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00:00:29.603Hello everyone, Welcome to another special episode of OpsCast brought to you by MarketingOpscom.
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00:00:35.061I'm your host, Michael Hartman, joined today by my two compatriots Naomi Liu and Mike Rizzo.
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00:00:37.932Happy New Year, Happy.
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00:00:40.299New Year, yeah, for years.
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00:00:48.478So we are getting together, getting the band back together, which we don't get to do as often as I'd like.
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00:00:50.942I mean, I miss, I miss talking to you guys regularly.
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00:00:59.377So I miss you too, michael thank you, um, but this is we.
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00:01:06.353We kind of realized that we are about to hit four years of doing this podcast, so we started in.
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00:01:10.352If I remember, mike is this, is it your birthday, january?
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00:01:20.033it's like the day before my birthday okay, so you know happy birthday, mike yeah, a little bit early um we started doing a cameo
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00:01:24.617that year sent him a cameo yeah yeah, oh, did somebody do that?
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00:01:25.859Yeah, michael.
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00:01:36.021Tucker actually uh like organized um that, oh gosh, the co-founder of uh Apple um did a cameo.
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00:01:38.674It was actually kind of fun and special.
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00:01:41.542Oh, that is too funny yeah.
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00:01:43.114Wow I forgot about cameo.
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00:01:44.790Maybe that'll be part of.
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00:01:55.572What we talk about is like all the things that have changed since january of 2021 what was the thing with all the audio experiment, the audio chat room thing that was happening?
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00:01:59.703yeah, when oh oh, what was that call?
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00:02:00.846Now I'm so curious.
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00:02:03.751Oh good gosh, I know you're talking about.
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00:02:05.094I never understood what it was.
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00:02:11.852Yeah, you, you figured out, but I but I remember, like I when we started this clubhouse.
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00:02:14.897That was it did you ever do it?
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00:02:16.602Did you ever join a clubhouse session?
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00:02:20.865I joined one or two I never did, trying to see what happened.
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00:02:25.622I never quite understood how that they should have sold the second that they got that offer.
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00:02:27.849Oh yeah, it's a lot of money?
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00:02:28.038no, I don't know.
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00:02:28.257They got an offer.
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00:02:28.971Oh yeah, it's a lot of money they get offered.
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00:02:42.693No, I don't know, they got an offer to get acquired like right away by like pretty quickly, but I think it was like by x at the time, twitter right, or maybe somebody else, I don't remember, but they turned it down, should it take that's crazy, yeah.
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00:02:46.358So think back four, four years ago, 2021.
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00:02:53.165We were still kind of kneeling from the covid and the lockdowns and all that.
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00:02:56.336And we, when we started do you remember this?
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00:02:58.641We started as a, as a like talk radio.
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00:02:59.951Right, it was a live show.
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00:03:01.074We had an audience.
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00:03:07.591As much as we tried to get people to come on in in real time, you know, to join us.
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00:03:08.612That didn't they mean it was.
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00:03:10.356The online chat part was good.
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00:03:11.399We still had that interaction.
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00:03:13.584Uh, yeah, it was fun.
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00:03:14.854I liked that.
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00:03:26.973I liked that aspect of the show and it it sort of became the DNA of why the show is what it is today, like this raw sort of unfiltered discussion, I mean for our listeners.
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00:03:45.010If you're listening to this episode, you know there's a quite a bit that goes into doing a show as you might imagine um, but, like you know, some prep work right, like hartman does an incredible job of uh, getting on and saying, hey, what should we talk about with you?
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00:03:45.973What's your passion, what's your?
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00:04:02.239And there's a bit of an outline that we follow, but generally it's just sort of a loose discussion and it's meant to go exactly wherever it needs to go, like a live radio show, and that's where the DNA of our show came from.
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00:04:07.219Yeah, I don't know, but I think that I enjoyed that aspect of it.
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00:04:08.875Those were fun days.
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00:04:17.735I think it was it, was it was at the Daryl Alfonso episode, we had where, like in a fire alarm or something, went off in the background.
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00:04:22.220Yeah, his literal smoke alarm went off and we didn't mute it.
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00:04:27.093Yeah, and Michael, I think you and I were on one where, um, I can't remember who it was, was it AJ?
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00:04:28.598I think you and I were on one where I can't remember who it was.
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00:04:28.800Was it AJ?
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00:04:39.098Might not, it might've been, I can't remember who it was, but someone had a, a baby, like alarm that went off, that saying like twinkle, twinkle little stars.
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00:04:43.418Yeah, the entire episode and we couldn't figure out where it was coming.
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00:04:50.172That was not AJ oh right, it's like I don't know the kid.
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00:04:50.712What are you?
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00:04:52.316talking about no.
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00:04:54.440What's his name?
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00:05:04.650Raja, raja, yes, yes it was like a very low level twinkle, twinkle little stars that played the entire episode and I was like, is that coming from my neighbor's house?
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00:05:05.552Like where is that Right?
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00:05:07.092I remember that.
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00:05:10.235We were just trying to lull everybody to sleep.
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00:05:11.995You know it's so funny.
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00:05:13.616Yeah, all those things you know.
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00:05:15.979But I think it's I don't know.
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00:05:25.304Yeah, I'm sure that sometimes that's distracting or annoying, but to me it's part of the like, it's just part of the ethos.
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00:05:26.806I'm glad we keep it that way.
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00:05:29.407I you know, I think there's trade offs.
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00:05:30.288Either way, right you can.
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00:05:47.918You can really do a lot of work to to clean things up and uh, totally, yeah, Do all that kind of stuff and it's, we say it's a, we say it's a show, that's so you know, we are marketing operations professionals by trade.
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00:05:50.020We are not podcast producers by trade, right?
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00:05:55.451Uh, thankfully the tools are helping us make it a little bit easier a little bit better.
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00:06:04.980Although I don't know about you, I I have had a couple of people ask me for, like they, I want to start a podcast.
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00:06:06.461What can you tell me about it?
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00:06:07.543Right, what you know?
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00:06:27.552totally so I mean, I will say that we have learned a lot about what it takes to spin one up, and I think we, I think if we were to take a stab at revamping the show or launching another show, we would probably do it differently this time, probably partially because it's just interesting to try a different approach, right?
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00:06:31.120Absolutely but but yeah, I think there's a lot of learning.
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00:06:35.754I get that question a lot, though, michael, like what tool do you use to publish?
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00:06:36.736How do you distribute?
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00:06:38.762You know all that kind of stuff.
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00:06:47.020Yeah, to answer that question for all of you, uh, we record on riverside, shout out to them thanks for the product, it's been great.
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00:06:49.224Yep, we pay for it.
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00:06:59.732They don't give it to us, uh, and we publish and distribute to all of the media streams that you are tuning in from via buzzsprout.
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00:07:05.383So, yeah, that's how we do it, but oh, and, we do a bit of editing in descript.
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00:07:16.581Yep, to like truncate any dead space if we have dead space, or whatever they're our podcasting tech stack yeah, that's our podcasting text texting.
