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Hey crafters. Just a reminder, this podcast is for informational entertainment purposes only and should not be considered advice.

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The views and opinions expressed own and do not represent those any or we currently with are associated with, or have worked with in the past.

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Thanks for tuning the FutureCraft podcast.

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Let's get it started. Hey there.

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Welcome to the Futurecraft Marketing Podcast, where we're exploring how AI is changing all things from brand to demand.

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I'm Ken Roden, one of your guides on this exciting new journey.

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And I'm Erin Mills, your other co host, and together, we're here to unpack the future of AI and marketing.

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We're going to share some insights, test the latest technology, interview industry pioneers, and talk to folks doing really cool things.

0:57

Ken, what really cool thing have you done in AI recently? So this is a real scenario that just happened about, I don't know, 45 minutes ago.

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I used ChatGPT to help me Problem solve a tech issue.

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I was having with one of the applications we use to actually make this podcast.

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And I was trying to go through the support hub or talk to one of their digital assistants and it just wasn't working.

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So I was like, whatever, let me try chat to BT and explain the problem.

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And it said, Oh, it may be one of these three things.

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And then gave me step by step what I could do to solve each of them.

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And the second one worked it saved me so much time and so much frustration.

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So do you think that, you would use that instead of going to the support center for other technology is like your starting point or what do you think? I have to laugh because the big joke about millennials is that we don't like talking to people.

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And in this example, it was totally true.

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I wanted the answer now and the support team wasn't able to get back to me fast enough.

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But this was actually something where I could get the answer I needed.

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if you start thinking about voice overlay onto these things, I can have a conversation with it.

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And actually have it walk me through what I needed to get done or explain what's not working.

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I'm actually curious to see how customer support's going to change due to chat GPT.

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Totally. What about you? I took your advice from the last episode.

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last time you were talking about how you had uploaded your persona of a stakeholder, an internal stakeholder.

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I had a board meeting. So in prepping my slides, I actually wanted to.

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Get a sense of what would the board, really dig into based on what I was presenting.

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So uploaded the slides and asked a bunch of questions about, what would they care about and what would they dive into? That's really interesting because, especially on a board, it's multiple perspectives, right? how did you think about personalizing it, but also keeping it kind of broad for a board? Yeah, I did a couple of different variations.

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I first said a broader scope of a board and the types of folks that are on it.

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And then went in and really crafted it to much more about Each person and what sort of I know about those folks that are on the board.

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Which really helped to mitigate some of the questions that were coming out know if I have an answer or something that you know Maybe I wouldn't have dug into on the slide It gave me just another data point to bring up during my talk track I really like that.

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It's just going onto this ongoing thread that I'm experiencing in kind of my AI journey right now, where I'm not using AI just for content creation.

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it's actually helping me prepare for some human interactions.

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And, you know, it's not perfect, but it's giving me an idea of what direction to go into, and I feel a little more confident going into some of these conversations.

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And also, think of things that maybe you wouldn't have thought of when you're going into those conversations, but now you can just a little bit more prepared.

3:50

there's just so many directions that this AI world is taking us.

3:55

And I think one of the ones that I'm mostly curious about is how are things like operations and analytics and marketing going to be handled? one of the things that I find really.

4:05

Fun and exhilarating about this AI journey we're on is it's demystifying a lot of areas that.

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before, like I just couldn't find the answers to, or it was really hard for me to get the answers to.

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And one of them is marketing ops and analytics.

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I think that generative AI gives us a chance to create data literacy across our teams.

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There are a lot of folks that struggle with Analytics or what should they be looking at? How should they be interpreting things? And today we have a really special guest, Grant Gregorian, who I've known for many years He is a mops genius.

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And has helped me to learn marketing operations and get excited about data.

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I think the conversation today is going to help demystify some of the marketing operations and analytics, around what's next.

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And I think that's one thing we're all trying to uncover and really understanding where can we get better insights and how do we interpret them? It's one thing to have all the data, which, we have so many data sources now and so much data, but really, what do you take from that data to action it? I'm particularly interested to talk to him because as you mentioned MOPS is not my area of expertise, but you Engagio and helped build some of their key functionality.

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And for me, that was one of the first times that I actually could get into reporting because it was so easy to view an account from a full perspective and understand how we were able to engage and warm up that account.

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So I'm super curious and excited to see what he's got to say about how AI is going to help us be better marketers and we can dive into that right after this break.

