in his mind just at a bar, which is my favorite way to discuss work topics.

0:08:51.6 TW: I do believe you called me after walking out of a bar…

0:08:56.5 MK: I did.

0:08:57.4 TW: After having had a few drinks with John…

0:09:00.9 MK: I did.

0:09:01.0 TW: Which was one of the more entertaining phone calls I’ve gotten.

0:09:03.1 MK: Yes, because it’s those people that when you discuss stuff and you’re just like… It just takes you one level deeper and you know that the person you’re speaking to is infinitely smarter than you, but at the same token, you never feel that way during the conversation. He’s really good at explaining these really technical concepts. Like, I’ve seen him internally do it with a few of our marketers and you’re like, he’s so good at distilling these things down into a way that people can understand it, which yeah, that’s definitely in my top five for this year as well.

0:09:32.9 TW: I’m conflicted because I literally never want to actually talk about or think about that stuff and there’s so much sleaze in the space of advertising, that it’s… I actually… Same thing, I loved the discussion and I definitely know there are things that are now deeply embedded that have helped me think about and talk about that whole space and even approach it with clients at the same time. I’m like, these are kind of the questions. It’s such an uphill battle with so much of an industry machine stacked to misbehave on so many dimensions. And not the measurement piece, but it’s like you’re just wading into a morass of awfulness and saying, “I’ve got a better yardstick,” and you’re like, “I’m getting attacked with a flame thrower, I’m sinking in the mud.”

0:10:32.9 MK: There’s also just very strong opinions in this space, and I think that’s the reason that some people get a bit intimidated by it, is like… And even marketers have strong opinions about measurement.

0:10:47.9 TW: Opinions stated as fact.

0:10:49.3 MK: Yeah it’s that too.

0:10:53.0 TW: I will probably put myself, I probably should put myself top on that list. Josh, you got one?

0:10:58.7 JC: Yeah, so actually, really I thought we had such an awesome year ’cause when I was looking over the episodes, I was like, “Oh my God, this is so hard.” There’s so many that I loved and so many that I want to talk about. But actually, probably the top one for me this year was on owning versus helping. So, actually a guest list episode, which I totally loved it because I thought we took a topic and covered it in really good depth from multiple angles and it’s something that I think I had been observing in my own company. When I think about some of the people who are really, really effective and some of the people I most like to work with, that’s actually what they demonstrate in the exhibit. And so, I think it just took this concept that I’d been observing and it helped me think about it in more concrete terms. And I really walked away saying, “Yeah, I learned something from this episode, something that can help me in my career.” And ultimately, that’s what I love about this show. That’s why I started listening in the first place. So, that episode was like… I thought it was just spot on, so yeah, good job, guys. [chuckle]

0:12:09.3 MK: And the funny thing I love about episodes like that is sometimes when we’re talking about them, we’re like, “Oh, is this really a show?” And that one in particular, I had so many people reach out to chat to me about it afterwards. And it is those things that you really… Those thoughts that you struggle with internally. And once you talk it through, you’re like, “Oh, there’s so much value in discussing this stuff in our industry, even though it’s not specifically about number crunching or data or whatever.” Yeah, I love that one too.

0:12:42.1 TW: We actually used that article, which, Moe, you had found and wound up doing an internal discussion with an internal analytics community at Search Discovery. And then we had as a bonus, people could if they wanted to listen to the show. So, I wound up actually listening to the show before. And I was like, “Oh, we took that article,” and I think we had a pretty useful and more in-depth discussion around it, I will say, and I was pretty quiet during the internal discussion ’cause I’m like, I kind of said… I’ve had my opportunity to hash this out. I would say that’s a topic that even people who read that article or the first part of it, ’cause it was clipped behind a paywall, but there was enough to get it. People still really struggle with that. They struggle with even the idea of it, as analysts. And these were analysts at kind of a range of levels. And I’ll say it was a little like, “Oh, I kind of want some of these people to listen to it again and then I wanna have a one-on-one ’cause they’re still missing it.”

0:13:47.8 MK: Oh, that’s interesting.

0:13:50.0 MH: What I remember from that show is that we recorded that show right before that quiet quitting thing trended. And I was like, “Oh, darn it. We didn’t work that in.” It was like a couple of weeks after we recorded it or something, everybody started talking about that. I was like, “Oh, that’s like a perfect… ”

0:14:02.2 JC: Yeah, totally.

0:14:04.6 MH: I enjoyed that one as well. That one was one of the ones that surprised me where I had a lot more to say about it than I originally thought. So, that was fun. But yeah.

0:14:15.5 TW: I’ll throw in the talking to Prukalpa Sankar, the Modern Data Culture Stack. Just she’s… One, I now love her newsletter and I was reading it before, and I think it was… Was it last year that we used her year in review to actually track down a bunch of people? She has been the source, and we told her that. But just this idea that while we were having that discussion, she said something about data enablement and we said, “Wait a minute, what?” And we wound up having this really interesting idea of, what does that mean and how would it work? And then it was actually cool. I think it had been maybe floating around in her mind, but it came up in one of her newsletters, officially trying to work out the thinking on it.

0:15:06.1 TW: So, that was one where I’m like, I think we helped the guest formulate some thoughts as well. But her… For running a technology company, which I feel like we’re always a little nervous if we have somebody who’s a product manager or running a technology, a platform, there’s a risk that it’s… We’re always nervous that it’s going to become a sales pitch. I don’t think it ever has. She is so focused on the people and the process, you almost don’t even know that she’s trying to solve a problem with her company and with her platform. But I don’t know, she just seemed like one of those people who I could kind of listen to her, I’d kind of just throw a topic at her and then listen to her kind of work out and think it through, and there would be some really useful things that came out of her brain.

