#298: Listener Questions Answered Live from Marketing Analytics Summit!

[Announcer]: Welcome to the Analytics Power Hour. [Announcer]: Analytics topics covered conversationally and sometimes with explicit language. [Jim Sterne]: The Marketing Analytics Summit is pleased to present these four amazing podcasters. [Jim Sterne]: We have Michael, the self-effacing every-man consultant who knows far more than he lets [Jim Sterne]: on.

[Jim Sterne]: We have Moee, who flow all the way in from Sydney, Australia. [Jim Sterne]: She's the determined, driven practitioner, the one to stand up and say, well, that's [Jim Sterne]: all very well and good, but how do we actually make it work? [Jim Sterne]: There's Val, who co-founded the Consultancy facts & feelings, because we have strong [Jim Sterne]: feelings about our facts and no facts about our feelings. [Jim Sterne]: And there's this guy named Tim.

[Jim Sterne]: Ladies and gentlemen, take it away. [Michael Helbling]: Hi, everyone. [Michael Helbling]: Welcome to the Analytics Power Hour, this episode 298. [Michael Helbling]: And we are recording live at the Marketing Analytics Summit in the beautiful Santa Barbara.

[Michael Helbling]: You know, 21 years ago, my very first Analytics conference was right here in this city at [Michael Helbling]: this conference, formerly known as E-Metrics. [Michael Helbling]: And similar to today, it was a conference full of smart, engaging, and passionate people [Michael Helbling]: learning together about how to solve the problems they were facing day-to-day in the analytics [Michael Helbling]: industry. [Michael Helbling]: A lot has changed. [Michael Helbling]: A lot has changed.

[Michael Helbling]: But persistent through all of that is this beautiful analytics community. [Michael Helbling]: And the shared learning, this podcast was actually created to encourage and celebrate. [Michael Helbling]: So to that end, I have my co-hosts with me. [Michael Helbling]: And we have put out a survey to gather your questions.

[Michael Helbling]: We've been asking you during the conference. [Michael Helbling]: And so we have a number of them to get through, and we'll do our best to answer them from [Michael Helbling]: some of the perspectives we bring to the table in our various roles. [Michael Helbling]: So let me introduce them. [Michael Helbling]: Moee Kiss.

[Michael Helbling]: Hi, folks. [Michael Helbling]: Hi. [Michael Helbling]: Director of Data for Product, Canva. [Michael Helbling]: And of course, Tim Wilson, Head of Solutions at facts & feelings.

[Michael Helbling]: Hello. [Michael Helbling]: And Val Krull, Head of Delivery at facts & feelings. [Val Kroll]: Hello, hello. [Michael Helbling]: And I'm Michael Helbling, my president of Stacked Analytics.

[Michael Helbling]: Okay. [Michael Helbling]: What a privilege to be here with all of you in person. [Michael Helbling]: It's been a wonderful couple of days. [Michael Helbling]: So let's just dive right into it.

[Michael Helbling]: So we've got a question. [Michael Helbling]: This one came from James from Namer's Children's Health. [Michael Helbling]: What's the best approach to establishing yourself as a partner and not an order taker when working [Michael Helbling]: with stakeholders? [Val Kroll]: James is the one who has the most trouble with the uncomfortable pause.

[Val Kroll]: So that's why he looks the best. [Moe Kiss]: Oh, I assumed that was your cue. [Moe Kiss]: Anyway, we were having a conversation earlier about taking notes over lunch. [Moe Kiss]: And if you don't want to be perceived to be the person in the room taking notes, then [Moe Kiss]: don't take the notes.

[Moe Kiss]: And I think it's really jarred with me because I have this belief, I mean, I always know [Moe Kiss]: that I come back to everything that Cassie Kazarkoff says about just be useful. [Moe Kiss]: And I am sometimes fine. [Moe Kiss]: I'm still like, I might be the most senior person in the room and sometimes I do still [Moe Kiss]: take notes. [Moe Kiss]: Part of that's my brain, but part of that is also that I want to be useful and the people [Moe Kiss]: in the room are normally smarter than I am.

[Moe Kiss]: And I have much more interesting things to say. [Moe Kiss]: So I actually kind of struggle a little bit with the question in and of itself. [Moe Kiss]: I think one of the things that maybe means that it's OK to still take notes, but is also [Moe Kiss]: adding your voice to the conversation. [Michael Helbling]: I think, I don't know, I just, again, we were chatting about this at lunch.

[Moe Kiss]: When you don't contribute to the conversation, when you're not willing to be accountable [Moe Kiss]: for what you say, I think that's when you kind of, you're not the partner, so to speak. [Tim Wilson]: I mean, I think it's, I agree. [Michael Helbling]: I think it's don't be an order taker. [Tim Wilson]: I think to me it is, and there have been a lot of discussions at this conference, a [Tim Wilson]: lot of the discussion in the industry were at large around how are we using AI and there [Tim Wilson]: to be curmudgeonly and a little cranky about it.

[Tim Wilson]: But a lot of is, how do I take more orders? [Tim Wilson]: How do I take more orders and produce more output? [Tim Wilson]: And that misses, to me, the fundamental part of becoming more of a partner is to step into [Tim Wilson]: their shoes, ask the questions, write it down, be genuinely curious. [Tim Wilson]: Don't be trying to get to, how quickly can I turn this into a ticket?

[Tim Wilson]: And I think that has been, AI has nothing to do with that. [Tim Wilson]: That has been a 20-year problem in our industry when we sit around and wring our hands and [Tim Wilson]: gnash our teeth about why aren't we brought in. [Tim Wilson]: We produced the next dashboard like they asked us to, we gave them recommendations, but did [Tim Wilson]: you ever actually sit down up front and say, I just, I'm an analyst, I'm curious, I want [Tim Wilson]: to understand what you're grappling with.

[Tim Wilson]: And there have been, even at this conference, there have been some discussions around that. [Tim Wilson]: But I, I lay awake at night fretting about the industry being, I want to be a partner, [Tim Wilson]: but I behave like an order taker. [Tim Wilson]: And it's like, it's simple, just be curious, go ask them, get inside their heads and start [Tim Wilson]: asking them, how can I have some problems? [Michael Helbling]: Yeah, okay.

[Moe Kiss]: I kind of want to call a bit of bullshit on it though, because I do, I get- [Michael Helbling]: On brand? [Moe Kiss]: I get what you're saying, and I hadn't really thought about like AI driving more of the [Moe Kiss]: order taking. [Moe Kiss]: I actually feel like my experience might be a little bit different. [Moe Kiss]: I think the thing that I just keep observing is data folks don't want to be accountable.

[Moe Kiss]: I had this conversation at the back of the room earlier, it's like, they want to be like, [Moe Kiss]: here's the numbers, don't look at me, like I don't want to be on the hook for the recommendation [Moe Kiss]: that I'm making. [Moe Kiss]: And I don't know, I don't think that's an AI thing. [Moe Kiss]: I think that's just a, maybe it's a 20 year old industry thing. [Tim Wilson]: I think it is, I mean, I actually agree that it's like, we make recommendations and they're [Tim Wilson]: not following them.

[Tim Wilson]: And a lot of times like, where did this start? [Tim Wilson]: Well, we asked them what they, we asked them what their business question was. [Tim Wilson]: If you're asking them, even if you're saying, I'm asking what the business question is, [Tim Wilson]: there is a human element of saying, I am your partner, I am in this with you together. [Tim Wilson]: So I'm just pushing for moving upstream and not jumping to the data and jumping to the [Tim Wilson]: solutioning and jumping to, did I produce the published report that made a recommendation [Tim Wilson]: and then I'm upset.

[Michael Helbling]: So you didn't fix that? [Val Kroll]: Yeah, I'm just kidding. [Val Kroll]: I would say like to get started with that, it's not even always about like anticipating [Val Kroll]: all of their needs. [Val Kroll]: I think it is being curious and just thinking about the motivations and the stresses that [Val Kroll]: that person has in their role, like what pressures are they facing?