5:43

Hey, Grant welcome to the FutureCraft marketing podcast.

5:47

We're so excited to have you here. we're back with FutureCraft Marketing Podcast.

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Many of you in the mops world are very familiar with our next guest, Grant Gregorian.

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Grant is the epitome of a startup enthusiast and a mops wizard.

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He's currently the co founder and CEO of Moji Technologies.

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a tool that's simplifying marketing data analysis that automatically delivers insights and recommendations, making complex data accessible and actionable for marketing teams.

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Prior to Moji, Grant had really impactful tenures at Engagio, where he was the director of product management and path to scale for many of you early days of attribution, a company that he co founded and later saw acquired by Engagio, where he developed tools to help marketers measure the ROI of their campaigns.

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Through multi touch attribution modeling. Grant, it is so great to see you.

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Thanks for coming on the FutureCraft marketing podcast.

6:45

We're happy to have you. I'm excited. All right.

6:47

Let's get into it. Can you give us an overview of how generative AI is currently being used in marketing operations and what are the primary functions that serve? Yes.

6:58

Awesome. I would say we just can't stop talking about it.

7:01

Every conference that you go to that has to do with mops.

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It's AI. And when we meet each other in the hallway, or when we Slack with each other online, it's pretty much all AI.

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And it's because I think we're both terrified and excited about the prospect of what's to come.

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There's just so many applications.

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It's a mind boggling in marketing operations specifically.

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And so as. Stewards of marketing capabilities and organizations.

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We are very much attuned to what, what should we doing today to enable our teams to use this incredible technology and not fall behind.

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And also not to become obsolete and also to power up our own careers along the way.

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And so everyone's paying attention. I don't think it's overhyped.

7:47

Personally don't think it is. it is really impressive for anyone who's, talk to these chatbots and the pace at which they're getting better is also incredible.

7:56

it's a scramble, first of all, there's a vendor arms race.

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and then we're all paying attention to what are the vendors doing.

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And then internally in our own organizations, we're thinking about how do we harness this? How do we enable it? How do we make it safe? How do we not expose personalized data through some LLM system that, God knows what will happen to it.

8:18

So it's all top of mind and we're all discussing it.

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I understand that feeling of being very excited about it, but also a little scared.

8:27

I think we're all in that same space. What role do you see generative AI specifically? Playing in enhancing reporting or decision making and marketing operations.

8:37

And how can marketers leverage AI better to get those insights? what we're working on at Moji is on data analysis side, The ability for generative AI to explain and verbalize data.

8:53

I'm going to go on a quick rant.

8:55

first of all, I want to distinguish and I'm glad that you're using the phrase generative AI and not just AI because sometimes we get tripped up because as soon as you come to my house, which is Statistics and data there's more than one AI here and it's been around for a while.

9:10

And so when I say AI, I don't necessarily mean generative AI, which is a more recent phenomenon with a breakthrough with open AI and all of those incredible models, I think basically anytime we do any math, that's more than division, we get to call it AI.

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Okay. So any statistical analysis, progression, causal analysis, any modeling that you used to do in statistics class, wow, you're an AI expert now, right? Because that's what we, that's the label these days.

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And one of the challenges that we've always had in marketing analytics, and I've been doing marketing analytics for over a decade, is this last mile problem, which is after we deploy the dashboard, we, imagine deploying the dashboard is like a big, Party All the planets have to align.

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The data has to be cleaned up and vetted.

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All the systems are hooked up. The users the marketers are interviewed for requirements and what do they want to see? What kind of charts and how do they want to make decisions? You do all that work.

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Finally, there is this dashboard and you're like, look, here's this pie chart, and then guess what happens? I would say six out of 10 times, guess what happens? They say, thank you so much, This is an incredible pie chart.

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I can see that you've done a lot of work here.

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This is just what we requested. What do you think is the next step? What should we do? And I'm like, do your job.

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I thought you were a grownup. I thought you were here for work, just do the thing.

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And it's not that clear. It's not that simple.

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If whenever I've tried to put myself in their shoes and say does this really tell me what to do? It's not that easy.

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Like you have to drill in, you have to think about the areas, business decisions that are floating around.

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And how does this actually dear me for one decision to another? It's not simple.

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And everybody is at a different kind of data literacy curve.

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And so what I was thinking about is how can we bridge that gap? And especially regenerative AI.

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There's this ability to verbalize and talk about the data that the computer becomes really good at, and it can come down to your level or whatever the level you need to be at in order to articulate the point that you're trying to make with the data set.

