Episode 78 - Kimberly Storin

Narrator: [00:00:00] Welcome to the Digital Velocity Podcast, a podcast covering the intersection between strategy, digital marketing, and emerging trends impacting each of us. In each episode, we interview industry veterans to dive into the best hard hitting analysis of industry news and critical topics facing brand executives.

Now, your host, Erik Martinez.

Erik Martinez: Hello and welcome to this edition of the Digital Velocity Podcast. I'm Erik Martinez, and today we have Kimberly Storin, the Chief Marketing and Communication Officer for Zayo Group to talk about how marketing teams can integrate AI into their business processes for better outcomes. Kim, welcome to the show.

Kimberly Storin: Thanks for having me, Erik.

Erik Martinez: So, I'm super excited about AI and everything AI. I probably don't dig into it as much as I really want to. But you seem to have an amazing background in marketing and communications and integrating [00:01:00] technology. Could you just take a brief moment and tell us a little bit about your journey ?

Kimberly Storin: Sure. So I started in marketing and communications back in the dot com boom or bust, depending on the day. As I saw the 25 year anniversary for that yesterday. So that kind of reminisced a little bit about those early two thousands. But I started in communications in the early two thousands and after quite a few years in client service, I decided to really focus and pick my major in B2B technology and marketing in particular. So I've been in marketing and B2B technology since 2010. Working at some pretty large technology brands like Dell, AMD, IBM and now Zayo.

Erik Martinez: That's quite the resume. Awesome. Well, I am excited to talk about this. You know, I think for the vast majority of people, AI is still very new. And I've talked to businesses every day that are adding AI tools to their tech stacks, and yet we're not seeing the [00:02:00] gains that one would expect from these tools. And I know it's early but, what do you think the core problem is and how do we go about fixing it?

Kimberly Storin: Yeah, so I think there's a couple of core problems. I always like to start out with the history lesson, like AI has been around since 1954, right? That's when we had the Dartmouth conference. That's when you saw Alan Newell and Marvin Minsky and all of them come together and really start to think about the power in terms of neural networks and machine learning, deep learning, et cetera.

So the technology has been around for a while and we've gone through some AI winters, we've gone through some AI excitement in the market. And it was kind of party tricks for a long time, right? You saw Watson win jeopardy back in the day. And then, we had the hype of Watson overall with IBM, and then we fell into some more kind of the decline of interest around AI.

And then, all of a sudden we woke up and it's AI everywhere. And it's AI at your fingertips in a way that it never [00:03:00] has before. So when I first started working with the data scientists that are building and developing these AI platforms and tools, it was really technical people that were building these things, right? It was data scientists, it was the IT practitioners. It was line of business in the sense of, they were the ones kind of starting the use case discussion, but it was these data scientists and IT practitioners and really deep technical folks that were trying to bring these solutions to bear for the use cases that the line of business was developing.

And the challenge that arose obviously was like, we don't have the compute to be able to do this work. So that's when you started to see the rise of the GPU accelerated server. And I actually had the privilege to build a GPU accelerated server with Nvidia while I was at IBM. And so we had the compute challenges and then we realized it wasn't just compute, it was also data.

So then we realized that even if you figure out the compute challenges and the software limitations, you then [00:04:00] have this problem of garbage in, garbage out. And I would say we're still facing that limitation across the board, right? That our data is not cleansed in the way that it would need to be in order to run great AI models.

And then of course, compute continues to still be an issue. So you've got some, pretty significant technical limitations that have always kind of, come to bear in the enterprise world. What's exciting now is we've moved into this AI everywhere mindset where you have these really large language models that are being developed by folks like Open AI and Google, Microsoft, et cetera.

It's really democratizing AI in a way that I think we never really expected, right? I, if you had asked me in 2015 when I was working on a GPU accelerated server. I would've told you that you would always need a data scientist to run AI workloads. And that's not the case, right? I planned a vacation two years ago, 100% using chat [00:05:00] GPT, and my stepson, is now superpowered by AI in college. And what we're realizing is you have to be comfortable with the technology and we're not at the point now where AI is going to replace you, although maybe, down the road that might be the case. I don't, personally, think it's coming, in the near term future of that replacement, but it is augmenting and you will be left behind if you don't know how to leverage AI.