[Val Kroll]: And I think that this has come up a couple of times too about how do we de-risk the [Val Kroll]: decision that's upcoming for them or where should they spend that next dollar and do [Val Kroll]: a little bit of prep work before you walk into that room to show that you're trying [Val Kroll]: to empathize with what they're dealing with because their job is hard too. [Val Kroll]: It's very different than yours, but starting from that place, I think is a good way to [Val Kroll]: kind of say like, we're in this together, we're side by side, not sitting across the [Val Kroll]: table and I'm just going to push something on you at some point.

[Moe Kiss]: But I think the difference there is you talked about preparation and I think a lot of the [Moe Kiss]: curiosity can come without necessarily absorbing stakeholder time. [Moe Kiss]: And I worry sometimes that the push is like, oh, well, I haven't got enough context. [Moe Kiss]: My stakeholder is time poor. [Moe Kiss]: So, you know, that sort of thing where it's, I actually think there's a lot of personal [Moe Kiss]: responsibility that data folks need to take to be like, I have enough information available [Moe Kiss]: to me throughout various, various Slack channels, emails, et cetera, to have some of that curiosity [Moe Kiss]: before even asking the question of a stakeholder.

[Tim Wilson]: 100%. [Tim Wilson]: 1000%. [Tim Wilson]: I see your 100% and raise it. [Tim Wilson]: But I think if you're thinking about it, you should be saying, this is my understanding, [Tim Wilson]: but here's something that I can't.

[Tim Wilson]: I listened to our quarterly conference call and there was something that doesn't make [Tim Wilson]: sense to me. [Tim Wilson]: I tried to figure it out. [Tim Wilson]: It doesn't. [Tim Wilson]: I think you, marketing manager, might help me explain this because I can't square that [Tim Wilson]: circle.

[Tim Wilson]: So, yes, showing up and that certainly worked with analysts who say, well, what are my lists [Tim Wilson]: of discovery questions? [Tim Wilson]: What is your most challenging business problem? [Tim Wilson]: If that's the way you show up, they're going to be like, I have to explain every minute. [Moe Kiss]: 25-year-old data slanted slightly because that's kind of how they show up sometimes.

[Moe Kiss]: No age. [Michael Helbling]: No age. [Michael Helbling]: All right. [Moe Kiss]: We're going to move to our next question.

[Moe Kiss]: This is the whole episode. [Michael Helbling]: Sorry. [Michael Helbling]: And this is coming from a member who's here in the audience, Michelle Kiss. [Michael Helbling]: Whoo.

[Tim Wilson]: Any relation? [Michele Kiss]: None. [Michele Kiss]: Completely the same person. [Michele Kiss]: Complete coincidence.

[Michele Kiss]: Yes. [Michele Kiss]: Confuses everybody. [Michele Kiss]: Okay. [Michele Kiss]: So, first of all, my question has two parts.

[Michele Kiss]: There's a pre-question that is required for setting the context. [Tim Wilson]: Yes, they're related. [Michele Kiss]: And so that we can interpret your answer. [Michele Kiss]: Okay.

[Michele Kiss]: So, first of all, the pre-question is where do you guys stand on AI? [Michele Kiss]: Are you a skeptic or a fan? [Michele Kiss]: Okay. [Michele Kiss]: So, that's the context.

[Michele Kiss]: Then, what things have you personally found that it is useful for and reliable for? [Michele Kiss]: It has to be life. [Val Kroll]: Okay. [Michael Helbling]: I'll go first.

[Val Kroll]: So, I would say that I'm a skeptic, but that's just kind of like my nature. [Val Kroll]: I don't think there's anything new or special about that. [Val Kroll]: That's just kind of who I am as a person, but I'm excited at the same time. [Val Kroll]: And I think I've been inspired by a lot of the conversations we've been having over [Val Kroll]: the past couple of days that have gotten my wheels turning about some different things [Val Kroll]: that I can try when I get back to my desk.

[Val Kroll]: So, I would say more on the skeptic, but still excited, still optimistic. [Val Kroll]: I don't think, you know, world's ending just yet. [Val Kroll]: One of the things that I have been playing around, this is recency bias, but just thinking [Val Kroll]: about how do I start at like day 60, day 90 with the where I'm at with an understanding [Val Kroll]: of the business context for a potential prospect conversation. [Val Kroll]: And so, we had been doing a lot of process effects and feelings very manually to kind [Val Kroll]: of go through and listen to like most recent earnings calls or pulling out, you know, press [Val Kroll]: releases or seeing what was publicly available just to kind of understand what is the context, [Val Kroll]: what is the competitive nature, where are they competing and using AI and building out [Val Kroll]: some gems to build that out for me.

[Val Kroll]: And so, I'm asking it to give me some tables and comparisons of where do they compete on [Val Kroll]: what message is? [Val Kroll]: Is this about pricing? [Val Kroll]: Is this about quality? [Val Kroll]: And so, really trying to figure out like how do I get into that context so that I'm not [Val Kroll]: asking like question number one, what are your goals?

[Val Kroll]: It's like, let me start with something because then I'm going to be able to ask much richer, [Val Kroll]: deeper conversations. [Val Kroll]: And so, again, recency bias, but that's been the most fun one just to kind of understand [Val Kroll]: outside of an analysis, what's something I can do to show up in those conversations [Val Kroll]: to kind of position myself to be a better partner. [Moe Kiss]: Mine are not sexy. [Moe Kiss]: Like I don't...

[Moe Kiss]: That wasn't sexy. [Moe Kiss]: Build me a table of your competitors. [Moe Kiss]: Well, it depends what you think is sexy. [Moe Kiss]: Yeah, I mean, I do a lot of leadership-y things and those things tend to be quite admin-y.

[Moe Kiss]: I do think the one... [Moe Kiss]: Oh, I forgot your first part of the question. [Moe Kiss]: I'm excited and terrified. [Moe Kiss]: I would say I'm...

[Moe Kiss]: I don't... [Moe Kiss]: Fan feels like a strong word. [Moe Kiss]: I do like a lot of the potential and the personal gains in the way that it's changed how I work, [Moe Kiss]: but I have this like level of fear, which I think is pretty rational and normal. [Michael Helbling]: It's a pretty big shift.

[Moe Kiss]: And yeah, a lot of the ways I use it are not sexy. [Moe Kiss]: But I do think the thing that has been really nice for me personally is feeling like code [Moe Kiss]: is not so far away. [Moe Kiss]: Like it's been a couple of years since I wrote code very regularly, and there are things [Moe Kiss]: that now I feel much more comfortable. [Moe Kiss]: I'll go do a quick Here's the Queer I Want to Vibe code something.

[Michael Helbling]: And I also know enough to know if it's not correct, which is important, but it makes [Moe Kiss]: it feel like more approachable to a skill that's pretty rusty. [Moe Kiss]: The rest of the stuff is like making my snarky comments in Slack, seem less snarky, like [Moe Kiss]: meeting summaries. [Moe Kiss]: Like, yeah, it's not sexy. [Tim Wilson]: So I'll say I'm a skeptic and a fan.

[Tim Wilson]: So I'll punt on the first question. [Tim Wilson]: My skepticism comes from I've been developing this observation that I feel like we are [Tim Wilson]: as analysts, we are often saying this is the thing the tool can do. [Tim Wilson]: This is my hammer. [Tim Wilson]: So now I'm going to go figure out what the nail is, and I'm going to tell myself that [Tim Wilson]: the nail is going to solve a problem that has nothing to do with the technology.

[Tim Wilson]: So I have found it to be very useful on debugging code, kind of piggybacking off [Tim Wilson]: of what you said, because coming from having written code, debugging it. [Tim Wilson]: It is very, very useful. [Tim Wilson]: I get very, very nervous when I have Vibe coded and yes, it brings results out. [Tim Wilson]: But I've now seen in the wild how that can go awry.