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And it's really good at that. And so that's what we're trying to do in terms of reporting and analytics.

11:25

So we're really using the generative AI portion of it.

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And less on the deep kind of causal analysis and the modeling and the predictive analytics part of it, which is also valid, but still needs even more explanation.

11:37

And so it's this explanation power that we're hoping to harness and really democratize data as a result.

11:44

I love the idea of democratizing data. It was really good, that we're talking about generative AI versus kind of other investments in AI or innovation, just generally speaking, are there recent innovations in AI that you've seen generally not specifically gen AI that you think are particularly interesting for people who are in mops or care about, Marketing operations and being more efficient so that's the thing that's been disorienting over the last few years is just a chain, the pace of change.

12:14

and also just as you plot the changes that have already been made into the future, I just, I'm having a really tough time.

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Like I used to be able to squint and imagine what the future will be like.

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And I felt I have a handle on this, and I can develop products and I can imagine future products that will help marketers and I'm having a tougher time doing it because of how Weird the world is if you start to think about the capabilities that are possible.

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So let me give you an example. We want to make data more accessible.

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first thing that we did is we started going to the data sources, using API, collecting the data, doing some analysis and then sending the results to users.

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a lot of the customer feedback was we already have a bunch of dashboards.

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We already built all of the capabilities.

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I don't want you to recreate it. Can you use this instead? okay, I'll just go to your dashboard instead.

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I'll try to articulate what it all means and how to interpret it and what to do about it.

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one of the capabilities that I stumbled upon is you could literally take a screenshot of the dashboard and send it to one of these AI systems.

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And that, you can do a little bit more work than that. You can take each component and separate it out, send it to these new systems and they do a tremendous amount of job at summarizing it, finding highlights things to pay attention to and things that I would have done as a human being, but they do it so much better and consistently.

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And it's just taking a picture of it. It did, it's not even, doing anything fancy.

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And so this ability to just replicate what we do in a whole new way is mind boggling.

13:53

I don't want to look at dashboards anymore. You look at the dashboard, tell me the highlights and then tell them, and I'll dive in and figure out why something's not happening.

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And I'll be tier two analyst. You take care of tier one problems and I'll jump in only when I need to.

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Let's make that. And that's how approached it is with every new capability.

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I think about what does this unlock for us? How can I help, more teams leverage this within, within the mission statement that we have, Enable marketers to better understand what's happening.

14:24

I haven't tried that yet with the dashboard.

14:26

So I'm definitely taking that away. one of the things I think that's interesting that you pointed out is this level one, analysis and created a bit more sophistication, I think, with marketers, in terms of data management, we get these beautiful dashboards, we maybe have some insights that we pull out.

14:42

But junk data in, it's not really going to matter.

14:46

Do you see a world where, there's generative AI supporting, integrating, different data sources and cleaning data and just getting better results overall? Or what's your, what are your thoughts on that? I haven't seen that in real life yet.

15:01

Partially because we haven't come to a consensus as a society yet as where exactly these generative AI.

15:08

Systems are going to live and it probably will vary from organization to organization, but we're very, I think, correctly guarded about our corporate data sets.

15:17

And we are not, going to let, Alexa and Siri come in and just do whatever they want with our data.

15:24

so the plumbing of the data sets, the integrating, the working of the data is very much still the work of data engineering teams and, the vendors That host our data.

15:37

And then it's we then selectively expose it to generative AI or explanation.

15:43

Like for example, recently have low, which is part of Salesforce.

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They came out with a feature and they've been.

15:49

Really in a forefront of using journey of AI and interpreting data as of course they would be of this notion of there's a dashboard, but there's this little sidebar and you can chat with your dashboard.

16:02

you can ask a question and it will tell you answers.

16:04

and it's at that level Especially with one of the areas that I've been thinking about is in marketing.

16:10

it's okay to be a little bit wrong. And so it's a very probabilistic kind of a science.

16:15

A lot of times you just want to paint a broad picture that's pointing in the right direction.

16:21

that invites a lot of what's called synthetic data.

16:24

You could pad the data the kind of polish the outliers and say, we only have a few signals.

16:32

Of real data, but it's probably like this in order to tell a story.

16:38

That's true. I'm okay with that. And I think we these generative AI systems actually really good at that and generating data that kind of looks like other data.