00:07:17.703 -->
00:07:25.052There's a hubspot rss email that goes out once a month to those that are subscribed with the last episodes that went live in the prior month.
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00:07:27.297There you go and comes from.
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00:07:28.519Does it say it's coming from me?
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00:07:30.864I think it still says it comes from you.
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00:07:36.998Yeah, because I remember the first time one came out and I was like oh, look at that, I'm sending somebody, sending myself an email.
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00:07:40.394Gotta love automation.
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00:07:41.599That's right.
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00:07:45.158Yeah, but it's, I'm with you.
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00:07:56.086I think we've covered a lot of ground in terms of different topics and, yeah, but I'm with you, I think we've covered a lot of ground in terms of different topics and it was clearly well, it's interesting because I think there's a lot of topics we've covered.
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00:08:02.423There's a lot of things that we all have passion about that I think we'd like to cover more, maybe even.
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00:08:22.701So, yeah, we're always open to new ideas and I mean the biggest to me, the biggest, one of the biggest changes right now is just, yeah, I'm still I'm starting to see more of our guests or potential guests, people who've raised their hands or said had interest, bringing up things like AI.
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00:08:31.792We've had some great conversations with people talking about mental health and Naomi you, health and uh, naomi, you, you had.
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00:08:37.464Well, we also we didn't have Mopsapalooza or summer camp before we started all this stuff.
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00:08:39.875So that's all new.
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00:08:50.764Yeah, I mean in terms of like topics to cover, right, I think we've had a really amazing and varied range of guests and topics that have come across the show.
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00:09:38.057I think something that was eye-opening for me was during this past MOPSA, where Audrey and I hosted the women's breakfast, mopsa Mimosas that we had an intake forum where women who were interested in coming to this breakfast was still in an intake forum with just some information about what they wanted to talk about and a lot of recurring themes around diversity in the workplace, leaning in, getting a seat at the table, work-life balance, mental health those were all recurring themes that a lot of the attendees those were all recurring themes that a lot of the attendees wanted to discuss and talk to other women at their table for networking on those topics.
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00:09:51.333So I think it would be good to explore some of those topics as well for future episodes for this year, whether it be, you know, having a maybe we have like a roundtable with some of the women who came to the women's breakfast or we bring in a guest speaker.
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00:10:04.221I don't know what that looks like, but um, yeah, I just think that would be something that would be really interesting for some of our listeners y'all need to do the women take over thing again, like we had the women yeah, that would be really fun time we need to do.
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00:10:06.153Yeah, that would be.
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00:10:14.231We should extend it to like the whole month, though like yeah, we could do that you just run it for like the whole, like four weeks, for at least four episodes or something.
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00:10:19.262I'm done with that, yeah yeah, it makes my job a little easier.
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00:10:30.189Yeah I was looking at our uh, our stats all time stats for for top downloads.
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00:10:37.961I'm sure we shared some of these things in a social post, but for those of you that have been diehard listeners and fans, first of all, thank you.
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00:10:38.822Yes.
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00:10:45.156Second of all, top stats what the fuck is marketing operations with Amy Goldfrey?
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00:10:54.238Still, it's two years, it's over two years old, it went live june 14, 2022 and it is 784 downloads.
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00:10:56.966So shout out to amy for that's right.
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00:10:59.992Awesome episode that obviously resonates to this day.
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00:11:03.098Uh, what else is on here?
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00:11:08.217The evolution of marketing ops in the age of generative digital experience with paul wil.
00:11:08.217 -->
00:11:09.601That's about a year old now.
00:11:09.601 -->
00:11:13.420It's actually over a year old from July 24th of 2023.
00:11:13.420 -->
00:11:15.554I'll give you the top five.
00:11:15.554 -->
00:11:16.197We'll stop there.
00:11:16.197 -->
00:11:20.201A marketing ops maturity model and more with Simon Daniels.
00:11:20.201 -->
00:11:24.120So analyst extraordinaire, simon Daniels came on.
00:11:24.120 -->
00:11:24.661That was great.
00:11:24.661 -->
00:11:26.317That was May 22, 23.
00:11:26.317 -->
00:11:28.736That has 616 downloads.
00:11:28.736 -->
00:11:34.595Uh, the great attribution debate with andrea lb, andrew smith.
00:11:34.595 -->
00:11:39.403Uh, can't get enough of andrea andrew throw down, that was a fun one.
00:11:40.310 -->
00:11:46.261Um, that is almost two years old as of march 27, 2023, and it's 558 downloads.
00:11:46.261 -->
00:11:52.975And to round us out, bring us home top five is attribution ruining marketing with carrie picklesimer.
00:11:52.975 -->
00:11:57.429And that one is over two years old, september 19th of 2022.
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00:12:01.238So apparently we didn't know what we were doing in 2021 at all.
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00:12:02.982Uh, because, no, I'm just kidding.
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00:12:15.534The next one on the list is from 2021 yeah, yeah, when our very first episode is is just a scooch under uh, scooch, is that the right word just under 500 downloads.
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00:12:30.797So I mean, for that's another thing, for that I tell people all the time starting out doing this, I would have assumed that how was how how many podcasts and stuff there are, that the metrics would be incredible and they're pretty terrible.
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00:12:33.077Yeah, oh yeah.
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00:12:36.999The way that you get reporting from these tools, yeah, it's horrible.
00:12:36.999 -->
00:12:43.096You can't tell hardly anything unless you go to a specific streaming provider to get stats or whatever.
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00:12:49.372Right and it's partial at that point, yeah, which to me like.
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00:13:09.742So one of the things that we occasionally get is feedback from people, and we've been fortunate enough that most of it's been positive, almost all of it's been positive, and I always thank those people, because we really don't get anything else.
00:13:09.742 -->
00:13:15.482Like it's really you're sort of throwing this out into the ether and you don't know if it's landing, you know.
00:13:15.482 -->
00:13:17.658So it's always nice to get that feedback.
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00:13:29.879Yeah, yeah, I mean good or bad, right, like we always want to hear from everybody, but it's so rare to get either yeah, and so we appreciate whatever we get from anybody.
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00:13:34.640So it's been yeah, it's been a lot of fun.
00:13:34.760 -->
00:13:46.439I do know I spoke to one of our community members recently who I shall run remain nameless, and she said she's a long time listener.
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00:13:59.242I'm hopeful to have her on the show soon, but, um, a lot of like the content, the guests that have come on um, so all of you who've ever been guests, like thank you.
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00:14:27.404She uh and and she joined the community um, she has now built her career around all of the advice coming from everybody in this community across and it really like a lot of it stemmed from her discovery of uh, this podcast and and she ended up joining the live workshop with um uh, one of our instructors and she.
00:14:27.404 -->
00:14:36.353It was a leadership workshop that she took and she discovered that because of this podcast and she now feels even more equipped to take on a new leadership role in her organization.
00:14:36.353 -->
00:14:50.110I mean, she's literally like bolstered so much of of her career around everybody supporting her from the content you all contribute on the show, right, absolutely, if it's who I think you're talking about.