0:16:02.2 MK: Totally. And she’s one of those people that thinks very deeply about the topic that she’s discussing. And so it’s a skill that… Love to be able to bottle up. [chuckle] But to be able to get to that level of like, not just what everyone else is saying in the industry, but like her own thoughts in addition to that, I think she does that in an incredible way, which is why we definitely used her as a jumping board for a lot of other episodes throughout the year as well.

0:16:34.1 MH: Yeah. She also really… Like, a lot of times, I’ll ask a question of some of our guests, sort of ask like, why do you do this this way or what’s your motivation or what have you learned? And I remember asking her one of those questions, I think it was sort of about how she gets into her team’s effectiveness or something like that. I can’t remember exactly what, but she was… Already thought through it all. Like, she’d already thought through and considered, “This is exactly how we attack it. Boom, boom, boom, boom, boom. This is why we do it that way.” And I was just like, “Wow.” I was so… I mean, I was just so impressed with her…

0:17:07.5 TW: I’m wondering now that you say that, if it was like she talked about the data cribbing sessions and it was like, man, that sounds like it would…

0:17:14.0 MH: Yes, yes, I think that’s…

0:17:14.9 TW: Turn into a Beach Fest. And she was like, “Oh no, here’s how we do it. Boom, boom, boom, everybody… Like, get a better understanding.” And I was like…

0:17:22.2 MH: That’s what it was. I would just… That was just… Yeah. How do people do that? [chuckle] She’s obviously such a great thinker and so smart and like… It’s incredible. Anyways, I really liked that episode as well. What’s another one of your favorites?

0:17:42.1 TW: Well, I was gonna echo that going through the list of everything this year was like, boy, it was a…

0:17:48.0 MH: We did all right.

0:17:49.6 TW: What do you call it? Something of riches, a… Not a tragedy of riches. I’m blanking on the…

0:17:57.2 JC: Embarrassment, is it…

0:17:57.3 TW: Whatever. Embarrassment of riches. There we go. That sounds right.

0:18:00.2 MH: A banner year. [chuckle]

0:18:04.1 MK: I don’t think I’ve heard that expression before.

0:18:04.1 MH: An embarrassment of riches? There’s probably an Australian version of it. [chuckle]

0:18:10.2 TW: We’ll have to localize the…

0:18:10.9 MK: Timmy, you’re already Googling it?

0:18:11.2 TW: Of course I am. [chuckle] Yeah. An over-abundance of something or too much of a good thing.

0:18:19.3 MK: I don’t think I’d describe it that way, but sure.

0:18:21.8 TW: Oh, well, it came from a…

0:18:24.4 MK: I don’t know.

0:18:25.8 MH: It’s just enough.

0:18:28.2 TW: 1738 translation of a French play, which I’m not going to pronounce the name of the French play.

0:18:32.5 JC: Maybe something lost in translation there. Can I shout another episode?

0:18:39.5 MH: Yeah, do it.

0:18:42.5 JC: So, I just wanted to mention this one just ’cause it was like pure joy. But number 197, Did the Dungeon Master Just Pass the Turing Test with Hillary Mason? I love this episode just… I guess first off because I’m a big nerd, so it’s right up my alley. But yeah, I just thought that it’s really cool what her company is doing, what they’re trying to build, the generative AI, natural language-based role-playing game. To me, that just makes me so happy to think someone is tackling such an ambitious problem like that. But I guess the other thing is, we hear a lot of stories about the harmful effects of AI and all of the negative sides of that. And then just to hear someone come on and talk about something that is just really cool and almost, I guess, wholesome, it was refreshing. It was really refreshing to hear. And also just cool to hear talking about… It’s a big problem, and how they’re going about solving it, how they’re setting up their team, what tools they’re using, how they’re approaching it from a technical standpoint… I was like, this is just so fascinating. So I love that episode. I’m really excited to see how that turns out. I’m definitely gonna be playing that game when it’s released. I think they’re still doing it…

0:20:01.4 TW: I think watching Michael just completely just dive into the various minutia of RPGs and…

0:20:13.2 MH: Hey, I can say from our Measure Slack Gaming channel group, there’s a lot of people that are into D&D and that sort of thing.

0:20:21.1 JC: Yeah, that Venn diagram probably has a big overlap. [laughter]

0:20:24.3 MH: Yeah, Hidden Door opened up their Discord to fans and things like that. So I’m on their Discord and they do Q&As and talk about what they’re developing. And they’re getting ready to do some sort of alpha types of stuff soon. I haven’t had time to look into it recently, but it’s pretty cool what they’re doing. And that was a very cool episode.

0:20:45.1 JC: Yeah.

0:20:48.0 MH: The biggest thing I took away from that episode was just how much wisdom Hilary Mason had developed in the way that she was approaching all these things. So many ways, it’s like deeds done, like seeing the problems, seeing the solutions, work through the challenges. And that was the thing that really stood out to me as much as the subject matter was very interesting too, but it was the wise-ness that she was approaching the whole concept with just really stood out to me.

0:21:18.7 MK: And that was the…

0:21:19.9 MH: That was a good… That was a fun show.

0:21:21.4 MK: The thing that I didn’t expect us to touch on is she did actually talk a lot about how to be responsible with data and ethics and AI, all that sort of stuff, which to be honest, number one, it’s gonna sound really corny, but I would almost describe her perspective on that as beautiful. The way she talked about it, I just found incredibly impressive and their approach. But it’s definitely not an area I expected us to even get into or that it would be as relevant for her space maybe as it is. And that was like a really interesting angle of the show of that particular episode for me.

0:22:00.4 MH: Yeah. I mean, it stood out to other people. We just got an email from a big CEO the other day mentioning that episode specifically.

0:22:05.6 MK: Oh, really?

0:22:08.9 TW: Yeah.

0:22:09.8 MH: It definitely stands out to people for sure, that that was not just you probably. Anyway, Moe, what’s another favorite from yours, from your list?