I think as we look at our teams and the, functions that we run as marketers, we have to really ask ourself those hard questions of are we supercharging our teams with the power of AI? And are we building AI native workflows and processes within our organizations in order to be able to do more with less?

And that's really what AI, I think can offer as we start to think about. Embedding these tools that we don't have to develop, right? We no longer [00:06:00] need the data scientists in order to develop these AI tools because there's teams and companies that are built and, really looking to solve our problems with these AI enabled tools.

So it's a different mind shift, I think, than where we were, 10 years ago.

Erik Martinez: Do you have a simple use case that you could give the audience to set the stage for what that might look like? Because I think, part of it is like what part of my operation or what part of my workflow do I really need the place? Everything we've read, everything we suggest to our customers is fine. Like, find those really repeatable tasks that you can teach AI to do, right? But what's a really good use case for a marketing team to think about?

Kimberly Storin: So for marketing, I think the clearest and cleanest use case right now is content. I think content [00:07:00] generation and the ability for AI to superpower your content generation is at our fingertips right now. Our team uses a tool called Jasper and we're, very happy with that tool. We use chat, GPT regularly to solve that problem, I've played around with other, content solutions as well. And it's not an end all, be all. Again, it doesn't replace the human, but can it make your first draft or your outline faster? Absolutely. Can it make your revisions and your editing and your grammar. Faster? Absolutely. And so I think, when I'm stepping back and saying, what's the first use case that I would try to leverage AI in terms of making it. Easier, faster, better. I think content is, one of the first ones to go attack.

I think there's, you know, there's other things. We've been using chatbots for a really long time and so that's another place that I think [00:08:00] is, a pretty easy sandbox and a place to really think about, how do you play around with the, power of AI is in the chatbot. In some of the intent-based tools that are being brought to market.

And then of course, analytics is another great place that you can really start to play around with. I find that the analytics piece, when you can get the prompting right, because at the end of the day, AI is only as good as your data and your prompt engineering. And so if you can get that prompting right and that data right there is a lot of power in analytics, but I think it takes a little bit more time to ramp up and to see those results.

Erik Martinez: You've mentioned several times now in our conversation so far, I'm gonna paraphrase here, but you're talking about data gaps and data problems. I'm actually prepping a discussion next week for a summit on multi-touch attribution. And one of my positions on multi-touch attribution is that [00:09:00] it's limited by a number of factors. One data collection on the pixel side, even if you're using server side tracking isn't perfect. It's much less than perfect, right? Second thing is, if you are a smaller brand, and you've work with some enterprise brands, but if you're working as a smaller brand, you may not have budget to be in all the places.

And so your data set is limited to just the things or the programs that you're running. So your multi-touch attribution model might. Uncover some truths, but it's also missing other truths because you either have incorrect tracking or you're missing data because you are not investing enough to generate data.

How do you propose marketers get around that issue or start tackling that issue in a systemic way to improve?

Kimberly Storin: I think part of it is, picking some use cases where [00:10:00] you are not as dependent on the data and use that as the testing ground. That's why I really like content, right? Content is a way like, yes, Jasper absolutely lets us load up our brand voice. It learns from the work that we're doing. It gets better and better over time as we continue to train it on our brand and our voice and our tone, et cetera. So it's absolutely true, but it's also not 100% dependent on the data that's loaded in, like you might see. In a intent based model or an attribution model, right, where that gets a little bit more challenging.

So if you're trying to build a culture of AI adoption and build a culture of experimentation within your team, there are use cases and opportunities for workloads that would give you the chance to start to build that muscle memory and build 'cause so much of it. Is cultural, [00:11:00] right? How comfortable are people in your organization with learning these new tools and technologies that will supercharge them?

But there's still some hesitancy. Will this replace me? Will this take my job? And while I don't think that's the case. Right now, at least. You do have to help them overcome that hesitation. And so picking those tools Another one I love is Zoom transcription, right? The AI Companion. It's great tool and it's a great way to start to understand the power of AI at your fingertips in a way that gets your team comfortable with that. Being able to transcribe notes from interviews or research or be able to do competitive analysis. All of those things supercharge your team and get them over that cultural hurdle, and then you can go tackle the big ones.