[Tim Wilson]: I actually find that it's very useful just from a thought clarity. [Tim Wilson]: And I think that hasn't changed. [Tim Wilson]: That probably took me three times listening to Jim Stern, give various [Tim Wilson]: presentations about writing prompts for it to take. [Tim Wilson]: And it was the first time I heard it now, kind of everybody saying it of some [Tim Wilson]: of the keys with writing prompts, but prompts, I think by writing.

[Tim Wilson]: So saying this forces me to organize my thoughts and then I'm going to trust [Tim Wilson]: and verify what comes back. [Tim Wilson]: That is much more on the help me clarify my thinking, because if you're helping [Tim Wilson]: me clarify my thinking, just like a human being who I think, no, that's wrong. [Tim Wilson]: That's bullshit. [Tim Wilson]: You can challenge me, but you may be wrong.

[Tim Wilson]: I am not, and which wasn't the, where is it? [Tim Wilson]: Not useful, but I, anytime it's like, it's going to basically do glorified [Tim Wilson]: anomaly detection and spit out insights. [Tim Wilson]: Yeah, I'll go to the mat for a while on that. [Tim Wilson]: And I'm pretty triggered with various claims to have it do that.

[Tim Wilson]: Michael, what happens after you finish a GA4 analysis? [Michael Helbling]: Oh, traditionally, I guess I paste screenshots into a doc, rename it final, [Michael Helbling]: final, uh, you know, do not change final, uh, lose the source query and then wait [Michael Helbling]: for somebody to ask, can we break this down by campaign? [Michael Helbling]: Terrifying. [Michael Helbling]: Please stop.

[Michael Helbling]: I would love to emotionally and professionally. [Tim Wilson]: Well, that's why ask dash, why.ai just released the Prism Cod co-work connector. [Tim Wilson]: It brings the whole Prism brain to your GA4 big query data.

[Tim Wilson]: Ooh, the whole brain analytics, agent harness, skills, memory engine, the works. [Michael Helbling]: Wow. [Michael Helbling]: So co-work doesn't just answer questions. [Michael Helbling]: It remembers context, uses repeatable skills, keeps analysis [Tim Wilson]: organized, exactly.

[Tim Wilson]: You're, you're picking it up. [Tim Wilson]: Your co-work based analyses are accessible in Prism, organized, traceable, [Tim Wilson]: auditable, and ready to use with your other data sets. [Michael Helbling]: I love that. [Michael Helbling]: Cause currently my audit trail is mostly like, oh, I know I had a reason for doing [Michael Helbling]: that.

[Michael Helbling]: I can't remember what it is. [Tim Wilson]: That checks out. [Tim Wilson]: The connector also ships with ready to run funnel and cohort skills right out of [Tim Wilson]: the box. [Michael Helbling]: So I can ask for retention by acquisition channel and not immediately enter a [Michael Helbling]: fugue state.

[Tim Wilson]: Right. [Tim Wilson]: And every analysis becomes a shareable page. [Tim Wilson]: Prism auto-generates the dashboard page right from co-work. [Tim Wilson]: Oh, so the answer doesn't die in a chat thread.

[Tim Wilson]: That's right. [Tim Wilson]: It lives as a reusable and shareable analysis. [Tim Wilson]: Well, that's very rude to my old workflow, but fair. [Tim Wilson]: We'll go to ask dash, why.

ai. [Tim Wilson]: That's ask dash the letter y.ai and sign up for the wait list. [Tim Wilson]: Yeah.

[Michael Helbling]: And use code APH and that'll get you pushed to the top of that wait list. [Michael Helbling]: Ask dash, why.ai code APH. [Michael Helbling]: I like it.

[Michael Helbling]: Co-work. [Michael Helbling]: It's GA for analysis, but with receipts, which was not part of the question. [Val Kroll]: We're only on our second question. [Val Kroll]: You can't, you can't get triggered yet.

[Tim Wilson]: No, I welcome it. [Tim Wilson]: I was triggered 36 hours ago. [Michael Helbling]: I think it's okay. [Michael Helbling]: I go through life triggered.

[Michael Helbling]: All right. [Michael Helbling]: We have another question from someone here in the audience. [Michael Helbling]: So I'll hand it off to Jen Coons. [Jenn Kunz]: It actually follows up with what Tim was just saying, perhaps a bit of it.

[Jenn Kunz]: Do any of the ways we promote and use AI in the industry make you feel icky? [Jenn Kunz]: Do you have a threshold of lines that you don't want to cross when it comes to AI? [Tim Wilson]: Can I add, I'll add a new one to that. [Tim Wilson]: I am not a fan of the note takers in meetings and doing the summaries, [Tim Wilson]: which I know is super controversial just inside.

[Tim Wilson]: And because to me, I've watched and I've watched this time and time again, [Tim Wilson]: how much that drives laziness and not paying attention in the meeting [Tim Wilson]: and not editorializing. [Tim Wilson]: And it is flat summaries. [Tim Wilson]: I've worked with some clients where they have literally said, oh, [Tim Wilson]: you weren't at the meeting, we recorded it. [Tim Wilson]: Here's the Gemini summary.

[Tim Wilson]: And it's just not useful because it's not telling me what the human beings [Tim Wilson]: in the room were thinking about. [Tim Wilson]: Let me throw one other, I'll be quick. [Tim Wilson]: Because, Jim, when you did your closing note, you know, yesterday, [Tim Wilson]: which was very good, not going to be too useful for people who were listening [Tim Wilson]: to this, but there was a lot of talk about using AI to ramp up junior analysts [Tim Wilson]: and build lots of different, use different tools that kind of let them kind [Tim Wilson]: of do self study.

[Tim Wilson]: And I wound up wondering about where do we teach the junior analysts, [Tim Wilson]: how to actually relate with people and have the creative, collaborative process. [Tim Wilson]: And so there's something there, too, that makes me nervous that we're [Tim Wilson]: at a conference right now, like are we on some logical trajectory where we [Tim Wilson]: think we're all just going to sit at home and just have AI do everything [Tim Wilson]: that needs to happen. [Tim Wilson]: There is a very, very real part of this job that is human and communication [Tim Wilson]: and collaborative creativity.

[Tim Wilson]: And I get very nervous that people are not recognizing the value of that [Tim Wilson]: and trying to have AI replace it. [Tim Wilson]: That was really deep. [Moe Kiss]: I was going to talk about meeting notes. [Tim Wilson]: Go for it.

[Tim Wilson]: Do I need to move away? [Moe Kiss]: No, but so for me, I actually find the meeting notes summaries incredibly [Moe Kiss]: useful. And the biggest thing for me is, like, as someone who self-declared [Tim Wilson]: has ADHD, can you square the meeting notes with the taking notes by hand? [Moe Kiss]: I do.

So I do still often also take notes. [Moe Kiss]: But the taking notes for me is me, number one, it helps me pay attention [Moe Kiss]: in the meeting. And number two, it helps me retain the informations. [Moe Kiss]: Like if we're talking about especially something complex, I won't necessarily [Moe Kiss]: fully hear it.

And then the next day, I sometimes do look at my own notes. [Moe Kiss]: I won't necessarily look at the notes. [Moe Kiss]: But what I find useful is the next steps. [Moe Kiss]: There is always like, no, when you are trying to corral like 20 people, [Michael Helbling]: you can be like, what is the big deal?

[Moe Kiss]: What is it? Why is that the big deal? [Val Kroll]: Tim, just fell off the stage for those of you listening. [Val Kroll]: That was a red fox impersonation for anyone who walks.

[Moe Kiss]: It's like, this person's going to follow up with this. [Moe Kiss]: By then this person's going to follow up with it. [Tim Wilson]: And because it's actually fucking terrible at that, it just goes through [Tim Wilson]: and says, this is what it was. [Tim Wilson]: And you need the human editorial person saying, [Tim Wilson]: what are the real next steps?