0:22:18.8 MK: Big shock. Like this year, I’ve been totally obsessed with this whole data products thing. Well, I’ve been obsessed with it, I would say for over a year, but this year definitely was like me really kind of doubling down in that space and learning as much as I could. And it was really nice, just I’ve been catching up with Eric from Stitch Fix quite a lot, just about my own, I guess, understanding of the space and kind of where I’m at and all that sort of thing. So it was really nice to have him on the show and be able to share that with our listeners as well because, yeah, it’s… For anyone that has heard me speak this year, that’s the topic that I’ve been kind of delving into. And so it was just nice to be able to share that with everyone and explain kind of where my head’s at and how I formed some of my thinking. And Eric’s obviously been a big part of that.

0:23:02.1 MH: Nice. That was also one of the ones on my list as well. So I’m glad you brought it up. What was intriguing to me from that episode was the extent to which I started to realize that a lot of the work I do in consulting is actually creating data products. And I don’t approach it like I’m creating data products. And so that was actually a really big moment to think about. And as I go into next year, one of the things I’m really thinking about a lot is how do I start to actually recognize the data products we create as data products themselves and not sort of like an output or an artifact or a deliverable, but actually like a thing that we’re producing? And then think about the production of it from a data product production perspective and include the right roles and the right things in the production. Because it’s like, well, the analysis piece or the science piece or whatever we’re doing from the data side of it, that’s one piece, but there’s the application itself potentially or the visualization or whatever the different roles that need to be involved. And so being a little more all-inclusive in the way we design them.

0:24:08.8 MH: And I’m excited about it because I think it’s gonna do a couple things. I think it’s gonna help us actually talk to our clients about what is going on with their data with a little bit better like understandability almost in a way. And then I also think it’ll help people value the things we’re doing sometimes in a better way. Because it’s like this is a thing we’re creating. It’s a tangible thing. So yeah, that episode was a really big one for me. I knew about data products before, but I’d never really sat down and thought about what is or what isn’t a data product to me. So that was kind of cool.

0:24:42.0 TW: Well, but I think that was also an episode where there’s kind of like distinct topics, which I worry about. Our industry is really good at taking… Somebody comes up with a cool phrase and…

0:24:56.7 MH: Oh yeah.

0:24:58.4 TW: Everybody like just… There are groups that say, “Ah, I’m gonna take that over.”

0:25:05.3 MK: “Butcher this. ”

0:25:05.4 TW: Right. Yeah. And so like data as a product, running a data team, like a product team, data products, a dashboard or some derivative of that. And we chatted with him like… And Eric was another one who was like super thoughtful. He was like, “Yeah.” And I think right before we recorded, he’d actually had a, I think in one of his posts, one of his articles was kind of saying, “Yeah, these are different things. This is… Let’s not treat one set of rules as the be-all end-all solution for everything.” But yeah, another thoughtful guy.

0:25:43.6 MK: I think… Yeah, for me personally, the… I guess the… I hate saying the word “journey”, but sometimes I just can’t find something to use in its place. The path I’ve been on, I don’t know, whatever, insert corny word that should probably be on a Bachelor type show, it’s also helped me realize how we better use the knowledge that other specialties have. So when we talk about data products, like I think what we’ve been doing perhaps in the industry is data folks are building things and maybe without the expertise of whether it’s someone from UX, whether it’s like an understanding of how product strategy and roadmaps get built. And we’ve kind of just like plodded along and tried to figure it out on our own. And for me, it’s actually been really reassuring in this space to be able to look and go, “Hang on a minute. We can actually leverage our colleagues over here that know way more about this than us. What either skills can we learn from them or how do we get more of their resources and time so that the things that we build can be more mature and more fit for purpose and ultimately avoid us making that mistake of building shit that doesn’t get used?” So… Yeah.

0:27:02.5 TW: But that is specifically the data products, right? ‘Cause there was also a discussion about treating your data team like a product team, which is…

0:27:13.8 MK: Yes, yes.

0:27:14.9 TW: So it’s like the Venn diagram of the… I mean, I don’t know, that was… Yeah, we don’t need to rehash that episode. I still worry that that basic… You put the word data and the word product, you put it together and you can run into people who are talking completely past each other. I think it even came up with like product analytics, right? Like that, “Oh, data for my product, product analytics,” and that has kind of… As there have been product analytics companies that have gotten heavy funding and lots of marketing and loud mouthpieces out there and guaranteed that group will be people who say, “Yes, it’s like this data is product.” Like, no, this is what you’re talking about, Moe, is completely different than product analytics. Not that you couldn’t have a product analytics team that is running the product analytics team as a product team. So I don’t know. It’s a fun area. So we’re gonna… We’re just gonna navel gaze for this whole thing or are we gonna shift to industry? I’m not the moderator here, Michael, but…

0:28:20.4 MH: Well, I don’t know, ’cause there’s one episode that’s on three of our lists and we haven’t talked about it. Josh just added it to his list.

0:28:28.8 TW: Are we talking about Mr. C Mastication himself?

0:28:31.9 MH: That is correct, yeah. JD Long. So we did around psychological safety and analytics, which kicked off this year. But yeah, that was a good one. So we could talk about that briefly. I just remember the rubber duck thing that he talked about, rubber duck debugging, I think was like, that’s the coolest, coolest thing I’ve ever heard of.

0:28:56.2 TW: And then I promptly have like… Every developer that I would ask about it would be like, “Yeah, of course, rubber ducking.”

0:29:00.9 MH: Yeah.

0:29:01.4 TW: And I was like, “Oh yeah, okay. Yeah.” Yeah.

0:29:05.7 JC: Yeah totally. I thought but that was a good tip and I thought the cool thing about that show was he had actually a lot of really practical advice about how you foster more psychological safety, like “Do this thing with your team. Don’t do this other thing with your team.” And even like when you’re interacting with other teams that might not be as psychologically safe, there could be like an impedance mismatch. He used that term. I was like, “That’s… I like that. That’s such a good description.” So yeah, another episode that was just really, I think just had a lot of really practical advice. So that was a good one.