16:46

And if you think about. Companies that we work with, which is B2B companies, like when they have so many examples of successful opportunities, We just have a few a year that are big enough to pay for the whole thing.

16:58

And so in those situations I think it could be used to smooth out some of those curves to say, yep, this is what we want.

17:06

this is what it looks like in order to help it better understand, to make connections between the data.

17:11

It's the art and science, like being a little bit more integrated.

17:14

Yes, because if I can explain it and get the value in being able to, someone have that eureka moment or oh, I get it, and then have them.

17:22

Age, what they're doing as a result that, Increases the performance of some campaign that would be worthwhile.

17:28

100 percent and I think that's one of the bigger challenges because you do have so many varying levels of folks of, understanding data and what it means and what's the next step.

17:39

as you are working to simplify some of this. Marketing data analysis what are some of the strategies that folks have been using and where are you seeing that be really effective? Yes.

17:49

So that is an area where generative AI is I think going to have a big impact because the example I like to think of is a Khan Academy.

17:59

If you guys know Khan Academy, fantastic resource.

18:02

I use it with my kids all the time. But Khan Academy has this vision of a personalized tutor, a tutor that can, that knows where you are in any specific subject.

18:12

And if you think about, education, that's been the Holy grail of being able to have personalized educator who knows what you know, and has the context of all the other path conversations that it add with you and any gaps you may have in some subjects.

18:26

This is where I'm squinting. In the future, you don't all get the same dashboard.

18:30

The source of the data is the same, but you get what you get with what you want.

18:35

And so I think that the communication density changes depending on the role and the context.

18:42

So some people may want a 10 slides because they're going to go present to the board.

18:48

Another person just wants, you A quick email with bullet points.

18:51

Another person wants. Automatically generated podcast they can listen to on the way to work with the same content.

18:59

Why not? And so this malleability of the form factor and malleability of the content makes it perfect for personalizing this communication.

19:08

that means that we can track who's at what level of data literacy or data comfort and tailor the message accordingly, make it more verbose or less verbose.

19:19

Just get to the point. I know what 0. 2 coefficient means.

19:22

Just tell me what the number is. And other people would say, can you remind me It's 0.

19:25

2 good. Is it bad? What is it supposed to mean? And that's, and without judgment, because it's a robot, you can go deeper.

19:32

And I am excited about that. Okay, Grant, Erin and I are both huge Engagio stans.

19:39

Like we both have had a lot of success using it.

19:42

So I want to dive into some of your experience there. You worked on defining customer journeys and tracking account stages, right? How do you see AI enhancing that process of customer journey mapping and what benefits could it bring or insights could it bring around customer behavior? Yes.

19:58

Thank you. And you know what I miss about Engage because it was sold in Incorporated is the whale.

20:03

love the way. I think his name was Geo and it was one of my favorite parts of Engagio.

20:07

Yeah. So here, I think this is gonna be a combination of the.

20:11

The generative AI and non generative AI and the non generative AI parts are going to play a deeper role here.

20:22

And they already do both, demand based and Sixth Sense and companies like that.

20:26

They've been around for years and for years had these predictive models that try to take different factors of success for a customer journey and weight them correctly.

20:37

And try to estimate what it all means. And therefore what a prospective best case customer looks like.

20:43

Those are models that are. We can call them AI, that's AI.

20:47

It's not generative AI. But we use that today.

20:50

Those vendors are actively using AI and we are actively as customers using AI to tell those stories.

20:58

Accounts go up and down and sometimes our customers, sometimes they're not, sometimes they're in pipeline, sometimes they're not.

21:03

And it's a, knowing that on a dashboard is impossible.

21:07

And so I am looking forward to being able to automatically, it's show me a movie of how my pipeline has been changing.

21:15

Okay. So It's something that happens over time.

21:18

So there should be like a little movie. Why is it always a dashboard? And so those things will be possible and the ability to explain the data would be possible because that's the thing that's been so frustrating is that there is all this like modeling and all this data and we're just not comprehending it correctly.

21:37

How do you explain it? And then tell it to me across multiple channels.

21:41

Deals and then give me something that they have in common.

21:44

There's no way that you can do that easily.

21:48

we have the data for it. we almost lack the vocabulary to explain.

21:52

it's almost like there's an abyss between so much data, which I think is almost overwhelming how much access we have to data versus, years ago it was I have this lead and they filled out the form.

22:03

Great. Now, all the, research that folks are doing before they're even coming to you.