Erik Martinez: Yeah, that makes perfect sense and is excellent advice. I was reading some of your articles and one of the things you mention is the importance of moving [00:12:00] beyond the isolated AI experiment. What do you mean by that? And how should marketing teams integrate AI into their strategies holistically, because I think, you're talking about, "Hey, we gotta change our culture", right?

But then how do we get out of this sporadic testing mode?

mode

Kimberly Storin: Yeah absolutely. I do believe that rogue AI experiments lead to mediocrity. I think you end up spending more than you plan to. I think you may spend in places that you are not realizing that you're spending if you are not controlling it. Obviously, data can be put at risk.

There's a lot of potential bias as well that can come out come to the surface in those little experimentations that happen. Like if somebody's kicking the tires. I used to see this where I would have, IT folks building mini server farms under their desk, literally. With [00:13:00] GPU accelerated servers and they would go around in their company and basically challenge them. I can run a campaign faster than your marketing team or I can build a chat bot that looks like this. I wanna prove it out. And it was almost shadow IT in a way, right? There were costs, that were being assumed by these decision makers, and what they were really doing was just kicking the tires under their desk, and there was no control.

And I'm starting to see that in terms of marketing, because everybody inside a marketing organization is playing around, and some of it might not be, causing harm to the organization, right? If everybody's leveraging chat GPT, the free version. Maybe there's minimal harm in that.

But once the organization is purchasing enterprise class AI software for content, for analytics, for product marketing and competitive research you can quickly lose control of, your return on investment. And so [00:14:00] that's why I think it's really important that you have a planned and focused approach that is very much based in cultural adaptation in order to move the needle. And I think it starts at the top. It needs an executive mandate with a clear objective and a framework for collaboration across the team.

And then I think it also requires systematic and standardized approach. Almost what I would call a center of excellence model. Where you have a marketing AI champion, sometimes I call them a spiritual leader, right? Who have really invested in understanding the nuances of AI, prompt engineering, the importance of data and the importance of cross organization collaboration of working closely with the IT team, making smart decisions from a security standpoint for the organization, and then really leading with that intent and structure across the board. Stopping those one-off [00:15:00] rogue experiments is really important because the team should embrace a mindset of experimentation across the board. Versus just seeing that in pockets. And then once you start to see that agility and curiosity and kind of the adopt and go mindset, if you will, inside the organization, you can really start to pilot those AI initiatives

And with an experimentation mindset that looks like scaling or killing it quickly, you're monitoring the results. It's overseen by this core AI champion, even though there may be other teams involved in running, the work through that platform, but it's all overseen by that spiritual leader. And ultimately becomes a decision of how quickly are we seeing results?

Where are we comfortable with the progress that we're making? How do we double down and scale that or where do we kill it quickly? And at the end of the day, it is the processes, the [00:16:00] tools, the data, and the people. Way more than it is just a, technology in and of itself. And so having those processes and having the ability to really look across the organization and determine, is this working? Am I seeing the results that I expected? And how long should I be waiting for those results to manifest? And sometimes. Some of these tools are easy, plug and play. Some of them require pretty significant integration with your CRM system or your intent data or your website, et cetera. And those things take longer, and they do require patience, and they require collaboration with the customer success team at the vendor that you're working with, in order to truly understand what that integration implementation process might look like, that timeline, and ensuring that you're baking that into your assumptions and your ROI payback as [00:17:00] well.

Erik Martinez: So let's unpack that a little bit. What I heard you say is a couple things. One, you should have somebody in your organization who's championing this process and you're investing in that individual training and giving them some authority to experiment within some bounds. When you're thinking about an individual, what are the qualities that person needs to have in order to kind of assume that role? Because, we're working with a lot of marketing teams that are very small,

Kimberly Storin: Yep.

Erik Martinez: Right? They're really pretty small. They have to run very fast. They have lots of hats that they wear, and, I've seen smaller marketing organizations and large marketing organizations, we all have the same problem, there's way more to do than we could

Kimberly Storin: Of course. Yeah.

Erik Martinez: So if you were sitting in charge of a mid-size enterprise and you were gonna [00:18:00] pick somebody, what are the qualities that person would have and then what would be the first type of project that you would task them with?