0:29:34.8 MH: Well, we could certainly talk about past shows for the whole hour.

0:29:38.6 TW: If we go long enough, there’ll be like one show that’s left out.

0:29:42.3 MH: Yeah.

0:29:42.9 TW: They’ll be like, “Oh wow, they really… That was a real stinker.”

0:29:46.8 MH: The one show that we did, you don’t have to guess, and then don’t tell the guests that we had that they were the only one we didn’t talk about. No, obviously…

[overlapping conversation]

0:29:53.8 JC: Hopefully they don’t listen to this episode.

0:29:56.1 TW: Yeah. [chuckle]

0:29:56.8 MH: But what’s going on in our industry people? Come on. Like this year has been a crazy year for things happening. What’s weird is the last couple of years and sort of like COVID and ITP and GDPR, like they all start merging together and I sort of feel like 2019 to now is all sort of one big year. But there has been a lot happened just in 2022, so if we can remember, we can talk about that a little bit. What were big things going on from your perspectives?

0:30:26.7 TW: I mean, to me, when you mash it together with COVID, I feel like big tech that just kind of crushed it through COVID, just like broke growth records right and left.

0:30:37.9 MH: Yeah.

0:30:39.4 TW: And then 2022 is that was softening and things were crashing, but it also feels like the various governing bodies around the world that had been building cases. I mean, we’re looking at fines in the hundreds of millions for like every big tech, whether it’s under the DPA, GDPR, different areas. And I wanna say it was right at the beginning of the year when Austria was kind of on the forefront of really starting to crack down ’cause at Superweek, there were discussions of like… And I think Zoli had actually gotten, I can’t remember who it was, from an agency in Austria, like kind of a later add to talk through and say, “Where does this all fall?” So I feel like this was a year, although it’s crazy… Like these are hundreds of millions of dollars or tens of millions of dollar fines and I can’t actually list them now.

0:31:37.8 TW: If it wasn’t… It was like, “Oh, there was that one big meta thing.” Like, no, I’ve totally lost count. There have been many. And it’s just happening. And I can’t figure as big as it just now costs to doing business. Like what is it… So that, I guess, axe had been hanging over the head of, “Yeah, we’re gonna get serious about it.” It feels like this was a year where they started cracking down on the really deep pockets. And that makes me wonder if like, okay, so that’s gonna move kinda down market and it’s gonna be equally painful for organizations that still have their heads in the sand.

0:32:19.9 JC: Yeah. Wasn’t it even this year that we had the… There was like some rulings that Google Analytics even was not tech… Was like in breach of GDPR because of how they process the data…

0:32:32.2 TW: Oh, yeah.

0:32:33.8 JC: The companies in the EU.

0:32:35.9 TW: Yeah.

0:32:36.5 JC: So I think that was like early this year or this summer.

0:32:39.1 MH: That was the Austrian one. And then that was followed up, I think, by about four other countries in Europe as well, kind of came to the same conclusion throughout the course of the year.

0:32:48.7 MK: But I think that part of the issue is the interpretability and there are different ways that different companies can interpret the regulations in a specific location. And that gray zone, I think, is so tricky for us all to navigate. Like I think it’s even tricky for lawyers to navigate because there isn’t a lot of precedence. And so I think that what’s been happening this year really just highlights how complex it is and the fact that there isn’t necessarily a right answer, a yes or a no, it does come down to what’s legally defensible, what’s in the best interest of your users? Yeah, I’ve actually, funnily enough, been struggling with a lot of this stuff myself as well internally. And I think before everything got rolled out, I just had this real black and white view and it’s definitely changed this year with a lot of the penalties that have been coming out to some big companies.

0:34:01.4 TW: But I think that’s where that’s been setting the precedent and the companies are looking at it and the lawyers. And I’m not particularly sympathetic for the lawyers. That’s the job. Every contract, even if it’s two pages long, has that… I mean, I’m not disagreeing. It’s like that’s… Yeah.

0:34:24.8 MK: But the reason I do feel for the lawyers is because it’s in a technical domain that they don’t have experience in. Like often you have a lawyer that isn’t experienced in contracts or whatever, but understanding deeply about how cookies and tracking and even data processing works, I actually think that’s really fricking hard. And I think a lot of lawyers…

0:34:49.1 TW: Well, and the regulatory… Even the regulatory bodies, I mean, you’ve got legislators drafting legislation in a US state, in a European organisation. It’s a really complicated space. And it comes back to those fucking ad tech assholes who are like, you’re literally trying to… There’s a degree of like, just… I mean, Stéphane Hamel, it’s like just no consent, no tracking. I kind of appreciate his start.

0:35:24.5 MK: We have discussions, what is consent? Like that is the discussions I have with people about like, when you say marketing consent, what do you mean? Because one person thinks one thing and one person thinks another thing.

0:35:36.2 TW: Well, but even on that, it’s because we’ve got greedy fucks who are analysts, marketers, advertisers who say, “Oh, what do you really mean?” I mean, even… I mean, this is at the risk of… This needing to be edited out. Like, oh my God, like there’s another area that’s way more serious when you’re like, “What is consent?” And it’s pretty simple in a human sexual relationship what consent is. It’s pretty easy.

0:36:06.6 MH: Oh boy.

0:36:08.0 TW: You draw the bar in the most conservative area, and then you get confirmed consent. And so like, it’s not hard. We make it hard because we wanna have the data, we wanna track, we wanna work around the browser limitation, we wanna do the targeting. And we can tell ourselves some bullshit stories about being able to put more relevant messaging in front of you, the consumer who’s gonna appreciate it, but… I mean, so that’s… That is a party at play that is just naturally just… Just we’re wired to think that every cookie we can’t drop and every extra day that that cookie can’t be unexpired is just a personal affront to our ability to generate actionable insights, which I think is a crock of shit.