22:07

How did I digest that? I'm curious, once folks solved some of the data cleanliness problems and, have some of these tools in place.

22:15

What would you say are some KPIs that would be important to show, from a marketing operations perspective to the business? If we're talking about in terms of generative AI, then I would say To me, the metrics that are important to the two that come, that we've been thinking about at Moji too, is what is engagement? I would want my team to be engaged with the systems and to use them and to be clicking on stuff and conversating with them.

22:45

And so I would be thinking about that. Because if nobody's using it, it means something's not working.

22:50

They don't find it useful. And so we need to do some additional work to make it useful so that they get embedded in the day to day work, because we know that they have capabilities that will improve the team's efficiency, that all the things, right? So I want the team using it.

23:05

And I want metrics that show that, it's up and to the right in terms of usage.

23:11

The thing that it's been more elusive is is it any good? Is it like if it gives you insights or advice or tells you to change something, was that like demonstrably good for the business in terms of increasing performance in some way? That would be amazing if we can get there.

23:30

And that would be just KPI like anything else that we would track an ROI on investment on a system like this.

23:38

Does it bend the curve somehow and make better decisions for us? Or maybe because of that increased usage, we're just interacting with the data more and we're just faster to create things and iterate and so it, does it just grease the wheels of an existing team already? And so those are the things that I'm thinking about.

23:58

What advice would you give to CMOs or MOPS leaders that are looking to integrate, whether it's generative AI or AI, into their strategies? And are there any real skills or knowledge areas that they should focus on? Yes, I would say these days, the thing to do is to Establish a safe space where your employees to play with this stuff.

24:21

I would encourage CMOs and other Data leaders to create a place where you explicitly give permission for your employees to play with generative AI.

24:33

So it means they have some, maybe some internal data and the model in the same room where you can start to mesh them together, or at least a place where they can copy paste things from, they go to Salesforce.

24:46

And so that is very scary for many organizations because a, we're doing something that we don't know about.

24:53

We don't know exactly what the outcome will be or what the capabilities that it might unlock, and we're playing, we're exploring together.

24:59

And so the skill there is like creativity, experimentation, culture that I would encourage.

25:06

Having done that, I would check back in and say what does this unlock for us? What capabilities did you discover and try to then maybe find a more dedicated way to double down on that capability.

25:18

if the team comes back and says, Hey, I'm finding myself, pasting an email from this vendor and summarizing it into the slides.

25:25

Can we find a way to do that? I would leave it up to your team to experiment and come up with use cases on their own.

25:32

Yeah, I think that's really interesting for the reason that I think people are still nervous on where to get started.

25:38

If we could go a little bit deeper in that. Could you maybe give us like a.

25:42

Good, better, best of what mops should be thinking about right now, considering what's out there for AI, whether it's generative or another category.

25:53

Yeah. The worst is to just ignore it and hope that it goes away.

25:57

I don't think this one is going away. This one is everyone else is excited about it.

26:01

You're going to be forced to use it. Good as if you're doing it on your own at home and you're playing with it.

26:07

And you're like, Oh gosh, like this could be really powerful for me at work.

26:11

But you are yourself upscaling, paying attention and getting a sense of the capabilities of the models.

26:18

So I would say step one is get a sense of the capabilities of the models.

26:22

Play with them, talk to them about work, ask them questions that you know, the answers to.

26:27

That's always the best one, and see if they'll.

26:30

Surprised and delight you because they have surprised and delighted me a lot but also disappointed.

26:35

and level three is, can you actually use it at work? And do you have a safe space where it's being used at work? Where the lines start to get blurred and you get to really.

26:45

Experience the future in the context of all your coworkers and have discussions about it.

26:50

That's actually what I did in a previous role. I was leading a marketing function.

26:53

I was like, guys, just go find stuff and yes, don't use any proprietary information, but play with it.

26:59

What do you like? What works? What could fit? It's not going to be perfect.

27:03

What could we leverage? And how could it help us? And I just think that curiosity is really important right now.

27:09

And it is a little scary. how do you think generative AI.

27:13

Is going to change the MarTech landscape.

27:16

Where do you think it's going? Yeah, it's going to destroy it completely.

27:19

It's going to be so confusing. I have no idea.

27:22

Already had that monster ocean giant tech.

27:26

What is that called? The MarTech landscape.

27:28

Oh yeah. The thousands and thousands of vendors.

27:31

We're going to just explode that even further.

27:34

and so I, again, this goes back to this.