[Tim Wilson]: That's where it's trying to go through a discussion. [Moe Kiss]: To get back to the question, though, of what makes me feel [Moe Kiss]: ick, what makes me feel ick is things being shared [Moe Kiss]: that have not been properly vetted and QA and meeting notes [Moe Kiss]: fall into that category just as much as analysis or write up does. [Moe Kiss]: Like that's a bit that I get stressed about. [Moe Kiss]: Is it analysts are like, yes, I can pump out more stuff.

[Moe Kiss]: I'm going to automate this report. I'll send it out. [Moe Kiss]: I'm never even going to look at it. [Moe Kiss]: And I'm like, oh, that feels uncomfortable.

[Tim Wilson]: But isn't the meeting notes is asking people to do a lot [Tim Wilson]: because they're like, I got to get the meeting notes out promptly. [Tim Wilson]: And it takes an enormous amount of diligence to say, [Tim Wilson]: I am truly going to read through these and modify and write my own little summary and write. [Tim Wilson]: So it's like, you can paint the picture, [Tim Wilson]: but watching what actually happens with the people I've worked with, [Tim Wilson]: all of a sudden I'm like, oh, this was just barfed out.

[Tim Wilson]: And I'm sure they scan through it and I'm sure they told themselves, [Tim Wilson]: yeah, that seems about right to be fair. [Moe Kiss]: I just take the like the here are the action items. [Moe Kiss]: I don't send the whole summary. [Moe Kiss]: Is that worse or better?

[Tim Wilson]: I well, if you take them and you say, yeah, that looks about right. [Tim Wilson]: I think that's a problem because I think there is much more often. [Tim Wilson]: There is the person who's sending those out [Tim Wilson]: should have a responsibility to say these are the things that really need to happen. [Tim Wilson]: There's a level of prioritization and wording and body language [Tim Wilson]: and and adding net new stuff that I know that Joe said that Joe was going to do this.

[Tim Wilson]: But the reality is I know in our organization that Joe is going to have Mary work with him on this [Tim Wilson]: and putting that sort there, there is something in that maybe I'll get off that. [Moe Kiss]: There's a lot of nods, so I'm interested to hear more Tim. [Moe Kiss]: Normally, I don't have this kind of live feedback that suggests maybe you're right. [Michael Helbling]: That they're agreeing with me.

[Michael Helbling]: I think I'd go in a little different direction, [Michael Helbling]: which is I get sort of this icky feeling or there's a threshold. [Michael Helbling]: I don't want to cross with AI in terms of relating to it. [Michael Helbling]: And what I mean by that is some of the LLM big companies put out research [Michael Helbling]: where they kind of take what the LLM is doing and equate it to emotion [Michael Helbling]: and telling you that basically if you behave around your AI a certain way, [Michael Helbling]: it may actually impact its performance and that's sort of what they're seeing.

[Michael Helbling]: And I think it's a really dangerous thing and I think it's also tricky to talk about [Michael Helbling]: because I don't want to advocate for being mean to your AI or whatever. [Michael Helbling]: But as humans, we anthropomorphize things really a lot. [Michael Helbling]: And so I think we very easily buy into this idea that I make my AI feel bad [Michael Helbling]: if I yell at it or I make it feel good if I tell it does a good job. [Michael Helbling]: But in reality, it feels nothing.

[Michael Helbling]: And most importantly is human to human interactions. [Michael Helbling]: I modify them a great deal based on what I know of that person [Michael Helbling]: and the empathy and the intuition I'm getting from that conversation. [Tim Wilson]: So if someone's struggling, I modify empathy and modifying Tim's going to need a definition of hang in there, [Michael Helbling]: and so you adjust to that person like if you're giving feedback, for instance, [Michael Helbling]: whereas if I'm giving feedback to an AI, I want to be as direct and succinct as possible [Michael Helbling]: without having to kind of couch it in a phraseology or terminology [Michael Helbling]: that keeps it secure in its own quote unquote emotions, which are not real.

[Michael Helbling]: And so for me, that's sort of a weird line that I think I'd love for us to avoid [Michael Helbling]: as we approach AGI. [Moe Kiss]: Can I ask a crowd question? [Moe Kiss]: Only if you can figure out how to get a mic to them. [Moe Kiss]: No, I was going to make you count the hands for a rough estimate.

[Moe Kiss]: Well, if you each take one and we take the average of each of your estimates, [Moe Kiss]: maybe we'll have a decent score. [Moe Kiss]: OK, creating an agent based on your stakeholder one, stakeholder two, stakeholder three, [Moe Kiss]: so that you can tailor your comms and have a persona built out for each of it. [Moe Kiss]: Like, I want to know how we feel about the ick factor of like, is that icky or is it thoughtful? [Moe Kiss]: Because anyway, I can finish my thoughts afterwards.

[Tim Wilson]: Sam Bert, would you like to answer that question? [Tim Wilson]: There was a whole session on that. [Michael Helbling]: So here's my take on that, because I learned about that yesterday in a session [Michael Helbling]: and I actually really quite liked it, because I look at AI as a tool to take [Michael Helbling]: information and position it in the best possible way for the audience that you're [Michael Helbling]: presenting it to, much like you would present maybe a slide deck to one person [Michael Helbling]: and a narrative to another based on how they consume or prefer data or information to be consumed.

[Moe Kiss]: Two notes. Just to be clear, I'm not picking on Sam. [Moe Kiss]: That was like very persona based. [Moe Kiss]: I'm talking about like someone in your team creates one that's like, this is Moee.

[Moe Kiss]: This is how she receives information, like very personalized. [Moe Kiss]: I think that's a bit different. [Tim Wilson]: So I think and I think there's two aspects. [Tim Wilson]: So I think Sam's and yours.

[Tim Wilson]: One, I think if it actually forces the person who's creating it, this is where we [Tim Wilson]: to actually really think about like to create it, you have to think about what do I need to? [Tim Wilson]: What do I know about Moee? [Tim Wilson]: What have I seen about Moee? [Tim Wilson]: Can I ask Moee something?

[Moe Kiss]: So that's like, but do you think that they would or do you think they would just be like, [Moe Kiss]: I'm going to upload 50,000 conversations, a bunch of Zoom transcripts, whatever of [Moe Kiss]: interactions with this person and you tell me what you think they're going to like. [Tim Wilson]: I think that's going to be less effective. [Moe Kiss]: Yeah, it would probably would be. [Tim Wilson]: And then the second part of that, I completely lost what my other thought was.

[Tim Wilson]: So on Brent. [Michael Helbling]: Well, a lot of these questions are tailored around a bunch of information. [Michael Helbling]: I uploaded about you three. [Michael Helbling]: No, I'm just kidding.

[Michael Helbling]: OK, we have another question coming from someone who's unfortunately not here. [Michael Helbling]: Joe Domoleschi, if you were stripped of your fancies tech stack and could only provide [Michael Helbling]: one specific deliverable to a stakeholder to prove the value of marketing analytics, [Michael Helbling]: what would it be? [Michael Helbling]: Live dashboard, a PDF report, a slide deck, a meeting with actionable insights, etc. [Michael Helbling]: What would you do?

[Val Kroll]: So one specific deliverable to prove the value of marketing analytics, [Michael Helbling]: just to clarify, that's what it says. [Michael Helbling]: Yeah, OK. [Val Kroll]: The results of an A.B.

[Michael Helbling]: test. So Format can be anything. [Val Kroll]: I mean, well, he said deliverable. [Val Kroll]: OK, so I would I would do a presentation, tight narrative results of an A.

B. [Val Kroll]: test. That would be my that's my no explanation. [Tim Wilson]: I think my not might not be a prove, but might be to convince or define.