0:36:53.9 MK: I don’t think everyone thinks that.

0:36:56.6 TW: If you were in a discussion around what does consent really mean, it’s like, well, how about if we drew the line at the, until you have explicitly and proactively agreed to be tracked in all of these ways, I’m not gonna track you at all? People are like, “Okay, fine.”

0:37:11.3 MK: I’m gonna turn this conversation in a slightly different direction ’cause otherwise, Tim and I could just keep going for all time. But one of the really interesting things that I’ve been chatting a lot to people about in more the machine learning space is that the default for a lot of our models has always been full signal. And I am stealing someone else’s language here, which I’m not going to mention where it’s from, but someone else’s language, that the default has been full signal, right? So we have all the attributes we want and we build models off it. And then there’s the next step down, which is like constrained signal. So you have some attributes or some percentage of your user base that’s covered all the way down to no signal, right? And the fact that our mindset probably needs to fundamentally shift about model building, that instead of starting with that full signal model, and then try to work backwards, we should actually start with no signal and then only add where we can. And it was like, this is a concept that has come out of a lot of this privacy stuff and chatting to MLEs about losing data and that freakout of like, actually, maybe this is an opportunity to reset how we think about these things.

0:38:28.0 TW: I love that. I mean, but, but we’ve got the biggest player in the space saying, you’re losing this signal and the word signal, and we’re gonna do conversion modeling for you, and we’re gonna base that on our signals. We’re gonna take the full signal data we have, and we’re gonna model this other stuff for you. Which doesn’t feel right in the limited places where we’ve been able to compare their modeled version to reality. It’s been way off. And I love that is what… But again, like it’s getting people back to the… We have been in a space in econometrics, in social sciences where they don’t have like all the data. Like there… Like there, there needs to be just a big ass reset. I love the, like if you started with no signal, what would you do? You know what, you’d probably start by making some assumptions and questioning them and thinking really hard and wondering what you didn’t know, and then figuring out what you most needed to know and what it would cost you to learn that. And man, we’d be in a much better space. But we keep having this, like, we’re fighting privacy as though it’s a zero sum game that every. Like every part of that fraction of the signal we lose, we need to try to claw to make up for it and replace it. And that just feels, wrong.

0:40:00.6 MH: It’s difficult. And I try to have empathy for both sides, but you’re absolutely right, Tim. Like people are just sort of clinging to the old paradigm, which is a failing approach. Right? And at the same time, I do try to have empathy ’cause those people who work at companies or whatever, like their responsibility, what they’re measured on is the performance that they generate. And if they don’t know an alternative, they’re gonna try to be as close to what they think works. And I think that’s the problem is we need so much education around leaping forward and some stuff is, and, and some stuff is gonna break, is breaking right now. Like in this world, like if you talk to a lot of smaller, like D2C companies, they’ll all tell you what Facebook has been like over the last year. It’s been way less performant for a lot of companies. But in my mind it’s like, well that’s good. That’s an opportunity. So how do you go capitalize on that? How do you not make Facebook a center of your stack now? How do you make money as a business without, depending on that data?

0:41:07.6 MK: I think about it a different way, which is not like, how do you not make Facebook the center of your business? It’s actually the thing that like personally has really driven me over the last 12 to 18 months that is so fucking exciting, is like we’re actually moving to better methodology, especially around measurement to do with media mix models.

0:41:26.9 MH: That’s right.

0:41:29.1 MK: And experimentation. Which like if we still had an attribution world that existed that was possible, marketers would cling to and instead it’s like, oh, well this shit’s going away. You didn’t have a choice.

0:41:39.9 MH: They are. There’s a couple of vendors out there that are still selling just to be fair.

0:41:42.9 MK: I know, I know. I was at a conference recently where I was like, oh my God.

0:41:46.5 TW: Well I… The Facebook is less performant. I mean, I’ve got clients that are like, well we had to move the… Remove the pixels and these other pixels because I mean, for these reasons, so we just can’t see it. So Facebook is perform… Like, they’re literally confusing measurement and instrumentation with actual value delivered. And I don’t know if that’s exactly what, but there are ones saying, well, Facebook is doing worse, but that’s because the pixels are gone. It’s like, no wait, the pixels don’t actually fundamentally change the truth of what’s going on. And so I think Moe like that’s like, if we could… That’s the… That’s the message and the excitement. The problem is it is going out to a lot of people who really don’t necessarily want their world to be upended in the way that it should. I’m excited about it. There’s still a lot of people who are very, very defensive because they liked the old way and their extracting money from brands because of the old way. And so they want to more say, wait a minute, we’re just losing visibility, but we’re still… We’re still generating value at that same rate. It’s like, well maybe you weren’t generating value at that rate with pixels in your old methodology. I don’t know.

0:43:08.9 MK: It’s, do you know what’s so funny? I went to a marketing conference where like the majority of people were marketers versus like data people. And how many of these conversations were happening of like, oh, we can still do it, but like we just need to use this, this other side hack around or whatever it was. And I was like, really? This is what you’re telling people? Like… And I was actually kind of nervous actually, ’cause I was talking about like, I don’t think this is a big… Well, not that I don’t think it’s a big deal. I think it’s exciting because it’s making us use more sophisticated methods. And I was like really worried that it was gonna be really controversial because it was very different to what everyone else was talking about at the conference. And it really floored me, I think because I had, like, that’s not the culture that I work in. So I hadn’t seen that perspective of marketers still trying to cling on.

0:43:56.6 MH: Yeah, it’s definitely there. Speaking of negative, let’s talk about GA 4 because that’s a big thing that happened this year too. We don’t talk about tools that much, but obviously there’s so many companies that use Google Analytics in some capacity. And so the migration or the push to migrate everyone to GA 4 over this year has been kind of a big deal in the digital analytic space anyway. I don’t know if any of us are that involved. I, we have… I have a few clients that we’re helping with that process. But it is interesting because you… It really forces a rethink of the whole… Of the whole structure. And you can’t really do it apples to apples from universal to GA 4. You really have to go a level deeper and think a little bit more about, okay, how are you really gonna do this? And how are we… And you know, Google has lined the path with exactly what they hope you’ll do, which is, you know, start leveraging BigQuery for everything, which is good for business, I guess.