27:37

You're making me squint even harder by asking the futuristic question.

27:41

Try to play this game where I say, okay let's say that we have the generative AI.

27:47

It has improved to the point where we trust it with data analysis, but let's say that we've got GPT five or whatever.

27:55

And I do imagine these models getting better and better. And so it's able to do data analysis.

28:00

It's able to do basically what we do.

28:03

What's it like at work as a marketer, so what am I, okay.

28:07

So if I open my computer, what does it say? Is it like.

28:10

Hey marketer, here's all the stuff I've been doing while you've been sleeping.

28:14

Here's, I guess it will have to tell us how it's going at least here's the leads that came in that I responded to that is the lead also a computer that is inquiring, because I said, Hey, I'm buying the software, go get me bids and go evaluate technology, and so it's just so hard to imagine for me what it's like, because we've just got these robots running around.

28:36

And we're just hitting pause on Netflix, just in time to listen to what they're doing and then going back to watching, what am I doing exactly in this world? cause there'll be like I want to launch a campaign.

28:47

Okay. We'll and so you just give it thematic ideas and then it goes and finds both the customers that, prospects that it needs to contact.

28:55

We will send them an email, but those people don't want to read emails.

28:58

They'll just want a daily summary of all emails that came in.

29:01

You know what I mean? Read to them in a whispery voice on the end of the day, who knows? I have no idea, but they can do whatever they want with the content that's coming in.

29:11

what does it look like, whether it's the end of the year, or even like a couple of weeks from now or months from now.

29:16

we'll start to see it seep into data.

29:19

We're sure we'll see, all the vendors, Salesforce, Tableau, Looker, all the big vendors incorporating data summaries, data visualizations.

29:30

It's inevitable that robots will inspect, analyze, and summarize data for us.

29:36

It's just way too much of it.

29:38

And so they'll need a way to explain it to us.

29:40

So that's for sure coming and that means personalized communication through our marketing automation systems through our ads and then automated summaries of performance.

29:53

the thing that I'm looking forward to is the ability to really embed these systems into our data.

29:59

And in a deep way, not just in a copy paste kind of a model or even chat model, but where the model is sitting on top of a.

30:08

Multi relational database, and they can see, transactions over here, leads over here, interactions over here, and accounts over here and make sense of it.

30:16

That would be incredible. We don't have that yet.

30:19

And that's a near term possibility, I think.

30:23

And I'm looking forward to it. you mentioned Looker and you mentioned other technologies.

30:27

What are your thoughts on that? One or two considerations that marketing leaders or people in mops should consider when looking at integrating AI into their existing tech stack.

30:38

It's a good question. I would say these days, what's really good is meeting transcription.

30:45

That's fantastic. Like transcribing text.

30:47

I think that could unlock a lot for sales leadership and maybe that's more rev ops and not mops.

30:54

Those transcripts have so many insights and good information for marketing to use.

31:01

I think it's a underused area of those meeting transcriptions there.

31:06

I think they're currently being used to coach the sales rep or at best, do you at least keep track of all the conversations and where they are, but it could be such a treasure trove of common objections of tone of language and vocabulary words used by our customers for content creation for any marketing assets to resonate.

31:29

So the, I think some of the gold being mined today from data that was unavailable previously, isn't those all transcripts.

31:37

I would encourage folks to look into that and ask your sales labs, friend.

31:43

Where are those call transcripts? Can we get them? Can we take a look at them? Cause I think they might have some really interesting things for marketing team to explore and that's available today.

31:53

Those systems are already deployed and out and about.

31:56

being able to take that data driven approach of taking what customers are saying and incorporating it into, marketing.

32:03

what are some of the other things that you're thinking about that aren't, maybe top of mind for folks that, obviously the, there's the integration from our email systems and things of that, but I'd love to get your perspective of what are, what should we be thinking about? I can tell you what I'm thinking about.

32:16

So I've been thinking about on the data side of if you live in a world where analysis and insight is free and abundant all of a sudden, something that used to be so expensive can be generated in a moment's notice.

32:28

So what are we going to do? We have to think about who should get what, when, right? Which of our team members needs what information and what format when.

32:39

what is the cadence of it, do you want to receive, a little insight every day, or do you want to receive a big digest at the end of the week? So it's unlocked all these new questions.

32:48

And those are the questions that we're asking ourselves.

32:51

It's how do we enable this? And then how do we give the user the ability to tune it? It's how you said it to send it to me weekly, but actually want it every day.