00:14:50.130 -->
00:14:55.182I do believe we have that person scheduled for an episode, so oh yeah, that's all.
00:14:55.182 -->
00:14:57.012Stay tuned that's great.
00:14:57.634 -->
00:14:59.136So anyway, the point of me sharing.
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00:15:00.559That is that it's.
00:15:00.559 -->
00:15:08.641It's awesome that, though we rarely get the feedback, occasionally, weasionally we get inspirational moments like that.
00:15:08.641 -->
00:15:13.621And yeah, and I hope we all hope that this is helpful.
00:15:13.621 -->
00:15:16.235This stuff is helpful to you, yeah.
00:15:18.400 -->
00:15:20.395I don't know, definitely a labor of love.
00:15:20.395 -->
00:15:24.357So when we get that kind of feedback, it helps re-energize.
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00:15:27.174Speaking of re-energizing.
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00:15:30.163Yes, yeah, we're in a new year.
00:15:30.163 -->
00:15:33.552Like what are we?
00:15:33.552 -->
00:15:35.466What are we thinking about this year?
00:15:35.466 -->
00:15:40.770Personal goals, professional goals, what are you?
00:15:40.770 -->
00:15:41.072What's?
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00:15:43.467What's on the docket for Naomi this year?
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00:15:49.183Well, so I wanted to raise something with you guys, so over the holidays.
00:15:49.424 -->
00:15:50.828Yeah, I feel like we're in trouble.
00:15:50.828 -->
00:16:00.035No not only am I using my, am I using my mom voice, my stern voice can of worms I am a mom now, you know so yeah, that's right.
00:16:00.035 -->
00:16:04.286That's one of the big changes since we started, that's the biggest yeah that's a huge yeah.
00:16:05.168 -->
00:16:11.749I my husband and I we adopted our daughter, brought her back in may 2023, and that was experience.
00:16:11.749 -->
00:16:14.173I've now learned that I can just say no.
00:16:14.173 -->
00:16:16.544No is a complete sentence, just no.
00:16:16.544 -->
00:16:16.985Why?
00:16:16.985 -->
00:16:18.127Because I said so.
00:16:18.608 -->
00:16:58.735Anyways, over the holidays I had some friends visiting from LA and one of my girlfriends she works in admissions for a polytechnic university in Southern California and she was, you know, just talking about education and work and my job, marketing operations and whatnot, and she was saying that for the computer science department, they saw this year, compared to last year and all previous years, a double digit, almost 50%, decline in applications.
00:16:58.735 -->
00:17:04.317And they just thought, okay, like what is this, you know?
00:17:04.317 -->
00:17:12.181Like is it just us?
00:17:12.181 -->
00:17:12.602Yes, is this just us?
00:17:12.602 -->
00:17:13.002Or what's going on?
00:17:13.002 -->
00:17:21.469So they went and and I guess a lot of these schools are affiliated with one another so they went and, you know, talk to peers and colleagues at other schools and to see if it was just them and what was going on.
00:17:21.469 -->
00:17:22.873Was it an anomaly, something wrong?
00:17:22.873 -->
00:17:36.001And no, all of these other schools are seeing the same thing double digit, massive declines in applications for computer science, undergraduate or graduate or both undergrad.
00:17:36.001 -->
00:17:42.096And they did a little bit more digging, right, like what's going on.
00:17:42.096 -->
00:17:49.803So apparently this is all just like hearsay, right, but this is what they're, they're trying to figure this out because this is obviously concerning, right.
00:17:49.803 -->
00:18:08.489So apparently what's been happening is a lot of these students that are coming in, they're seeing the rise of AI and they think that there's no future in computer science because you can just type into an app and tell it to build you something, or basically they feel like AI is going to take computer science jobs.
00:18:08.489 -->
00:18:23.874So instead, what they're seeing because these students have to go somewhere, right what they're seeing is that there has been an increase in applications for engineering, and I asked my girlfriend actually this morning to and I'm just going to pull this up what is that split?
00:18:23.874 -->
00:18:41.743So there's been this is at her school only a 20% increase in applications for electrical engineering, a 10% increase in applications for mechanical engineering and a 15% increase in applications for electrical engineering, a 10% increase in applications for mechanical engineering and a 15% increase in applications for civil engineering, but a double digit, almost 50% decline in computer science.
00:18:41.743 -->
00:18:44.671And that's concerning to me, right.
00:18:44.691 -->
00:18:48.666So for myself, you know, my original declared major was computer science.
00:18:48.666 -->
00:19:03.882I switched about halfway through to communications and marketing, but the overlap between computer science and programmers and developers, I feel is very tangential, integrated into people who work in operations and I don't know.
00:19:03.882 -->
00:19:04.945That's kind of terrifying for me.
00:19:04.945 -->
00:19:05.808I don't know what you guys think.
00:19:05.808 -->
00:19:19.126Like I don't want an entire generation of you know unchecked AI happening right, like you know a lot of, a lot of a lot of folks that they've been talking to, or right like you know a lot of a lot of um, a lot of uh folks that they've been talking to, or potential, you know, applicants.
00:19:19.126 -->
00:19:25.673They're very interested in robotics, they're very interested in mechanical engineering, mechatronics, all of that.
00:19:25.673 -->
00:19:30.205You still need a computer science background to be able to power these.
00:19:30.205 -->
00:19:34.355I don't know what do you guys think curious so a lot of that.
00:19:34.375 -->
00:19:37.182So I don't remember if we've talked about this.
00:19:37.182 -->
00:19:40.020I can't remember if I've talked about it on the podcast either, but I'm.
00:19:40.020 -->
00:19:49.696So I graduated from an engineering school, uh, in a program called which the graduate degree would be operations research, which is sort of tied to industrial engineering.
00:19:49.696 -->
00:19:53.750So I'm now curious like what, what's the change in industrial engineering if that school has it?
00:19:53.750 -->
00:20:25.642But I can't talk about specifics, but in general I would say well, one of the things I know is happening I've heard this multiple places, not just with the, because I'm on the board now with that program and the engineering school that I graduate from, but there's there's a definite decline just overall in college like people going to college, in particular boys, men um, they're not going as as much.
00:20:25.642 -->
00:20:30.381So I think in general college campuses there's definitely more women, yeah, more women.
00:20:30.461 -->
00:20:32.364More women now in universities than men.
00:20:32.384 -->
00:20:37.913Yeah, and then there's in general.
00:20:37.913 -->
00:20:45.004It's been interesting to see some of the numbers, but it's a mixed bag.
00:20:45.004 -->
00:21:02.206When I've seen the engineering numbers in computer sciences and the engineering school where I went, where I went, one of the things they're seeing is there's been more of a rise in applicants and growth in undergraduate business programs that are somewhat affiliated with it too.
00:21:02.206 -->
00:21:16.009So you've got MIS, which would be more of a business school program as opposed to management science, which is the engineering equivalent, which is a little more heavy on programming things like that.
00:21:16.009 -->
00:21:39.028But I've been trying to pitch the idea that the degree program that I graduated from actually launched really well with operations and marketing operations in particular, because it's very much about optimization and analytics and process and all the things that we go through.