0:45:01.3 TW: Yeah. That one feels like a, yeah, it’s good money for agencies and there are people making… The content marketing right now is a lot of people saying how to find your UA reports in GA 4.

0:45:14.6 MH: GA 4.

0:45:15.4 TW: We actually, I just had a, one of our clients he was like, Hey, we’re gonna do this training and here’s how we… Here’s the topics we want to cover. And it was like… It was a mapping of… And this was more about the web interface. I’m like, I don’t think that’s right. I mean, I think from our users of data, getting them comfortable with the event centric model, which I think is objectively a better and cleaner way to capture and store data. But yeah, it’s a little more involved. And then I think you’re exactly right. There is constant beat of complaints about the web interface, the reports and the explorations and all of the gaps in that.

0:45:53.9 TW: And it’s like, but yeah, the raw data is much richer and better and cleaner in BigQuery. Now Google 98% to 99.9% of your user base is never gonna write a query in SQL. So I’m like, I’m living in an area where I think I’m gonna be excited when I’m like, yeah, I never use those web interface tools. I mean, I kind of got to that place with Adobe Analytics. I’d much rather pull the data from the reporting API with R but yeah, it’s gonna happen. And it has… I think it’s sparked a lot of those discussions around, do I have to… That the privacy and the migration to GA 4, there are a lot of companies saying, do I need GA 4 or should I go to another…

0:46:45.1 MH: Do I have to have it.

0:46:45.1 TW: Platform? And a lot of those platforms are all kind of salivating and saying, yeah, come to us, maybe we will be simpler. Maybe we will… You won’t have the privacy concerns. So yeah, that’s disruptive in the digital analytics space for sure.

0:47:01.7 MH: Yeah, it’s kind of interesting.

0:47:04.5 TW: Josh, are you doing a bunch of… Are you doing GA stuff theses days?

0:47:08.6 JC: No, no. I mean my company is purely Adobe Analytics, so yeah, we’re just doing that, but we are sort of changing the way that we tag to follow more of an event driven model, so I guess that’s relevant there too. And then also, you know, pulling the data out, you know, in clickstream events and then putting it, you know, somewhere else to process it with SQL, we’re definitely sort of doing some of those same things, but there’s just more steps involved because, we don’t have the… I guess Adobe’s equivalent would be what do they… Like customer journey analytics? We don’t have that. So, we’re sort of doing it that… I don’t know if it’s good or a can of worms…

0:47:50.9 TW: Can of worms.

0:47:51.6 TW: We’re gonna leave that closed over in the corner.

0:47:54.4 MH: We won’t create an equivalence around any products during this episode.

0:47:58.0 JC: Let’s set that aside.

0:48:00.9 MK: Meanwhile, I’ve just been so, like… I’ve just been so blissfully happy to not have to do anything with GA 4. And I remember like talking to my sister being like, why is everyone making such a big deal about this? And she’s like, this is huge. And I’m like, huh, really grateful. I don’t have to deal with it. So I have just been totally hands off, not concerned. Anytime I see it on an agenda at a conference, I’m like, I don’t need to go to that session. This is great. What else can I look at or listen to.

0:48:33.5 MH: Well that’s another one where there’s a lot of that trying to hold onto what was in the past and not really understanding or embracing the model coming. And so that’s why it kind of like connects with me on the privacy side as well, is sort of like, you can’t use GA 4 like you used UA. It’s not gonna work the same way. You need to kind of change your thinking about it. And that’s tough for companies who sort of, you know, use it a certain way. I depend on it this way, I’d like to use it the same way going forward. Well, that’s just not an option. I think it’s growth. There’s potential for growth in both of those. Like leap forward, grab the opportunity, grab the new capabilities, grab the good in it, and then craft that to your will. And it’s just sort of interesting. It’s all happening in our industry all at the same time. Right. And that’s sort of fun. I like change. I think it’s… Shows you great opportunities. So I’m all about it, but, like you Moe I’m not particularly perturbed personally.

0:49:37.7 MK: Though I will say we had a data analytics Wednesday panel on GA 4 and it was our most attended data analytics Wednesday of the entire year.

0:49:44.2 TW: That’s…

0:49:44.2 MK: It was so busy.

0:49:46.5 TW: I mean, how much of it was a bitch fest? Like how much was.

0:49:49.0 MK: No, it really wasn’t.

0:49:52.6 MH: It wasn’t. Okay.

0:49:52.7 MK: It actually wasn’t, a lot of it was like, Hey, how do I do this thing? How do I best prepare? Like, are we on the right track? I actually found it was a very constructive conversation.

0:50:02.8 MH: Well, let’s look forward and get our crystal balls out here and decide what’s gonna be happening in the future in classic Conan O’Brien in the year 2000. So deep track, most people won’t get that probably.

0:50:22.5 TW: Yep. I guess it will not surprise you that I don’t get the reference.

0:50:23.9 MH: On the old Conan show Yeah. You’re not gonna get it Tim. No. On the old Conan O’Brien show, they used to do this little segment where they would say that it was after the year 2000, it became pretty funny because there were always saying in the year 2000. That was way in the future.

0:50:37.6 TW: I was kidding.

0:50:40.1 MH: So who wants to prognosticate first? And maybe we should have Tim do it first so that way we can all disagree with him versus the other way around. No.

0:50:49.4 MK: Yes.