33:01

And I want it in this format and I want it like this. And can you also give me this other thing? as a result of generative AI, some of the new questions that we've been thinking about recently.

33:11

it's really neat because it evens the playing field.

33:13

I think, some of us who are real data nerds and then folks that are maybe that's not their strength that if they do other things really well, it really helps Okay, Grant, this has been an awesome conversation.

33:23

I've learned a lot here at FutureCraft marketing.

33:26

We're all about giving our listeners kind of practical tricks and advice.

33:31

So I'm going to give you four questions and just give me your quick hits for our listeners.

33:35

First of all, what's your best quick AI tip? Yes.

33:39

I would say quick, best day to talk to it.

33:43

Try the talking capability on the open AI app.

33:47

It is so much better than Alexa and my kids use it.

33:51

It was asking me questions and I'm like, you know what it's really good at is just making stuff up.

33:55

It's a make belief machine, and it just like unlocked so much for her because she's also a make belief machine.

34:01

she was like, it, I ghost real.

34:04

And it gives a boring answers of no ghost, sir, not real.

34:07

Tell it to tell, create a ghost story with it.

34:10

Can you create a ghost story about this and it does.

34:13

And then it can. And then it's can you make it like this? And it just keeps on, and then she's just sitting there talking to it.

34:17

And I felt good about it. Cause it's not a screen time, but it's like a creative ideation.

34:23

And my, my quick tip is I talking to it too.

34:27

Now don't just chat with it. Yeah, that's great.

34:30

What's your best prompt or workflow that you recommend? Go long, that's a, you're tempted to just do short, like texting.

34:38

Hey, tell me this, tell me that.

34:40

We found that the best prompts are actually multi pages long.

34:44

These things can ingest many tokens.

34:47

And so what we do is we craft a long essay, essentially with many sections.

34:52

And then you just put the whole thing in.

34:55

It feels overwhelming, but it reads it right away and it starts giving you much better responses than if you were just constantly kind of short form texting with it.

35:05

What's your best tip for keeping up with all of these latest AI trends and marketing? Use it, man.

35:12

You got to get in there, get your hands dirty.

35:15

I'll tell you for me personally, it's been amazing.

35:18

I've always wanted to be a more technical person.

35:21

Like I took coding classes in college and I've always been very impatient with all the syntax.

35:28

And now it's been unlocked because I just tell it exactly what I want.

35:32

And I say, can you make a. Python script that does this to this table and takes this and, and it does, and I just paste it in and it works.

35:40

And I'm like, I'm a coder now, this is incredible.

35:43

And so I would encourage you to whatever your career goals are to try to Use it as a coach to coach you along to level up in that way.

35:52

Or if you want to be technical, it is incredible for programmers, for coders it truly transformed how I work from that point of view, because suddenly I'm coding APIs and I'm getting Data results back and I have headphones on and dark screen.

36:05

And I'm one of those people now, all of a sudden, instead of being just a business user.

36:10

Yeah. what technology should our listeners check out that they may not know about? So this goes back to the original question of you got to be curious and exploring.

36:18

There's so many coming out all the time. The ones that I've been playing with I mentioned earlier is the image recognition capabilities.

36:25

I would try that. I would try sending it things other than text to play with it because it's becoming surprisingly good at it and recognizing, recognizing pie charts and what they mean and what they say.

36:40

And lay with the imagery, with the sound.

36:42

Don't just limit yourself to text when it comes to the system.

36:46

I think that's an area of active research and the systems are getting better and better at it every week, it seems this has been awesome.

36:53

I have learned so much about the democratization of data and how AI can maybe help us get more clarity into what we're doing and I think our listeners have learned a lot as well.

37:02

So thank you so much for joining us and we'll be back I think it's really crazy how, even the experts are trying to squint to see what's next and have a hard time figuring that out beyond, six months or a year.

37:14

And I think that's what's cool about generative AI is it's, moving really fast and everyone's trying to figure it out.

37:20

Yeah, I agree with you. It really excited me to hear about some of Grant's views on how AI can help.

37:31

remove some of the barriers for people like me who aren't as comfortable with analytics.

37:36

you can get data sets packaged in a way or insights package in a way based off your level of expertise.

37:41

So if you're, you know Heavy data analyst with a lot of expertise in that area.

37:46

You can get an output that meets you where you are.

37:48

And if you're in the earlier stages, you can also get that.

37:52

And I think that's really going to help people be more comfortable.