00:21:39.028 -->
00:21:42.807It's just I don't think people have thought about marketing as a place where that lands.
00:21:42.807 -->
00:21:47.369So I'm interested in that.
00:21:47.369 -->
00:21:48.866I'm surprised about that.
00:21:48.866 -->
00:21:53.588It's such a significant year-over-year change because I've seen it more as a trend.
00:21:54.241 -->
00:22:01.064I don't remember off the top of my head the numbers I've seen, if they translate to that same degree, but they're definitely.
00:22:01.064 -->
00:22:09.769They stand out and it really came out of part of it came out of the pandemic right and then I haven't seen impacts.
00:22:09.769 -->
00:22:16.614I haven't been hearing anybody talking about impacts from AI yet and the concerns that that's just going to take all the jobs.
00:22:17.278 -->
00:22:19.446Yeah, well, I think that that's why they were so concerned.
00:22:19.446 -->
00:22:21.225They're like Whoa, is it just like a glitch?
00:22:21.225 -->
00:22:43.086But then, once they started talking to other schools, they realized that they were seeing the same thing and that the the rumors that they have I don't think they have hard facts right now is that the students that are coming out of university, or, sorry, coming out of high school, are thinking that, you know, there will be no future in computer science.
00:22:43.086 -->
00:22:45.803That's what they're, that's what they're assuming right now.
00:22:46.045 -->
00:22:48.750So I don't know, fascinating.
00:22:48.931 -->
00:22:56.221Yeah, I was like, and it just evolved into this like conversation where like wow, and so I immediately thought of you guys.
00:22:56.221 -->
00:23:02.252I'm so like I'm curious what the two mics think yeah, I don't know.
00:23:02.333 -->
00:23:06.247I mean, I I wonder, I kind of wonder who you know.
00:23:06.247 -->
00:23:08.350To your comment, naomi, like who's gonna?
00:23:08.350 -->
00:23:11.663Who's gonna make sure this stuff's doing?
00:23:11.663 -->
00:23:13.027The right way.
00:23:13.027 -->
00:23:29.723It's like, it's like, it's kind of like you know, martech stacks without any marketing ops people like except for a little more scary right, exactly, oh god I don't know.
00:23:29.763 -->
00:23:35.268I feel like they're yeah it there seems like we're in for it.
00:23:35.307 -->
00:23:47.375If that trend continues, there's probably going to be you know that old, I graduated with a business degree and so I think of economics and unit economics and supply and demand curves all the time.
00:23:47.375 -->
00:23:55.386So not all the time, but that's where my head goes in this conversation the time, but that's where my head goes in this conversation.
00:23:55.386 -->
00:24:08.427And it seems like if that trend continues, there's going to be a supply and demand issue and all of a sudden, we're going to start seeing the uh, the computer science majors, uh, earning salaries that are probably two, two and a half x what they would normally have been.
00:24:08.427 -->
00:24:27.613If you know, because the supply will be low right, like there just won't be that many people and they're going to want to pay them top dollar to do that, and that'll be kind of like circa 2017, era of what developers were to startups in that ecosystem.
00:24:27.613 -->
00:24:30.932It was actually probably 2015, 2016.
00:24:30.932 -->
00:24:32.259I mean, that trend continued for a while.
00:24:32.259 -->
00:24:36.203Do you remember that people were getting paid crazy money when you?
00:24:36.223 -->
00:24:47.595were you were skipping school and going to a boot camp because you could go make 200k after the boot camp a year anyway.
00:24:48.176 -->
00:24:56.312Yeah, I mean I think it's interesting because there's these like meta trends that are happening in education and jobs.
00:24:56.312 -->
00:25:07.831I think part of the draw best I can tell part of the draw that is taking young men out of college or drawing them away from college.
00:25:07.831 -->
00:25:20.612There's way more facets to it than I think I'm going to say, way more facets to it than I think I'm going to say, but I think part of it is a view that college education is not worth what it costs.
00:25:21.240 -->
00:25:37.791Saddling yourself with debt is not, whereas if you go into, say, a trade, in particular, some trades that are, I wouldn't say, totally recession-proof, but they are much more stable over time.
00:25:37.791 -->
00:25:40.285Right the, the fluctuations are lower.
00:25:40.285 -->
00:25:52.701If you were, say, a plumber, right, um, and you can start making money right away, even if you're an apprentice, and then become your own, and then you can start a business like.
00:25:52.701 -->
00:25:56.846So I think there's there's this perception out there that there's that as well.
00:25:56.846 -->
00:26:02.251Now, yeah, it's not for everyone, but yeah.
00:26:02.653 -->
00:26:03.773So I don't, I don't know.
00:26:03.773 -->
00:26:05.195I mean I struggle with the.
00:26:05.195 -->
00:26:21.067I have no background or understanding of why, um, individuals that are males or deciding to, you know, forego the college experience or college education system or whatever.
00:26:21.067 -->
00:26:23.701But I mean that one makes sense to me to some degree.
00:26:23.701 -->
00:26:33.972Like I think colleges have been struggling for a really long time on the, the prices have been going up and the, the value to society.
00:26:33.972 -->
00:26:35.579I mean the, the value to society.
00:26:35.579 -->
00:26:38.649I mean like the baseline value to society isn't changing.
00:26:40.281 -->
00:26:48.700So like the unit economics of like what it costs to go get the same education that somebody got before isn't like, it's just, it's interesting, right.
00:26:48.700 -->
00:27:05.528Like we have to pay five X what what someone else did 10 years ago or more, and it's the same, the degrees, the same piece of paper, the information is largely the same, like not much has changed.
00:27:05.528 -->
00:27:18.355Yeah, you go to business marketing school and you learn about international marketing and yeah, they're going to tell you some stuff that changed because international law changed or whatever, but like the foundations of what you, what you learn anyway.
00:27:18.355 -->
00:27:26.803So I think I don't want to like prop up that college is a waste of money, because I no, I thoroughly enjoyed my college education.
00:27:27.204 -->
00:27:46.012Yeah, I think it was wonderful for my ability to get to where I am but no, I think there's like, I think, the value of it and I'm right in the middle of it, right with kids, in that age range but yeah, the value of it is beyond the education purely right or the financial part of it.
00:27:46.012 -->
00:27:51.245There's socialization, there's learning to be on your own, like all those kinds of things that are hard to quantify.
00:27:51.846 -->
00:27:53.389Depends on the degree too.
00:27:53.389 -->
00:27:55.493I mean, I hope my doctor went to university.
00:27:55.493 -->
00:28:00.509There's just some jobs that you yeah.
00:28:00.569 -->
00:28:03.506Right, yeah, right, there are certain things.
00:28:04.321 -->
00:28:06.168So, naomi, you brought this up.
00:28:06.168 -->
00:28:09.009I'm curious what was your reaction when you started hearing all this.
00:28:12.039 -->
00:28:25.729Honestly, I was fascinated, right, and I don't know how much of it is the difference between, like us schools and canadian schools, because obviously I'm coming from a canadian perspective and you know my, my husband.