[laughter]

0:50:52.5 TW: I mean, I don’t know, like with the looking, I feel like we wound up getting a little bit the great reckoning around privacy. Like I think that is… I think in the near term, I think that’s… That’s gonna be it. And then, I mean, I hope like… Moe like you wind up being a little bit more of the model. Like slowly companies are I think kind of waking up. Although, I don’t know, I still feel like it’s a battle. It’s between competing forces is to cling to the old and keep writing that until it completely bursts. It was a… I’m trying to think, when do we have Tim Tim Wong on? It was a couple of years ago.

0:51:40.0 MH: It wasn’t 2022, I think maybe 2021.

0:51:44.8 TW: But that I just… It feels like his predictions are just, it’s getting more and more fraught. And I think the way that we’re measuring because of privacy being both the regulations and changes to like browser technology. So in the digital analytics space and the way that we’re measuring the effectiveness of advertising, I think next year we’re gonna be like, okay, did we, did the needle get moved in a positive direction or is it just going into the crappy hole of pointlessness?

0:52:19.6 MH: Well, I feel like right now we’re just in this highly reactive state right? Where this change is just hitting it again and again and again. Right. Like Corey Underwood has a new blog post every other week about some new law that’s got passed or whatever in the United States for sure. Because state by state we’re slowly clawing out the space, which is about the worst way you could do it. I didn’t realize what a fan of centralized government I was until I compared what we’re doing in the United States to what was happening with GDPR. And I was like, we need some national legislation real bad.

0:52:52.7 TW: But unfortunately out of the average age of our national legislator is like 82, so yeah. When it comes to…

0:52:58.1 MH: Totally gonna understand cookies.

0:53:00.4 TW: Those lawyers, the lawyers that have it easy. Yeah.

0:53:01.7 MH: But no, I mean, and even on the GDPR side, ruling after ruling slowly kind of reveals the path, right? In a way. And there’s things getting like surprising things that I was like, oh, I had not even considered that. So, as an example, like Discord, which is, you know, like a communication software, they were just fined by the French Data Protection Authority. And basically it was primarily the reason was because they, you know, people who were good at privacy law and all that stuff would probably have a way better take on this. But basically they had no way to like delete accounts that no one used for a long time. Right. Because Discord, you can just log in and start using it. There’s really not, it’s not like a product led growth company, right? You get lots of users, well that data just persists on into forever.

0:53:49.3 MH: That’s not okay under GDPR. You’ve gotta have a point at which you go delete that data, some data deletion period. But there was also things in there about how if you hit the X on the discord on your lap, on your computer, that doesn’t actually close Discord. It just minimizes it. And they were going after ’em for that functionality. I was like, oh, well Slack and Zoom and Steam and a lot of other company, Xbox, all gonna wanna have a word here. Because that was one of the things they were like, well, if you’re in, you know, communicating with via like a microphone, a discord, and you close that, you might not know that you’re being collected at that point. Which I was like, well, it’s a, but it’s like, oh wow. So these privacy concerns are not just affecting like tracking pixels and stuff like that.

0:54:33.2 MH: It’s affecting like UX and UI decisions architecture, like how products are deployed and how they’re put onto your computer. And I was like, wow. I had not even really considered, but we have a lot of boundaries that we’re gonna be exploring with privacy and it’s just gonna keep going and going. And I think that’s what I kind of see over the next year. Just, we’re all gonna be reacting a lot because new privacy laws are gonna come into place. We’re gonna have to figure them out. And again, part of that reaction, Tim, to your earlier points is that it’s a lot of people trying to cling to what they used to have, right? How can we get as close to what I used to have and still keep on trucking the old way? And it’s like at some point you’re… The last pinky hole that you have on that way of thinking is gonna get yanked off of the rail and you’re gonna go flying. It’s like, do you want that to be a fall or a controlled jump? You know? So strap on your parachute and let’s get after it.

0:55:28.5 TW: So enough on the privacy, Josh I have like a bold, bold prediction.

0:55:34.0 JC: Oh God. Oh yeah. The the wild prediction. I think.

0:55:39.9 MH: Is it so bold?

0:55:40.0 JC: Sort of like.

0:55:40.8 TW: No, no. I was thinking more of the generative AI stuff.

0:55:46.3 JC: We could save the the other one.

0:55:47.8 TW: That’s right. To be fair, Josh has a couple of bold.

0:55:50.9 JC: Spicy, spicy takes.

0:55:51.3 TW: Spicy, spicy takes. Yeah.

0:55:56.5 JC: I could do the AI one. So I… Yeah, I have a prognostication about generative AI getting more attention and like potentially commercial applications and, you know, I’m seeing this, like, I’m seeing this on Twitter, there’s this awesome account, weird dolly where it’s just weird prompts being punched into Dolly. And then, you see these hilarious images that come back like launching the Eiffel Tower into space or Marty McFly trying to get plutonium at Walmart, and then it actually like spits out like a decently like serviceable image coming back from that. Like, these are actually getting to be pretty powerful and it makes me just think about like, well what are the, maybe like some of the marketing or commercial applications of that. I mean, we were talking about Hidden Door earlier, which is based on generative AI as well. But I’m thinking about if you can create these sort of images, like could you use that to do AI assisted design for marketing assets, creatives, like, I don’t know, website layout even…

0:56:58.4 MK: For Canva.

[laughter]

0:57:00.7 JC: Yeah, exactly. Well.

0:57:05.1 TW: And does the text generation like it feels weird. Like I see in the content marketing community, like these like use these tools to generate your SEO friendly posts, which I’m like, Really like that is just throwing noise. I like the generative art side a lot more because those really, I wonder if that novelty’s gonna gonna wear off at some point. Like, but you, they’re kind of fun ’cause you get to see the creativity and just what people throw out and then you actually have an image that represents it. But that will be… And I guess there are also… There have been some kind of lawsuits in that space where depending on which tool is being used and like if there were artworks that it can be traced back to as a derivative, then who actually owns the, like that’s a, that’ll be a morass of legal and regulatory stuff.