[Tim Wilson]: I would probably go to some sort of compelling story that I was comfortable. [Tim Wilson]: I might have pulled data from various sources. [Tim Wilson]: I might have run an A.B.

[Tim Wilson]: test, but I would actually tell a really strong narrative and maybe with slides. [Tim Wilson]: Maybe not. I think that would actually be more convincing. [Val Kroll]: Like, why does said deliverable, that's your constraint.

[Moe Kiss]: But see, OK, this is the difference when I heard deliverable. [Moe Kiss]: I was like, it can be anything. [Moe Kiss]: And it sounds like you've both interpreted that in like agency [Moe Kiss]: consulting land very different to me, because I would have said [Moe Kiss]: if I could pick anything, it would be an MMM. [Moe Kiss]: Like, I can talk about that for weeks and months.

[Moe Kiss]: I mean, at some point, it becomes valid. [Moe Kiss]: But it would probably be an MMM. [Moe Kiss]: Like, I'd love to go through an experimentation tool, [Moe Kiss]: but I feel like that maybe is not in the spirit of the question. [Tim Wilson]: I don't know.

Yeah. [Tim Wilson]: What is it? What is a deliverable? [Michael Helbling]: We could get that was not the question.

[Tim Wilson]: No, it's what is the deliverable is. [Tim Wilson]: So now I found sound like a consultant. [Tim Wilson]: But I mean, on an MMM being super compelling, [Tim Wilson]: and I'm sitting like 15 feet from Jim Janolio. [Tim Wilson]: So and having heard him talk like you can you can conduct a great MMM.

[Tim Wilson]: You can you can build it and then you can deliver it horribly [Tim Wilson]: and doesn't show anything or you can communicate it really, really effectively. [Tim Wilson]: So it is kind of what is a deliverable [Tim Wilson]: and how effectively is it created and delivered? [Moe Kiss]: Or we could just combine all three and then we'd like be winning. [Moe Kiss]: If we're perfect, you didn't answer yourself.

[Michael Helbling]: I'm going to ask the next question. [Michael Helbling]: From a member of our audience, Bryce Preslicka. [Michael Helbling]: Preslicka. Preslicka.

[Brice Praslicka]: All right. [Brice Praslicka]: So I have a client that had some major data issues previously. [Brice Praslicka]: Once we got on to the project, we've cleaned things up. [Brice Praslicka]: We're in a much better state now.

[Brice Praslicka]: The problem is one of the clients, [Brice Praslicka]: POC's continues to act as though we have unreliable data. [Brice Praslicka]: And even worse, we have a member of our team that continues to use words [Brice Praslicka]: like discrepancy and lack of trust and keeps using words [Brice Praslicka]: that don't really help us accurately convey that it's reliable now. [Michael Helbling]: So I've sent memos. [Brice Praslicka]: I have tried to coach them to not use certain words, [Brice Praslicka]: but with both an internal team and a client that don't trust data [Brice Praslicka]: that is in much better spot now, how would you go about trying to regain trust?

[Val Kroll]: In the role of the client you're supporting, [Val Kroll]: are they on the business side or are they in an analytics role? [Tim Wilson]: They're in the business side. [Tim Wilson]: Well, now you have to provide an answer because he was just clear. [Tim Wilson]: So here, I'll kick us off.

[Michael Helbling]: There's no time for cash measures. [Michael Helbling]: Jeez, we're in a world of AI now and we need to move quick. [Michael Helbling]: First thing first, stop inviting the internal person to the meetings. [Michael Helbling]: So they can't screw you up.

[Michael Helbling]: Second, take charge of those meetings and tell the client [Michael Helbling]: that you know what you're talking about. [Michael Helbling]: And it's time to make decisions and get off the pot. [Michael Helbling]: What are they afraid of? [Michael Helbling]: No, I don't know if I could pull that one off.

[Michael Helbling]: But but, you know, start to form the communication [Michael Helbling]: and put it into the positive realm so you get past that moment. [Tim Wilson]: I I mean, this is going to sound easier than it is in practice. [Tim Wilson]: But to me, one of the things that AI has not helped [Tim Wilson]: we have struggled with for for 25 years is businesses [Tim Wilson]: that are looking for certainty and precision when there is actually [Tim Wilson]: they're operating under conditions of uncertainty.

[Tim Wilson]: And Jen Kunze's presentation yesterday, like it's like people think that, [Tim Wilson]: oh, the data, the data was never complete. [Tim Wilson]: The data was never perfect. [Tim Wilson]: It's really no better, no worse. [Tim Wilson]: We can always point to stuff that's not working.

[Tim Wilson]: So that like so to me, once you're having the discussion about is the data right? [Tim Wilson]: You're losing if you're using discrepancy. [Tim Wilson]: If it's, you know what? Hey, can we reset?

[Tim Wilson]: Can we really nail down the one or the two or the three biggest decisions [Tim Wilson]: you're trying to make? Don't worry about the data. [Tim Wilson]: Forget about the data. [Tim Wilson]: Yeah, it's going to be involved at some point.

[Tim Wilson]: I think a lot of times what happens, if you can really get them saying, [Michael Helbling]: what I really want to know is, is meta delivering results? [Tim Wilson]: And they're like, can't you keep crunching the data from meta? [Tim Wilson]: But I know there are gaps. [Tim Wilson]: Instead, you may say, really, let me talk to you about what a geo lift test is.

[Tim Wilson]: So it kind of goes back to that order taker versus partner. [Tim Wilson]: And it's it's tough. [Tim Wilson]: They're still working with you. [Tim Wilson]: So they have some level of trust.

[Tim Wilson]: But I think we wind up fighting the fighting on the wrong ground. [Tim Wilson]: We were on the ground of like, no, but the data is good enough. [Tim Wilson]: Well, no, but this and go, I know it's an asterisk and don't use this word. [Tim Wilson]: It's like, instead of like, we so quickly lose sight of it's such a [Tim Wilson]: tangible thing to point to that the data has a problem.

[Tim Wilson]: And we forget to say, what's the what do we really want to know [Tim Wilson]: and try to elevate that conversation? [Tim Wilson]: I often I think it's like, that's actually not the right data set for it. [Tim Wilson]: Anyway, we keep chasing the wrong data set to most answer that question. [Val Kroll]: I like that a lot.

[Val Kroll]: And the one point that you mentioned that I just expand upon is I think [Val Kroll]: the really rooting yourself in like, what level of certainty [Val Kroll]: is really required to answer this question? [Val Kroll]: How much time do I have to turn this around? [Val Kroll]: Is it something you need tomorrow? [Val Kroll]: Do I have a couple of months before you're going to make this call [Val Kroll]: and really just trying to line up the various different methodologies [Val Kroll]: that are at your disposal to bring that to bear to bring the right evidence [Val Kroll]: to that question?

[Val Kroll]: You know, Paula's presentation, like merging those different sources [Val Kroll]: of evidence to really kind of paint that picture. [Val Kroll]: I think can like shake people loose from like focusing on, you know, [Val Kroll]: what percentage of, you know, people are opting out from whatever cookie [Val Kroll]: banners and things like that, right? [Val Kroll]: So I think like just not trying to play on that, like move the battle, [Val Kroll]: I guess, not play on that turf and kind of say, hey, like let's just focus [Val Kroll]: on like Tim was saying, like those top those top questions [Val Kroll]: that you're really grappling with.

[Val Kroll]: And let's think about how much business risk we really be introducing [Val Kroll]: if it wouldn't be perfect. [Val Kroll]: So like, let's think about the various ways we can kind of go about it. [Val Kroll]: And sometimes just injecting a little creativity, if you will, [Val Kroll]: into the methodologies, into that conversation can kind of get them [Val Kroll]: excited about some different ways. [Val Kroll]: Maybe it's a user test.