00:28:25.729 -->
00:28:28.035He's a high school um teacher.
00:28:28.035 -->
00:28:36.759When he started his career he was hybrid math and technology and for the past past few years he's been purely tech.
00:28:36.759 -->
00:28:55.522He purely teaches computer science because there's been such a, the demand is so high, right, and so and this is kind of a bit counter to what she is saying because there's such a high demand for tech, granted, we are in Canada, this is is he teaches at an all-girls school.
00:28:55.522 -->
00:28:57.247So is there a difference there?
00:28:57.247 -->
00:28:59.591Um, I'm not really sure it's just it.
00:28:59.591 -->
00:29:07.785Would we just had that conversation, right, because it's not what he's seeing, um, and it was just interesting well, where are they going?
00:29:07.785 -->
00:29:08.747They're going to engineering.
00:29:08.807 -->
00:29:09.348Why is that?
00:29:09.348 -->
00:29:13.146Is it just because of where you are geographically located?
00:29:13.146 -->
00:29:13.729I don't't, there's.
00:29:13.729 -->
00:29:21.010There's so many things, right, and it's such a small sample size that it's, you know, difficult to extrapolate takeaways from that.
00:29:21.010 -->
00:29:25.427But I just thought that was just a very interesting thing, especially because it wasn't just their school.
00:29:25.427 -->
00:29:29.281They had seen it with, like other schools and other admission departments that they had talked to.
00:29:29.281 -->
00:29:31.147Is this part of a bigger trend?
00:29:31.147 -->
00:29:34.300I don't know Right, but talk to.
00:29:34.300 -->
00:29:34.623Is this part of?
00:29:34.643 -->
00:29:34.924a bigger trend.
00:29:34.924 -->
00:29:36.373I don't know right, but it just gets you thinking like what would happen.
00:29:36.373 -->
00:29:36.532No, I do.
00:29:36.532 -->
00:29:48.846I do think it's interesting if that is part of the mindset that they're hearing is that people are shying away from computer science because they believe that the ai is going to essentially replace that kind of job.
00:29:50.068 -->
00:30:19.732I'm with you, right, I I I'm not sure I want ai to kind of go off and truly run on its own without some sort of intervention but yeah, right, and I think why one of the things that I would share out into the ethos, into the world, into the void, is I'm pretty steadfast.
00:30:19.732 -->
00:30:34.687I mean, maybe I'll be proven wrong and then that's what happens, but I'm steadfast in this idea that marketing operations professionals aren't going to get replaced by AI like overnight by any stretch, and I don't think they're going to get replaced.
00:30:34.687 -->
00:30:56.420Replaced, frankly, I think you have to understand the art of the possible and then you got to use ai to extend your capabilities right and do stuff faster and better and, with you know, more accuracy or whatever, and I think that that should be true of of computer science degrees and and those that are looking to head into that field.
00:30:56.420 -->
00:31:10.149Like this is a way to if you understand the art of the possible and you know how these things can work, then you can get to your end destination more efficiently.
00:31:10.149 -->
00:31:12.433No, I think.
00:31:13.481 -->
00:31:15.490I think, one thing that I'd be interested.
00:31:15.490 -->
00:31:41.172So for our listeners out there, if you've got a point of view or experience right, I think there are becoming more and more tools out there that can enable not only marketing, ops professionals, but kind of everyone to eliminate some of the the things that you do that don't really require creative thinking as much.
00:31:41.172 -->
00:31:53.847Right, and you can, you can, you can expect, you know, make your, you know your capacity will increase right To be able to do those things, and I think there's, I think there's opportunities there, opportunities there, and I'm bullish about that.
00:31:53.847 -->
00:32:03.509I also think that there are going to be opportunities for AI to go beyond that and to start to enable us to.
00:32:03.509 -->
00:32:12.691Again, I can't keep going back the idea of getting better insights in our data, as messy as it is, especially in the B2B world.
00:32:12.691 -->
00:32:14.530I think there's stuff there.
00:32:14.530 -->
00:32:18.825So I I would love for us to get more discussion on that, should we?
00:32:18.924 -->
00:32:27.625yeah, but um did either of you to speaking of messy data and ai?
00:32:27.625 -->
00:32:35.780Did either of you happen to catch the like, the small little like back and forth that steven stouffer and I had on linkedin the other day.
00:32:36.281 -->
00:32:39.147It was like no, it was in public like or whatever comments.
00:32:40.529 -->
00:32:54.071Yeah, he, he posted about this idea that, like the, the idea of data quality and um being so necessary to leverage AI is like a farce.
00:32:54.071 -->
00:33:00.822I agree, and I was like see, I love this, I love that, I love that you agree.
00:33:01.584 -->
00:33:40.806And I was like, well, hang on a sec, cause he, like he gave his example right, like, oh, I've, I fed it all this information and it was able to more quickly, uh, help me, identify the duplicates, right, right, like, out of all these records that looked identical or very similar to each other, like which one was the right one to sort of like maintain, right, I was able to take all this information and it used some of the information like last contacted, create date, whatever some of this stuff when I was like, but you gave it good quality data for it to be able to make that decision.
00:33:42.509 -->
00:33:56.011And and my point was, if you didn't give it the create dates and those things and you just said which of these looks like the right thing, it doesn't have something to leverage.
00:33:56.011 -->
00:34:07.780You have to give it something that is good in order for it to have an opinion of how to give you the right output that yields the result that you would look for.
00:34:07.780 -->
00:34:22.001And the good in this case was I'm leveraging the recency and the to to help identify accuracy, and that's so, at the end of like the, the argument sort of like diluted down to what is the definition of quality and good.
00:34:23.385 -->
00:34:28.782It's really what it sort of felt that I was like at the end of the day, it's still good quality data, that you found it to make a decision.
00:34:28.782 -->
00:34:36.996I don't know, it felt like a bit of a Socratic argument, but anyway, you agree Michael.
00:34:37.781 -->
00:34:53.007I agree, I agree, like here's why I say I agree Right, I think there's a lot of people I have not, I have yet to find anybody who says my Salesforce data or my marketing data is pristine, right, right.
00:34:53.007 -->
00:35:04.206And I hear a lot of people talk about holding back on, like we can't do, we can't trust our data, we can't do reporting, and so you're going through a lot of this effort.
00:35:04.206 -->
00:35:11.607My view is, uh, it's never first off expecting it to be clean and perfect or whatever, whatever.
00:35:11.607 -->
00:35:13.631Whatever that means is a fallacy.
00:35:13.631 -->
00:35:14.393It's just not.
00:35:15.060 -->
00:35:24.023It's just not the outside of financial data, where there's lots of rules and regulations and controls in place, you know about what can happen.
00:35:24.023 -->
00:35:31.807Pretty much all the rest of the data is going to have anomalies and errors and problems and you just have to, like, assume that.
00:35:31.807 -->
00:35:44.327So that shouldn't stop you from doing reporting, because what I think is, if you start doing reporting, it's going to highlight where those errors are and if there are root causes for common things, you can go address those.