KImberly Storin: So I think there's three qualities that I would look for innate curiosity. Somebody who is just interested in learning and doesn't assume that the status quo is the only way. So just inherently curious. And then I think I would also look for somebody that is trained in agile marketing.

And I know, agile marketing obviously. I mean at IBM it was 27 steps to being agile, which is not really that agile, but let's take the capital A out of the equation, right? And thinking about agility as a lowercase A. And I think as you think about, curiosity is kind of that ability to look forward and agility is the ability to look back and to tweak and modify and enhance and optimize what may or may not be [00:19:00] working. In that postmortem

Erik Martinez: The ability to iterate.

Kimberly Storin: Perfect. I love that. The ability to iterate. Then the third piece is feeling comfortable with calculated risk taking. So many times, like you'll see folks who get into this kind of role and. They're not comfortable in making and recommending calculated risks because there are a lot of unknowns. And yes, you have to mitigate the downside, obviously, but you also have to figure out how to bring people along and. Get them to buy into some calculated risk taking. So I'd almost say that last piece is almost twofold, right?

Erik Martinez: Because it's being comfortable with the calculated risk taking themselves, but it's also someone who can work collaboratively across functions and bring that, spirit of agility and curiosity and calculated risk taking to others. [00:20:00] And so I do think that there is this underlying attitude that will make or break your AI spiritual leader, within your marketing team.

I've worked with a lot of marketing teams and technology teams over the years, and I can tell you it's the person who can speak geek and speak normal right? To a certain extent. This notion of calculated risk taking, I find fascinating because I think a lot of our organizations are reasonably conservative,

Kimberly Storin: Yep,

Erik Martinez: Right?

Not necessarily entrepreneurial in the classic sense. I have a client and he is a classic entrepreneur. He will spend $99 to make a hundred dollars. He doesn't think about necessarily the costs of what he does. Right? So he just takes risks all the time.

But you're not suggesting that, you're suggesting the person who can say, "Hey, here's what I think the outcome's gonna be", [00:21:00] right? " Here's where we think some of the pitfalls might be, and here's our unknowns. And we just don't know until we run the experiment or we go through the process".

Because I think one of the challenges is when we start that process. I've got the story of. Way back when I started my career, I was working with a company on a neural network. And we had all the data challenges that we talked about at the top of the show. But we had executive buy-in, like this is what they wanted to do. They wanted to be able to forecast sales for their advertising programs using these neural networks. And this was 30 years ago. So, the data coming outta the system was very rough. But you had this scenario where we just, couldn't make enough progress fast enough. Like we finally cleaned up the data. We started training the thing, and it was just spitting out all sorts of random garbage. And so we ended up killing the program after about six or seven months.

How do you [00:22:00] avoid that pitfall? And what are the measures? Because you've got this person in charge who's trying to move the ball down the field, so to speak, and yet, it feels like they're getting sacked behind the line every single time. How do you mitigate for that type of scenario?

Kimberly Storin: I think the way to mitigate for that is to have the mandate start at the top. So if you as the CMO right, or you as the VP of marketing are not fully bought in, educated and continually updated on the progress that the team is making, like you can't have their back. And so that bi-directional communication up and down and ensuring that the executive in charge is clearly bought in and supporting the programs and the initiatives, I think takes away that inherent feeling that you're getting sacked from behind, right? There should be no surprises either way. And that requires executive support, [00:23:00] executive communication, and constant updates both sides. And that requires collaboration.

The CMOs best friend in this process has to be the CIO and the CISO as well. So making sure that you're not gonna get blindsided by IT requirements that you're not prepared for, or security challenges that you haven't thought through. And I find that those are often the places where the blindsiding stems from and as you pursue. A more tech forward approach to your marketing organization, the more that you need to be sitting with your CIO, Chief Data Officer, CISO and really understanding their care abouts and ensuring that they have your back as well. And I think that executive alignment and executive sponsorship will help stem some of those challenges downstream.

Erik Martinez: Awesome. Let's pivot [00:24:00] a little bit. You have talked about in this day of technology maintaining human connection. Connection with your customers and quite frankly, the people within your own organization. How do you view the role of technology in today's marketing world and trying to maintain that human element as you're going about doing your daily work?