[Val Kroll]: Maybe it's, you know, it's not going to be something [Val Kroll]: we're going to look for in a table as an example. [Tim Wilson]: So be sure to record the meeting and send them the meeting summary. [Tim Wilson]: Oh, for fuck's sake. [Moe Kiss]: I actually stayed very quiet on that one because this is an area [Moe Kiss]: I think Tim generally is normally right in.

[Moe Kiss]: Wait, why is everybody shaking their head now? [Moe Kiss]: But I do sometimes and I'm obviously in-house, so it's quite different. [Moe Kiss]: I do find if I have a stakeholder like that, [Moe Kiss]: I will almost always have one-on-one time with them. [Moe Kiss]: And I'll normally have some questions around like, [Moe Kiss]: what would have to be true for us to use this data source [Michael Helbling]: or, you know, are there other data sources [Moe Kiss]: that we could use to supplement the information [Moe Kiss]: so you'd be comfortable enough making a decision with what we have?

[Moe Kiss]: Like kind of trying to tackle it almost one-on-one, [Moe Kiss]: because especially soon as you get in a meeting with a bunch of people [Moe Kiss]: and everyone's like, oh, well, this data's wrong. [Moe Kiss]: So, you know, we're all stuck here [Moe Kiss]: and then everyone whinges about it for the rest of the meeting. [Moe Kiss]: It like it stops being productive. [Moe Kiss]: And so I would almost be trying to like really partner with that, [Moe Kiss]: like the biggest doubter of the group especially [Michael Helbling]: and build up that relationship and really work with them on [Moe Kiss]: some of the methods that Tim and Val are talking about here [Moe Kiss]: so that then they can also become your advocate, hopefully, over time.

[Michael Helbling]: Excellent. All right. [Michael Helbling]: Here's another question we got. [Michael Helbling]: Everyone at my company is being tasked [Michael Helbling]: with showing specific efficiency improvements [Michael Helbling]: they've delivered using AI.

[Michael Helbling]: I'm an analyst who supports marketing. [Michael Helbling]: What are some ideas you have that I could do for that? [Michael Helbling]: Don't make me do the Hollywood Squares one again. [Tim Wilson]: I just feel like this.

[Tim Wilson]: I'm starting to feel like we've beaten this particular horse. [Michael Helbling]: What do you mean, AI or efficiencies? [Tim Wilson]: Well, well, yeah, I mean, the AI piece and the big, [Tim Wilson]: I guess the my my qualm with the efficiencies [Tim Wilson]: and I totally recognize the person asking the question. [Tim Wilson]: They don't have control over that.

[Tim Wilson]: That's being pushed down and it's an organizational challenge. [Tim Wilson]: But efficiency is like producing more with the same [Tim Wilson]: or producing more with the less or producing the same with the less whatever. [Tim Wilson]: And it's like more what and and moving down the path of saying, [Tim Wilson]: well, we're we're producing more dashboards faster. [Tim Wilson]: We're responding to requests faster [Tim Wilson]: and everybody feels resource constrained [Tim Wilson]: and like we can't hire we can't double our headcount.

[Tim Wilson]: So AI is going to help us keep it fixed. [Tim Wilson]: And I think this is where I'm feeling like I'm beating a dead horse [Tim Wilson]: and I am the dead horse. I don't know that that has this idea that if we [Tim Wilson]: its volume, volume is the issue that we just need to generate more. [Michael Helbling]: But that volume of whatever we're producing is going to someone.

[Tim Wilson]: Like there's there's value in the friction, [Tim Wilson]: which does not make me an AI skeptic. [Tim Wilson]: I just think the efficiency part is really, really tricky. [Tim Wilson]: You know, I think I've seen that in articles [Tim Wilson]: that that's happening across a lot of companies are saying, [Tim Wilson]: we're just trying to make this as a actually Jim talking on, [Tim Wilson]: I think day one was showing like this is just a chase for headcount reduction [Tim Wilson]: and something's not right there.

[Michael Helbling]: So you you managed to answer that without giving this poor person any tips [Michael Helbling]: on how to do their job. [Val Kroll]: They should have been a marketing analytics woman. [Val Kroll]: Yeah, that's right. [Michael Helbling]: There's a lot of tips there.

[Moe Kiss]: Can I jump in, though? [Michael Helbling]: He helps. [Moe Kiss]: I learned this recently and I'm still kind of reconciling it. [Moe Kiss]: So I'm going to obviously tell a bunch of people the exact advice I got.

[Moe Kiss]: And we can all try it out, report back to me. [Moe Kiss]: Uh, I got some advice recently, essentially, like sometimes [Moe Kiss]: you just suck it up and you do it and a lot of conversations around [Moe Kiss]: AI at the moment are about productivity gains, not quality gains. [Moe Kiss]: And I find that just it gives me the ick. [Moe Kiss]: However, there comes a point where sometimes you're in a position [Moe Kiss]: and you just suck it up and you do it and you go, oh, my God, [Moe Kiss]: my team saved five hours a week.

[Moe Kiss]: Here's all the dot points, send it up to leadership, move on with your life. [Moe Kiss]: And then you get your team together and say, OK, let's have a conversation [Moe Kiss]: about how we improve the quality of our work. [Moe Kiss]: That's what matters here. [Moe Kiss]: So sometimes the signal you send up doesn't have to be the same [Moe Kiss]: as the signal you send down, but you better be smart about how you do it [Moe Kiss]: and don't get caught.

[Tim Wilson]: But you're setting yourself up to actually send a better signal up [Tim Wilson]: down the road, right? [Tim Wilson]: So I love that for doing both. [Moe Kiss]: Yes, obviously, team that was the grand plan. [Tim Wilson]: Check the box, but then separately say, but here's the real value we got.

[Tim Wilson]: And yeah, yeah. [Michael Helbling]: And we've been battling a problem like this since forever. [Michael Helbling]: I mean, there used to be a time in our industry when we thought [Michael Helbling]: if we collected every single piece of data, we would somehow magically know more. [Michael Helbling]: And it sort of is a redux of a similar way of thinking.

[Michael Helbling]: And so we have to kind of manage through it effectively. [Michael Helbling]: All right, we've got another question, and this one comes from also [Michael Helbling]: someone in the audience, Sam Burge. [Tim Wilson]: I think Michael surprised himself and didn't realize he should have [Tim Wilson]: already been on the move. [Michael Helbling]: So we'll fix that in post.

[Sam Burge]: How do you think analytics teams will look differently from today with AI? [Tim Wilson]: In the future. [Tim Wilson]: I mean, I I hope that on the one hand, they are still spark, curious, [Tim Wilson]: business thinking, technical kind of have a broad set of skills. [Tim Wilson]: So I don't think the teams will necessarily look a whole lot different.

[Michael Helbling]: How they work, they're obviously going to get, I guess, efficiencies [Tim Wilson]: and changing ways of working and become more prepared. [Michael Helbling]: But that's a tough one. [Tim Wilson]: Why did I jump in and answer that? [Michael Helbling]: I don't think I had a good I was just buying time for one of you guys [Tim Wilson]: to say something smart.

[Moe Kiss]: I don't know about. [Moe Kiss]: OK, this is my guesstimate. [Michael Helbling]: Yeah. [Michael Helbling]: And this is what I'm observing within my own team.

[Moe Kiss]: It seems like folks are kind of splitting a little bit. [Moe Kiss]: There are the folks that are going much more technical. [Moe Kiss]: I would almost, to some degree, even a little bit more specialized. [Moe Kiss]: And then there are the folks that it feels like the chasm [Moe Kiss]: between the technical and more the like business facing [Moe Kiss]: generalist is getting a little bit wider.

[Moe Kiss]: I don't necessarily see that as a bad thing. [Moe Kiss]: I think when folks have a particular strength in one direction, [Michael Helbling]: like we should encourage that. [Moe Kiss]: And that's a great thing. [Moe Kiss]: I do think it makes it harder for like teams [Moe Kiss]: and how they work together and all of that sort of stuff.