00:35:44.327 -->
00:35:55.692Over time it'll get quote better, but it will probably never ever be clean like financial data as an example.
00:35:57.036 -->
00:36:03.451Yeah, I agree, so I think that's why I was like well, ai, if AI can help accelerate that part of it, that improving it.
00:36:03.451 -->
00:36:18.613Now, the danger, what I see the mistake people make, though, is, instead of saying I'm going to start reporting, like we're going to build this great dashboard which is like the first way to like shoot yourself in the foot when you're trying to build this great dashboard, which is, like the like, the first way to like shoot yourself in the foot when you're trying to get insights.
00:36:18.633 -->
00:36:34.252I think it's a waste of time yeah, yeah, and I and, and I think to you know, and you know, I love, I love talking like steven, like loves pushing the boundaries on on all this capabilities and stuff.
00:36:34.252 -->
00:36:36.436I just the stuff he puts out is like awesome.
00:36:36.436 -->
00:36:38.400So if you don't follow steven, go follow him on.
00:36:38.400 -->
00:36:52.228Yeah then, but um, and I think I think the what is important about all this stuff is to say, and you know, if I was to rephrase, or you know, play back some of what you're saying michael's, like you know, don't, what is the?
00:36:52.228 -->
00:36:52.530There's a turn.
00:36:52.530 -->
00:36:55.302Michael's, like you know, don't let what is the there's a turn of phrase for it.
00:36:55.302 -->
00:36:59.043Like it's like don't let perfection impede your progress, kind of a thing.
00:36:59.043 -->
00:37:00.811Right, like you just don't.
00:37:00.811 -->
00:37:07.975You can start tinkering with these things and get a lot of value out of that without it being what you think is perfect right now.
00:37:07.975 -->
00:37:08.396Right.
00:37:37.105 -->
00:37:38.390What do you think, naomi, is data quality constantly just fighting?
00:37:38.390 -->
00:37:43.128Right, it's, it's you, you bring it, it comes in and it replicates across all your systems if you can't catch it properly, and it's in your backups and you know, it's just something that it's like.
00:37:43.128 -->
00:37:47.458Sometimes it feels honestly like one step forward, 10 steps back.
00:37:47.458 -->
00:38:01.235Right, yeah, like you've got a pretty good handle in it, and then, oh, we just went to a trade show and now there's like a massive data load or you know, it's just, it's just something that is just constant and I don't have.
00:38:01.235 -->
00:38:03.472I don't have an answer for what.
00:38:03.472 -->
00:38:17.667Like how does something you're right, michael, like nobody can say like, yeah, my data is pristine and perfect, right, it just right, it just doesn't.
00:38:17.667 -->
00:38:18.831No, I don't know any, but it doesn't exist.
00:38:18.851 -->
00:38:27.975No, yeah, um, it's just some, it's one of those things you just have to, you just have to deal with, yeah, and I and ai can definitely help you get there faster, right, like if you are looking at trying to solve data problems.
00:38:27.975 -->
00:38:35.507I think it's a great as long as you do it within the limitations and the boundaries of what is safe for your business.
00:38:36.389 -->
00:38:38.353Full disclaimer use ai safely.
00:38:38.353 -->
00:38:40.699But this goes back to why ai.
00:38:40.699 -->
00:38:58.332I don't think ai and I'm probably somewhat wrong in this will not replace people, and what they do is because I think we've all heard of examples of where AI spits out either nonsense or made-up stuff, right, think about ChatGPT in particular.
00:38:58.332 -->
00:39:20.285But I do think and I do strongly believe that you still need, especially on the data side, people who understand data where it comes from, how it works together, how people are interacting with it, to be able to go what you generated is nonsense or it's interesting but we can't really do anything with it, right?
00:39:20.285 -->
00:39:39.853Those kinds of things, I think, are still going to need people who understand that data, and it's part of why I keep harping on you know the few things I do right, understanding finance, understanding statistics, because I believe more and more like that's going to really make you stand out.
00:39:39.853 -->
00:39:46.074Even in a world where AI is doing some of the heavy lifting, people need to understand what the output means.
00:39:47.005 -->
00:39:47.586Yeah, I mean.
00:39:47.586 -->
00:39:54.531To me that just goes back to this idea of, like you know, quality can take on just like the word.
00:39:54.531 -->
00:39:57.577The damn word campaign can mean a million things to a million people.
00:39:57.577 -->
00:40:00.850I think this idea of data quality is the same.
00:40:00.850 -->
00:40:19.857The same in that you know you can feed a system a bunch of information, but what it might draw as a conclusion or as like an output is not relevant to the way that you think about your, your business and and you didn't.
00:40:19.857 -->
00:40:38.573If you aren't really like hyper specific about sort of like your aspiration for whatever, whatever it is that you're pursuing, right the answer to a question um, you, you should probably know your data pretty well, which means you have to feed it quality inputs to get a quality output right.
00:40:38.573 -->
00:40:40.446There's a but.
00:40:40.446 -->
00:40:47.641For those of you that don't follow Brinker, I suggest you do Scott Brinker.
00:40:47.740 -->
00:40:52.592Scott Brinker, Not Brinker International, which is a fine company but very different.
00:40:53.345 -->
00:40:54.115Yeah, follow Scott Brinker.
00:40:54.115 -->
00:40:54.423Some of his a fine company, but very different.
00:40:54.423 -->
00:40:54.629Yeah, follow Scott Brinker.
00:40:54.629 -->
00:40:56.696Some of his stuff is really, really interesting.
00:40:57.225 -->
00:41:17.173There's a really good thread, or a comment, that was added to one of his more recent posts on LinkedIn by Justin Norris, who shared this article that went really nerdy and really deep on this idea of AI and how you string together different um agents.
00:41:17.173 -->
00:41:20.113Uh, it was published by anthropic.
00:41:20.113 -->
00:41:26.615I can put it in the show notes for all of you, uh, but it is fundamentally what it gets down to.
00:41:26.615 -->
00:41:28.429Is is kind of what we're talking about here.
00:41:28.429 -->
00:41:30.916Is that like breaking down?
00:41:31.889 -->
00:41:49.978Um, when you think about an AI agent operating on your behalf, it ultimately comes down to like being able to like get it to do very specific things really really well, and in order to do that, you have to have like some pretty clear steps and like guidelines and you string together.
00:41:49.978 -->
00:42:01.032In some of these different models, they actually string together different parameters so that it can operate, uh, within those parameters independently, and then they bring them back together in an aggregator model.
00:42:01.032 -->
00:42:03.222That's just fascinating stuff, right.
00:42:03.222 -->
00:42:19.845Like you're basically like isolating these really specific outcomes and then bringing it all back together once each of them have completed their job uh, no, I the whole concept of agents and agents that follow you around like career coach or whatever, like the students, right that's.
00:42:20.266 -->
00:42:27.550I'm fascinated by that and how that might play out, because it's like it's hard for me to even wrap my head around with that.
00:42:27.550 -->
00:42:31.086From a practical standpoint, what does that look like in my, in, in our lives?