37:55

Not only inquire about data, but also ask questions because if you can do it with a bot, you don't have to worry about feeling stupid or like you should know this already.

38:04

It removes all of those What about you, Erin? What was your big takeaway Yeah, what I found, really interesting, but also really empowering from what Grant had to say about the role AI is going to play specifically in analytics is the accessibility.

38:19

You know I'm comfortable with data, but if it's an area in reporting that I'm not familiar with, doesn't always come natural to me.

38:27

Right. And so him saying that the chat bot or AI could produce.

38:33

A report that was made for me at my level of understanding of that topic, where I could also ask questions and not feel judged really is empowering to make me feel like, okay, I can dive in at my level, but also someone who's maybe more advanced or maybe someone who's a little bit less experienced in that area could also dive in and get the information they need and are looking for without some of those Psychological barriers we put up around not feeling confident or not wanting to look stupid.

39:01

Yeah, I really think about it as being a leader.

39:03

And, when you're bringing new folks on or folks that are new to the industry or new to marketing and really being able to take a lot of the things that maybe come, second nature to those of us have been doing it like a hundred years.

39:17

And really be able to help translate what that data means to them and to provide a little bit more self service.

39:23

Cause I think it can be so overwhelming. a dice lot of times, especially as you're more junior in your career, or as you're trying to help people get a handle on what's the action they should take from it.

39:33

It's not always that intuitive. And so I feel like with generative AI being able to query what is You know, what's the next thing? Or what should I be thinking about? Or, what does this even mean to me? Can be really powerful to your point, not having to go to somebody and ask Sometimes people feel a little oh god, I should know this or There's something that maybe just should be a little bit more intuitive and it's just not necessarily So I think that's what excites me the most I think it's definitely worth checking out, and we can certainly talk about it on a later date.

40:04

But I do think there's a lot of tools out there on the analytics side.

40:08

And as generative AI is continuing to evolve in that direction.

40:12

In that realm, we can dive a little bit deeper, but I'm super excited to, really understand the future of data analytics and marketing.

40:20

And I think one of the other powerful things that Grant said, and one of my key takeaways is really about, it doesn't have to be perfect.

40:27

I feel like oftentimes we're trying to nail what is that one thing that, had a prospect turn into an opportunity? And I think it's really about analyzing across accounts and getting a better sense of directionally what's right.

40:42

Yeah, it was making me think of some previous roles that you and I had working together where we had some kind of flagship metrics that we lived and died by as a team.

40:54

And when we were onboarding new people, imagine having some sort of, chat bot that could give you the ability to say, here are dashboards, and now you can ask questions about why do we measure it that way, or what are some reasons that a customer might not move to the next stage that we want them to so that we don't actually have to be there to answer their questions that they can actually dive in more at their comfort level.

41:15

Even at our level. I think that the thing is, I'm still trying to learn and trying to understand what's important.

41:20

And I think what Gen AI does for us is it really also helps with the segmentation because not all accounts look the same as we know, AI's existed for a while now and certainly has helped us.

41:30

But the generative AI piece, just being able to like bounce ideas off of it or, tell me a little bit more about, this conversion rate compared to this getting those insights, I think will be super cool and really being able to then incorporate those into our broader programs is something I'm super excited for.

41:46

So more to come, certainly, but a huge thank you to Grant Gregorian.

41:51

If you guys have not interacted with Grant before he's just lovely.

41:54

And certainly check him out on LinkedIn, as well as Moji Technologies.

41:59

Didn't really suck. Yeah, it sucked pretty bad.

42:02

I think I need to angle my microphone down.

42:05

Because I'm like looking at how your sound looks, and it looks a lot louder.

42:09

I'm Naturally louder. Sorry, Jake.

42:12

right. So more to come on the analytics front, which I could not be more excited about, and I think it's going to be very cool to get better insights.

42:21

To really be able to incorporate into all of our marketing programs.

42:25

So a massive thank you to Grant and thanks to Grant over the years for educating me and others in the industry as well.

42:32

And thanks to everybody listening. Hopefully you took away some interesting takeaways on our marketing ops special here.

42:38

Yeah. Thank you to Grant Gregorian.

42:40

If you haven't checked him out, Check them out on LinkedIn, check out Moji Technologies and really, dive into the metrics.

42:47

I think that's the takeaway I have for today.

42:49

And thank you to everybody that's been listening.

42:52

let's keep crafting the future of marketing together.