[Moe Kiss]: I had a massive rant a little earlier today [Moe Kiss]: because I am sick of reading very shitty, long documents [Moe Kiss]: which were based on someone's shower thought [Moe Kiss]: that never should have left the shower, [Moe Kiss]: but now is in a four thousand word document [Moe Kiss]: and being flung around our organization. [Moe Kiss]: And then someone else comes in and writes 50 comments on it. [Moe Kiss]: And then someone's like, over to you now, Moee. [Moe Kiss]: And I'm like, what do you want me to do with this?

[Moe Kiss]: I am now doing all of the thinking work of having to read it. [Moe Kiss]: And it's pretty like watery garbage, [Moe Kiss]: having to like respond, [Moe Kiss]: also trying to figure out what you want me to do with this [Moe Kiss]: because it was a shower thought bubble. [Moe Kiss]: And what my hope of where we get to [Moe Kiss]: is that it actually helps us think more critically, not less. [Moe Kiss]: I think we're in the shitty stage right now.

[Moe Kiss]: I'm optimistic. [Moe Kiss]: I'm going to bitch about the shitty stage we're in right now [Moe Kiss]: because it is shit, reading all these documents. [Moe Kiss]: But I am optimistic that with time it will help us [Moe Kiss]: think better about what we do. [Moe Kiss]: Like, I don't know, you're creating a hypothesis, [Moe Kiss]: like instead of having to tap your co-worker, [Moe Kiss]: you can like sense check, [Moe Kiss]: have I got all the key components that I need to have [Moe Kiss]: a really strong hypothesis for this experiment?

[Tim Wilson]: No, I think even like knowledge management, the ability [Tim Wilson]: because AI is helping so much with unstructured data, [Tim Wilson]: the calling through what has happened in the past. [Tim Wilson]: But it feels like it is an elevated role [Tim Wilson]: for what a great analyst should be doing five years ago [Tim Wilson]: is still the same, which is being deeply embedded [Tim Wilson]: in the business context and the business needs. [Tim Wilson]: It's been historically very hard to get the historical [Tim Wilson]: what have we done.

[Tim Wilson]: So I think some of those like the preparation, [Tim Wilson]: the pulling this together, using the tools, [Tim Wilson]: but I don't think it should change from what I think [Tim Wilson]: great analysts are doing, [Tim Wilson]: which is still having a deep connection to the business. [Tim Wilson]: It's a shifting kind of tool set. [Moe Kiss]: Can I just also add, Sam, [Moe Kiss]: one of the things I actually loved about your presentation [Moe Kiss]: was the idea also that we can change the format [Moe Kiss]: very quickly to suit different types of people.

[Moe Kiss]: Like I am an audio person. [Moe Kiss]: I would absolutely listen to a podcast on business metrics. [Tim Wilson]: I just remembered at the second point [Tim Wilson]: I was going to make back on that question. [Michael Helbling]: All right, fine.

[Moe Kiss]: Was this like from 10 minutes ago or? [Moe Kiss]: It was, but it was on that. [Tim Wilson]: It was asking, trying to figure out the best way [Tim Wilson]: that's what somebody would, how to respond to them. [Tim Wilson]: So when you said the audio person, [Tim Wilson]: how often do people actually know themselves?

[Tim Wilson]: So for all the listeners or anyone who wasn't in Sam's session, [Tim Wilson]: it was the, you know, there's the marketing person who says, [Tim Wilson]: I just want to have my cup of coffee [Tim Wilson]: and listen to the podcast. [Tim Wilson]: And there's a little trigger in me that thinks [Tim Wilson]: sometimes we seldom really know ourselves. [Tim Wilson]: So differentiating between somebody who thinks [Tim Wilson]: that's what they would want [Michael Helbling]: and someone who actually that would be effective.

[Tim Wilson]: And that had rang true [Tim Wilson]: from what we've dealt with for a hundred years. [Tim Wilson]: We've had people saying, I just need a dashboard that does X [Tim Wilson]: and we deliver them the exact dashboard. [Tim Wilson]: And they're like, this isn't helpful. [Tim Wilson]: Where's this other thing?

[Tim Wilson]: So there's this other layer [Tim Wilson]: that I think analysts historically have needed to follow. [Tim Wilson]: And the same thing opening up [Tim Wilson]: all these different formats is great. [Tim Wilson]: But what somebody says would work. [Tim Wilson]: And I think you have to deliver it to them.

[Tim Wilson]: But figuring out like, does that actually work? [Tim Wilson]: And giving them the opening, if they said, [Tim Wilson]: oh, I thought that would be really cool. [Tim Wilson]: And you tweaked and tuned the tone [Tim Wilson]: and the content and everything, [Tim Wilson]: but giving them the out to say, [Tim Wilson]: you know what that actually didn't work. [Tim Wilson]: I don't know that I wouldn't have known [Tim Wilson]: it wasn't gonna work until I actually tried it for a while, [Tim Wilson]: which we have not done in the industry very well forever.

[Tim Wilson]: We get in sort of a whiny mode of saying, [Tim Wilson]: we've given them all these dashboards [Tim Wilson]: and they're not using them. [Tim Wilson]: And it becomes this adversarial thing because, [Tim Wilson]: and then if we ask them, don't you want these dashboards? [Tim Wilson]: Well, they ask for them. [Tim Wilson]: Of course they're gonna say, yeah, yeah, yeah, [Tim Wilson]: this is really useful.

[Tim Wilson]: We haven't figured out how to say, [Tim Wilson]: no, that mechanism didn't work and it's okay. [Tim Wilson]: And we need to have the trust [Tim Wilson]: and we need to try something different. [Tim Wilson]: So we can go back and that was my other point. [Tim Wilson]: Maybe we should let, I'll get a word in and twice.

[Val Kroll]: Back to how do we think teams will change? [Val Kroll]: I think that there's gonna be some new muscles [Val Kroll]: that are built. [Val Kroll]: I think one of the things that we had been talking about [Val Kroll]: this conference is how this has given us [Val Kroll]: a lot of energy and excitement. [Val Kroll]: And I think that there's been some creativity injected, [Val Kroll]: which I think is just fun.

[Val Kroll]: Even if we're just talking about little things [Val Kroll]: that we do on the side that's not ready for prod, [Val Kroll]: but it's just kind of like stretching us [Val Kroll]: in some new ways, which I really appreciate. [Val Kroll]: The other thing that we were also talking with you about, [Val Kroll]: Sam or you and I were chatting about, [Michael Helbling]: is the communication skills [Val Kroll]: and how that's gonna be improving. [Val Kroll]: Because I think how often have you been in a conversation, [Val Kroll]: even over the past couple of days, [Val Kroll]: perhaps where people are just ragging on their stakeholders, [Val Kroll]: like, oh, they're so dumb, they just don't get it, right?

[Val Kroll]: And it's like, when you're prompting [Val Kroll]: and you're talking about something you need the AI [Val Kroll]: to do for you and it totally misses the boat, [Val Kroll]: and you're like, oh, geez, [Val Kroll]: I've totally forgot to give you this piece of context. [Val Kroll]: Of course you didn't understand what I was trying to say. [Val Kroll]: Think about your poor stakeholder [Val Kroll]: that you were not giving that context [Val Kroll]: for how many years.

[Val Kroll]: The video of, we were talking about this, [Val Kroll]: the dad with his son and daughter [Val Kroll]: about making the peanut butter and jelly sandwich, [Val Kroll]: about like, take the bread out of the bag [Val Kroll]: and he's like trying to, [Val Kroll]: and he like ends up like putting the knife [Val Kroll]: through the whole loaf of bread, whatever, [Val Kroll]: because he was just trying to follow the directions. [Val Kroll]: But I think it can help us build a little empathy [Val Kroll]: for our stakeholders, [Val Kroll]: because like, they're not wired the same way we are, [Val Kroll]: they don't have the same background that we do.