0:58:06.3 JC: Totally. There was even, I mean the other storyline I saw that was kind of cool. There was actually an AI… There was a song that went viral in China where it was an AI generated voice singing. It had a hundred million streams, more than a hundred million streams. And then it’s like, well they trained that AI on a real voice. And so like how does that work from a royalties perspective, right? Like who has that intellectual property? I think it’s really… It’s a really interesting and like potentially problematic as well, especially with the art. I think there’s a lot of artists that have, you know, come out with some of these AI generated art tools and said, well hey, like this is clearly ripping off my style. Like this was trained on my work and I didn’t… I didn’t consent or give permission for that. So yeah, there is also this like, this real questionable side of it too. But I guess I just get excited cause I’m like, oh, you know, we have so many problems with, we don’t have enough good creative variations when we’re doing DCO. Maybe we could use this for that. So.

0:59:10.6 TW: Are you committing now to generating at least one episode’s artwork with a generative AI technique?

0:59:19.5 JC: I might do it for this one.

0:59:19.6 MH: We might not be going far enough. How close are we to being able to generate an episode of the podcast with an AI? That’s the question. We could just get it to use our voices and get three computers talking to each other for an hour.

0:59:32.1 JC: Oh, maybe we could get it to edit the podcast too. Hopefully it’s able.

0:59:37.5 MH: Anyway, I agree. I think the thing that I… That keeps coming to my mind over the course of this year and thinking about AI and generative AI and some of the cool things that have happened is the show we do with Dennis Mortenson about, vertical AI and the application of it and basically like, these are tools and the best people into the future will figure out how to leverage these tools in the best way in the right places. And I feel like that’s very much the exploratory stage we’re in, right? It’s sort of like, yeah, you can’t make an AI write a whole article for you, but you could leverage an AI to assist you in writing that article. Like, you know, I was writing something recently and I was like, Hey, I wonder who the first person to coin this phrase is. Instead of Googling it, I just used the AI assistant in that particular tool to tell me like who that person was. And it’s like, oh cool. So that’s…

1:00:25.8 TW: Was it me.

1:00:26.3 MH: Pretty useful information. It was not you.

1:00:28.5 TW: Damn it.

1:00:31.8 MH: It was Ben Schneiderman. I asked it who coined the term data product actually was what I was asking. It was Ben Schneiderman in 1992, I think.

1:00:39.8 TW: Wow.

1:00:42.5 MH: So there you go. Like, so instead of like having to jump over to Google and look for that, I just used the AI assistant in that particular application to go find that out for me. But you know, it’s… But that’s one of the things is like, there’s lots of different applications of this that I think will start to emerge and we all have to figure out how to… How will they incorporate, how we incorporate them in kind of good ways.

1:01:04.3 MK: My only prediction for 2023 is that I’m gonna lose a shit ton of sleep.

[laughter]

1:01:13.9 MH: Yes. Well that’s a pretty sound forecast given your historical data.

1:01:19.3 MK: Yes. And the fact that I’m gonna have a baby in a couple of weeks.

1:01:24.3 MH: Well that was sort of the idea. Sort of the… I assumed you were using a data model from the year with the first.

1:01:35.5 MK: It’s too depressing to look at that data.

1:01:37.8 TW: That is gonna be interesting.

1:01:38.8 MH: Oh, but it’s cute.

1:01:42.2 TW: We do have a different, plan for…

1:01:43.8 MH: It’s cute data.

1:01:44.7 TW: For while Moe was out this time we weathered 2022 with me being out by just crunching things schedule-wise.

1:01:53.1 MH: We just slammed the episodes through.

1:01:56.1 TW: We’ve determined that is not the thing to do with someone who is eight months pregnant to say, you know what, let’s double our recording. So we do have a plan. We will not be, when young Harry arrived, his arrival led to us rebroadcasting old shows, and this time we’ve got a different plan that we’re pretty excited about.

1:02:16.7 MK: Yeah. It’s gonna be a wild Summer.

1:02:18.2 MH: Well, 2023 is gonna be an amazing year for a lot of different reasons, but yeah, this past year has been a great one for the podcast. I think as I think about it, no show would really be complete without a huge thank you to our audience because, we do this show, well, I mean we like doing it, but you, the listener really showed up for us this year and it’s been pretty cool to hit sort of a major milestone, if you will and those kinds of things. But, you know, hearing from people who listen to the show, hearing from fans of the show, going through a one chip challenge with Tim because of fans of the show. These are all things that like, as the pain recedes the memory, the fond memory then takes its place.

1:03:01.5 TW: I will say as COVID faded, this was a year where I can think of three specific live events where I got to meet people for the first time in person who were fans of the show and in some of the cases, we’d kind of connected, you know, digitally. So it was kind of like… It was kinda like what Twitter was doing for us, back in the early days. But that was like pretty cool to meet people in person and hang out.

1:03:31.2 MH: A 100%. Anyway, so thank you all for listening and I know I speak for both of my co-hosts, Moe and Tim and our executive producer Josh, when I say, no matter what challenges you’re facing, analyzing data in 2023 from all of us to you, just remember, keep analyzing.

1:03:57.3 Announcer: Thanks for listening. Let’s keep the conversation going with your comments, suggestions, and questions on Twitter at @analyticshour, on the web at analyticshour.io, our LinkedIn group and the Measured Chat Slack group. Music for the podcast by Josh Crowhurst.

1:04:14.3 Charles Barkley: So smart guys wanted to fit in, so they made up a term called analytics. Analytics don’t work.

1:04:22.2 Kamala Harris: I love Venn diagrams. It’s just something about those three circles and the analysis about where there is the intersection, right?

1:04:31.7 MH: Hooray. Hooray.

1:04:33.4 MH: Ba ba ba ba ba ba ba.

1:04:35.4 Josh: Meow mix meow mix. Please deliver.

1:04:39.2 TW: Rock flag and happy new year.

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