00:42:31.086 -->
00:42:31.127I?
00:42:31.749 -->
00:42:38.936don't even know what to expect from all this stuff 2025, this is going to be our whole world, I mean if it could help everyone get outside and move more.
00:42:39.085 -->
00:42:40.048I think that would be a good thing.
00:42:40.769 -->
00:42:41.352That would be great.
00:42:41.352 -->
00:42:42.856That would be great.
00:42:43.186 -->
00:42:43.527I've been on a.
00:42:43.548 -->
00:42:44.331LinkedIn kick.
00:42:44.331 -->
00:42:46.885Lately there was somebody that I have no idea who it was.
00:42:46.885 -->
00:42:51.877Somebody posted that their goal was to spend a thousand hours outside with their family.
00:42:55.405 -->
00:42:58.836Oh, spend a thousand hours outside with their family oh, I thought it was um oh gosh what was her name?
00:42:58.836 -->
00:42:58.877I?
00:42:59.118 -->
00:43:00.121know, I know exactly you're talking about.
00:43:00.121 -->
00:43:00.984Yeah, I was like good on you.
00:43:01.004 -->
00:43:08.988That is amazing she hit her goal this year with her and, of course, ops person tracking it, so yeah, well, that was I was where my head went.
00:43:09.390 -->
00:43:11.536Immediately it was like but how did you track that?
00:43:11.536 -->
00:43:14.859Like, what tool did you use?
00:43:14.859 -->
00:43:18.334Yeah, did everybody just go log in that they played for an hour outside?
00:43:18.334 -->
00:43:21.946I don't know was it an aggregate, or was it individual?
00:43:21.946 -->
00:43:28.376Yes sorry, yes the answer is yes, um, all right.
00:43:28.396 -->
00:43:31.747so where where do we see all this going?
00:43:31.747 -->
00:43:34.915Yeah, four years into it, what's what's next?
00:43:34.915 -->
00:43:35.317What do y'all?
00:43:35.317 -->
00:43:37.288Where would you like to see us going with this?
00:43:39.733 -->
00:43:40.153The show.
00:43:40.894 -->
00:43:41.196Yeah.
00:43:41.937 -->
00:43:42.158Does the?
00:43:42.198 -->
00:43:42.819show continue.
00:43:42.819 -->
00:43:45.468Does it morph into something else?
00:43:45.468 -->
00:43:48.612I don't know, I don't know.
00:43:49.353 -->
00:43:49.854I don't know.
00:43:50.775 -->
00:43:54.961I feel like I mean it's organic you know, yeah, I love, I love our show.
00:43:55.365 -->
00:44:13.531I, I I certainly I don't know if it's reached its shelf life and it needs to be sunset just yet, but I think, uh, you know, as long as people are interested in sharing their career paths and their learnings, we want to share their stories.
00:44:13.531 -->
00:44:23.907I love that idea, but I do see opportunity for us to potentially string together other show ideas.
00:44:23.907 -->
00:44:29.173I mean we have so many show ideas you do, I mean I do.
00:44:29.405 -->
00:44:30.649You're an idea generator, mike.
00:44:30.649 -->
00:44:32.335We know this, I know.
00:44:33.006 -->
00:44:35.876It's a problem, I have, it's a gift.
00:44:35.876 -->
00:44:38.043This, I know it's a problem, I have, it's a gift.
00:44:38.043 -->
00:44:40.512It's the glass half full version.
00:44:40.512 -->
00:44:45.256People on my team are like stop, stop.
00:44:45.256 -->
00:44:48.406Yeah, I don't know.
00:44:48.406 -->
00:44:59.341I would like to see even more people come on and share.
00:44:59.341 -->
00:45:06.976I'd like to see more of the B2C side come in and share a lot of their challenges.
00:45:06.976 -->
00:45:18.719They're different, they're the same and they're different they're the same and they're different, but they've been doing marketing technology and automation stuff operations for longer.
00:45:19.545 -->
00:45:26.097I mean, my first move into marketing was to build a 50 million household database for a company.
00:45:27.239 -->
00:45:30.310Yeah, it's been around for longer.
00:45:30.310 -->
00:45:32.747It's been bigger challenges, so I'd like to see more of that.
00:45:32.747 -->
00:45:39.077I'd like to see a continued push for the advancement of, like what does it mean to be certified?
00:45:39.077 -->
00:45:52.602That's obviously on my agenda, so I want to have more conversations around that for our audience, you'll see more of it from us, but yeah.
00:45:57.545 -->
00:46:00.329But you know, I mean I, yeah, I mean, mean I agree with everything you guys are saying.
00:46:00.329 -->
00:46:00.990I think I would love to.
00:46:00.990 -->
00:46:05.197The b2c part is interesting for me specifically.
00:46:05.197 -->
00:46:21.992Um, most of the people that I know in real life, locally, they are in the b2c space direct-to-consumer goods and I know never to call them or text them during Black Friday or Boxing Day sales or anything like that, and that's just a completely foreign world to me.
00:46:21.992 -->
00:46:26.857But they use a lot of the technology in a very similar way, just on a different scale.
00:46:26.857 -->
00:46:30.293So I think that that's really interesting.
00:46:32.807 -->
00:46:45.450I definitely think it would be interesting to have more discussions around some of the topics that we had covered during the Women's Breakfast, during WAPSA certification as well.
00:46:45.450 -->
00:46:49.819I often get questions on LinkedIn about how did I get into this role?
00:46:49.819 -->
00:46:54.053What are some suggestions or tips that I can give to people who are looking to get into this role?
00:46:54.053 -->
00:46:56.439What are some suggestions or tips that I can give to people who are looking to get into this role?
00:46:56.439 -->
00:47:02.113Because, unlike a lot of other career paths, there isn't a okay, I'm going to study this and then I'll get a job in marketing ops.
00:47:02.113 -->
00:47:07.207Right, it's not always so clear cut or so defined.
00:47:08.588 -->
00:47:17.181So I think topics that kind of lean towards those areas are things that I would definitely be interested in.
00:47:17.181 -->
00:47:21.545Also, I just love origin stories, right.
00:47:21.545 -->
00:47:46.634So guests that we had had, you know, for example, johnny from Slack and Vivian who had started Slack Sleep, now known as Will it, you know, like it's just conversations like that around their entrepreneurial spirit, I think is always going to be interesting and to hear how business, to hear how they started their businesses, the challenges that they have as small business owners.
00:47:46.634 -->
00:47:55.766I think there can be a lot of takeaways and parallels, right, when it comes to marketing, ops, people and how we digest information and I don't know.
00:47:55.786 -->
00:48:12.528Just lots of topics that I think that we haven't covered, that I think we can cover too yeah, two, two additional thoughts, or maybe it's a little slight difference to what you just talked about, naomi, but one that just occurred to me through our conversation.
00:48:12.528 -->
00:48:28.062I wonder if it would be useful to get some people from colleges and universities to talk about what they're seeing in terms of trends and how that could tie into it and maybe even help elevate the profession within the universities as a viable career path.