[Val Kroll]: And so I think it's one of the byproducts [Val Kroll]: that will help us become better communicators [Val Kroll]: and hopefully have a little bit more empathy [Val Kroll]: for people who don't make all the immediate connections [Michael Helbling]: that our brains do just because we're nerds. [Michael Helbling]: I think organizationally, [Michael Helbling]: I think we'll see departments flatten out a little bit. [Michael Helbling]: Like over the last 15 years, [Michael Helbling]: we've become super specialized [Michael Helbling]: in a lot of different disciplines, [Michael Helbling]: because analytics is actually multidisciplinary.

[Michael Helbling]: And I think AI will push that back together a little [Michael Helbling]: in a lot of organizations. [Michael Helbling]: And then those organizations over time [Michael Helbling]: will start to realize there's still a need [Michael Helbling]: for some of that specialization on the fringes, [Michael Helbling]: and they'll find ways to bring it back in. [Michael Helbling]: But I think we'll all express experience, [Michael Helbling]: some compression where an analyst will go back [Michael Helbling]: to being able to code something [Michael Helbling]: and also write a data pipeline [Michael Helbling]: and also go access the data lake [Michael Helbling]: and also build a dashboard and a great visualization.

[Michael Helbling]: And those were all things that like analytics people [Michael Helbling]: were attempting to do 15, 17 years ago. [Michael Helbling]: And then we realized we needed specialization. [Michael Helbling]: We needed a data engineer. [Michael Helbling]: We needed analytics engineer.

[Michael Helbling]: We needed a data visualization expert. [Michael Helbling]: And I think we'll begin to flatten those out with AI. [Moe Kiss]: That doesn't worry me a bit though. [Michael Helbling]: I don't say it's good or bad.

[Michael Helbling]: I just think that's what will happen. [Moe Kiss]: Like I feel like sometimes folks are over indexing [Moe Kiss]: on the generalization at the moment [Moe Kiss]: and thinking that, I don't know, [Moe Kiss]: a product manager can do a data scientist job, [Moe Kiss]: and I mean, some product managers [Moe Kiss]: is doing engineering jobs. [Moe Kiss]: Also interesting choices. [Moe Kiss]: So I think we're over indexing [Moe Kiss]: on the fact that folks can generalize.

[Moe Kiss]: And I heard there's a like- [Michael Helbling]: Outcomes follow expertise, even with AI. [Michael Helbling]: Okay, we have time for one more question. [Michael Helbling]: And that's our last question. [Michael Helbling]: And we have someone who is an audience member [Michael Helbling]: who's going to ask it and it's Jim Stern.

[Michael Helbling]: My question is, what are the first three skills [Jim Sterne]: that analysts have mastered [Jim Sterne]: that are going to be successfully taken over [Jim Sterne]: by artificial intelligence? [Val Kroll]: I wish we could get a question about AI. [Val Kroll]: No shade, Jim. [Val Kroll]: Just looking at Michael.

[Val Kroll]: First three skills, say it again. [Val Kroll]: First three skills. [Val Kroll]: Sorry, I was being an asshole. [Val Kroll]: First three skills.

[Michael Helbling]: What are Tim's favorite skills? [Michael Helbling]: So, probably like the, what is it? [Michael Helbling]: The ink to data ratio. [Michael Helbling]: So that probably going to be the first thing AI takes over.

[Val Kroll]: Data pixel ratio. [Val Kroll]: Data pixel ratio. [Michael Helbling]: I was paying attention, Tim. [Michael Helbling]: SQL, I don't write SQL anymore.

[Tim Wilson]: I am so much more on the debugging SQL debugging R. [Tim Wilson]: I think debugging coming over really, really quickly. [Tim Wilson]: I think a second one would be [Tim Wilson]: QA'ing or validating or vetting the results of an analysis, [Tim Wilson]: having that the thing that you're supposed to go [Tim Wilson]: to another analyst or try to come at it a separate way. [Tim Wilson]: I'm not sure what the third one is.

[Tim Wilson]: I think it's a lot of things that are going to be [Tim Wilson]: supplemental that we should be doing. [Tim Wilson]: Like not doing the QA, but giving me the list of, [Tim Wilson]: check my logic. [Tim Wilson]: Check the things that I, [Tim Wilson]: so maybe it's not what the junior analyst is doing. [Tim Wilson]: I think it's what the junior analyst ideally is working [Tim Wilson]: with another junior analyst or senior analyst [Tim Wilson]: to look over and review.

[Tim Wilson]: There's not a whole lot that I see [Tim Wilson]: a whole hard, whole hog hand in the keys over on. [Michael Helbling]: I came up with three, [Michael Helbling]: but I don't know if they fit the criteria. [Michael Helbling]: We'll have to go from there, [Michael Helbling]: but that's going to be where we have to wrap up. [Michael Helbling]: And I want to say first, a huge thank you.

[Michael Helbling]: To Jim Stern for organizing the marketing analytics summit. [Michael Helbling]: 45 years. [Michael Helbling]: And save your applause because also to all of you [Michael Helbling]: for being here and bringing your energy [Michael Helbling]: and your questions, your insights and experiences [Michael Helbling]: in a world changing daily with AI, it's the people, [Michael Helbling]: the community and human connection in our industry. [Michael Helbling]: It feels all that much more special and crucial [Michael Helbling]: in these changing times.

[Michael Helbling]: And obviously there's a huge audience also listening [Michael Helbling]: and we'd love to hear from you too. [Michael Helbling]: And you can reach us at our LinkedIn page [Michael Helbling]: or the measure slack chat group [Michael Helbling]: or by email at contact at analyticshour.io. [Michael Helbling]: Please leave comments, ratings and reviews [Michael Helbling]: on whatever platform you use to listen.

[Michael Helbling]: We do read all of them. [Michael Helbling]: And Tim brings them up in meetings. [Michael Helbling]: And I think- [Moe Kiss]: It makes us set KPIs. [Michael Helbling]: Yeah, it's terrible.

[Michael Helbling]: I can't wait till AI replaces that. [Michael Helbling]: All right, and I know that I speak [Michael Helbling]: for all of my co-hosts, Val, Tim, Moe. [Michael Helbling]: When I say, no matter the question or challenge [Michael Helbling]: you're currently solving, keep analyzing. [Announcer]: Thanks for listening.

[Announcer]: Let's keep the conversation going with your comments, [Announcer]: suggestions and questions on Twitter at analyticshour, [Announcer]: on the web at analyticshour.io, our LinkedIn group [Announcer]: and the measure chat slack group. [Announcer]: Music for the podcast by Josh Crowhurst. [Charles Barkley]: Those smart guys want to fit in.

[Charles Barkley]: So they made up a term called analytics. [Charles Barkley]: Analytics don't work. [Charles Barkley]: Do the analytics say go for it [Charles Barkley]: no matter who's going for it? [Charles Barkley]: So if you and I were on the field, [Charles Barkley]: the analytics say go for it.

[Charles Barkley]: It's the stupidest, laziest, lamest thing [Charles Barkley]: I've ever heard for reasoning in competition. [Jim Sterne]: Ladies and gentlemen, that is so much fun. [Jim Sterne]: Thank you so much for be adding the spark [Jim Sterne]: to the end of the marketing analytics summit. [Jim Sterne]: You guys are awesome.

[Tim Wilson]: Rock flag and AI gives me the ick. [Jenn Kunz]: Yeah. [Michael Helbling]: Yeah. [Michael Helbling]: Yeah.

[Michael Helbling]: Yeah. [Michael Helbling]: Yeah. [Michael Helbling]: Yeah. [Michael Helbling]: Yeah.

[Michael Helbling]: Yeah. [Michael Helbling]: Yeah. [Michael Helbling]: Yeah. [Michael Helbling]: Yeah.

[Michael Helbling]: Yeah.