00:48:28.826 -->
00:48:29.930Oh, that would be killer.
00:48:29.930 -->
00:48:30.572That's a great.
00:48:30.612 -->
00:48:40.251Yeah, that would be great and I think through our connections, it sounds like we all three have some connections to university folks, so I think that would be an interesting one.
00:48:40.251 -->
00:48:52.061The other one, and this is one that so one of our past guests, kyle Lacey, who I'm a big fan of, he for a while had a podcast that he did.
00:48:52.061 -->
00:49:07.038It was I don't know, each episode was maybe 15 minutes and what was really fascinating was he was talking to revenue leaders and he would get really deep into kind of personal stories and not about work stuff.
00:49:07.038 -->
00:49:11.977But, like you know, a guy was a recovering alcoholic and they talked about that.
00:49:12.326 -->
00:49:28.859I mean, I think these deeper things I'm not sure if it's this may be one where it makes more sense, like, if we want to get into stuff like that about people's stories from that standpoint, right, the personal side of what it's like to be a professional and dealing with things might be an interesting one.
00:49:28.859 -->
00:49:48.461And we've had a few people who have opened up about challenges that they've faced, whether it was losing loved ones or going through, you know, stress-induced kinds of things or whatever.
00:49:48.461 -->
00:49:49.785But I think that might be kind of an interesting one.
00:49:49.785 -->
00:49:56.917And my guess is, naomi, you probably heard stuff like that in the intake forms you talked about for the women's.
00:49:56.917 -->
00:49:57.839What did you call it?
00:49:57.839 -->
00:50:00.370Mops, and mimosas.
00:50:00.685 -->
00:50:02.251Yeah, I think it was called mops and mimosas.
00:50:02.251 -->
00:50:04.351That was Audrey's.
00:50:04.926 -->
00:50:05.951I hadn't heard that yet.
00:50:05.951 -->
00:50:07.391I just heard the women's breakfast.
00:50:08.706 -->
00:50:12.074We deliberated on what that name was going to be and she landed on mops and mimosas.
00:50:12.074 -->
00:50:12.575I loved it.
00:50:12.575 -->
00:50:13.197I was like that was great.
00:50:15.088 -->
00:50:15.630Yeah so.
00:50:15.990 -->
00:50:16.874I think it'd be interesting to hear.
00:50:29.545 -->
00:50:34.465So I guess maybe we end here with a shameless request to our listeners, for again, we always love getting the honest feedback.
00:50:34.465 -->
00:50:41.155It's always good to know that we're connecting with you one way or another for not helping us get that, but we love your ideas too.
00:50:41.155 -->
00:50:45.952If you want to see us go deeper into certain of these subjects or other ones that we didn't talk about, let us know.
00:50:45.952 -->
00:50:46.834Reach out to us.
00:50:46.834 -->
00:50:54.637I think we're all nodding our heads here Like we are very open to input and ideas, in fact.
00:50:54.897 -->
00:50:59.782In fact I um, I was interacting with someone who wanted to be a guest just today, who brought up something.
00:50:59.782 -->
00:51:06.968I was like, oh, actually we've never talked about that and I get it would be an interesting one for our audience and it could be.
00:51:06.968 -->
00:51:16.972It wouldn't happen to be, I think, where it could go into a practical like this is how I can use something today or tomorrow, so I learned could go into a practical like this is how I can use something today or tomorrow, so I learned.
00:51:16.972 -->
00:51:23.472And other ones are big picture things, you know more esoteric, and I think we're open to all those yeah, yeah, I totally agree.
00:51:24.253 -->
00:51:30.831If you've got a idea or you feel like you want to share your story, we would love, love for you to come on and do that.
00:51:30.831 -->
00:51:35.820I I personally I was just thinking about it this morning again.
00:51:35.820 -->
00:51:46.275I was like maybe I'll spin up a channel for those that are like I know it's a new year so everybody does the like I'm going to get fit or I'm going to do this or whatever.
00:51:46.275 -->
00:52:11.847I really am on a totally different journey of my health right now and I was like maybe I like that part of like we're already in a community full of people with like similar interests in the, in the category of martech, but I like getting one layer down to like, yeah, let's all support each other for the, for the other thing right like you're a marathon runner, maybe you're a crossfit enthusiast or a mountain biker.
00:52:11.867 -->
00:52:16.509I was like, maybe I'll spin up a channel for so anyway, I it all.
00:52:16.509 -->
00:52:23.512That is to say, if you've got other interests and you are game to share them or you want to share your background story.
00:52:23.512 -->
00:52:27.947I think that's what makes it possible to relate to each other in this field.
00:52:27.947 -->
00:52:29.309Yeah, because we all got here somehow.
00:52:29.309 -->
00:52:31.812So, yep, yeah, anyway, well, four, Somehow so.
00:52:31.812 -->
00:52:32.353Yep.
00:52:34.155 -->
00:52:35.157Yeah, anyway, four years.
00:52:35.157 -->
00:52:37.600I appreciate the two of you in this.
00:52:37.600 -->
00:52:42.771We appreciate you together.
00:52:42.771 -->
00:52:43.052It's crazy.
00:52:43.052 -->
00:52:46.878It's like when I realized it was four years, I was like four years, is that right?
00:52:46.938 -->
00:52:48.100Yes, blowing my mind too.
00:52:48.100 -->
00:52:55.865Yeah, I looked like a very different human being four years ago, I don't know, constantly exhausted.
00:52:59.611 -->
00:53:09.469That's mostly because I had a newborn, but you know that's okay, and I'm on the other end where I've now got ones that are in college or about to head off to college.
00:53:10.269 -->
00:53:12.512Yeah, we're running the gamut.
00:53:13.293 -->
00:53:18.958So Naomi's got a new name as a new parent New-ish.
00:53:19.478 -->
00:53:19.919New-ish.
00:53:20.798 -->
00:53:21.000Yeah.
00:53:21.600 -->
00:53:22.040That's good.
00:53:23.642 -->
00:53:25.771Well, good, well, this is fun.
00:53:25.771 -->
00:53:32.352Hopefully our audience appreciates this sort of open book view, like of where we think things are.
00:53:32.352 -->
00:53:42.835So anything else before we wrap it up no, no, no no see y'all.
00:53:42.955 -->
00:53:44.297Let's bring fling in may.
00:53:44.297 -->
00:53:45.700Let's go spring thing.
00:53:47.746 -->
00:53:50.488all right, well, that sounds great.
00:53:50.488 -->
00:53:55.271Well again, always, always fun talking to you too and to all of our listeners.
00:53:55.271 -->
00:53:56.952Thank you again for your support.
00:53:56.952 -->
00:54:08.200As we said, we're always open to ideas and feedback and suggestions, and if you have an idea or want to be a guest, talk about something, we're all ears.
00:54:08.200 -->
00:54:13.883So bring them on to any of us and we be glad to talk to you about it some more.
00:54:13.883 -->
00:54:17.266So until next time, bye everyone, bye everybody.
00:54:18.628 -->
00:54:19.318Bye everyone.