Kimberly Storin: I think it's really critical, right? I think people crave connection. I think organizations are seeing the benefit of that connection come through, and whether it's creativity or agility or just, ongoing speed of collaboration and that collaboration can happen with your customers, that can happen with your partners. Obviously it happens within your own teams.

And so again, kind of, going back to the importance of building a system. The processes, tools, data, and people. Like people [00:25:00] are such an important piece of that. And when we think about being, in B2B especially, right? Sometimes we forget how critical. It is. This is an emotional decision. People are making a million dollar decision and their job is on the line, their reputation is on the line, and we as B2B marketers often forget how critical that emotional and human connection is across our customers.

So ultimately, we do our best jobs when we make them the hero of the story. And that comes down to connection. So I think it's absolutely critical and I think, there's so much on the line, especially in B2B, that you have to be able to create that emotional connection.

Erik Martinez: Whether it's B2B or B2C, I think that's the same story, right? At the end of the day, we want to create meaningful connection. What does your team do to ensure that you're maintaining that human connection, [00:26:00] even as you're leveraging some of these more powerful technologies.

Kimberly Storin: Yeah, so we built a marketing manifesto. We obviously have cultures and values at Zayo that all of our teams like subscribe to, but within a subset of that is this marketing manifesto. And we've been really clear from a marketing standpoint the values and attributes that we want our team to demonstrate. That includes that there are no bad ideas. That includes that we unite to get it done. And those things really have kind of ingrained into the DNA of our marketing team and helped drive forward. The collaboration and the speed of agility that we're looking for in terms of being able to react to the market and being able to be the voice of, and the voice to the market.

So we started with the manifesto and that's really critical. And then because our team is distributed, we've got a team that [00:27:00] sits in Denver, but we also have a lot of folks that sit across North America. And so we built a culture committee that is a monthly connection point for all of our teams. We also have an internal Gchat Slack channel, right? That is really dedicated to connecting the team. We have a weekly question that we ask the team that is personal or professional, depending on the week. Somebody is assigned to be that chief Vibes Officer, every week to come up with a question that kind of spurs the connection.

And then every year we rotate out the two people that lead our culture committee and they're in charge of planning those monthly activities. It can be anything - like we've done, you know, MTV cribs, show off your workspace. We've done learning and panel discussions with marketing leaders that we've brought in. We've done just a variety, really, of [00:28:00] kind of get-to-know-you, team bonding, and learning and development. And they know to look forward to those cultural events every month. People carve the time out, they make the space for it, and really show up to help each other. And I've really seen, that marketing manifesto in particular really manifest itself in terms of the actions and the behaviors, and the team cheers each other on, right? One person's individual win is a team win. And you really see that across the board.

Erik Martinez: That's awesome. I think those are some really simple ideas to implement because, you know, my team has been distributed from pretty much day one and we do some of those things. But you mentioned a couple things, I'm like, I need to incorporate that into what we do as well.

Let's expand out to the customer now. How do you maintain that connection? You know, let's just talk about [00:29:00] advertising for a moment. Right. We're out, prospecting for new customers to come into our sphere of influence. And there's a lot of research that says, we can put the best promotion and that may be a trigger for somebody. But more times than not, the trigger really is more emotional than it is rational.

Kimberly Storin: Right.

Erik Martinez: So how does your team go about planning their advertising efforts on all the various channels to try to create that connection with the end consumer?

Kimberly Storin: So really think about it: when was the last time that you gave somebody your contact information and said, please call me and interrupt my workday and send me a bunch of spam that I didn't ask for? Right. It's been a long time. It takes a very good piece of unique content that I can't get anywhere else. And there are very few pieces of content right now that would get me to give you my personal contact information so that you can spam me. And [00:30:00] so for us, like what we like to be thinking about, so we view ourselves as the voice of, and the voice to the market. That is what we believe, in our team, that marketing's job is to do.

And we also know that it takes 15 touches to get anyone to make a decision. We know that people want to do 80% of the research before they talk to a seller and so that makes us think about how do we create the moments that matter? How do we be there in the moments that matter? How are we, first on the mind of a decision maker when it matters most, and so it really comes down to are you effectively leveraging all of the channels at your disposal? To be the voice of, and the voice to the customer means that you have to know your customer and know them inside and out, and understand the psychographics and understand where they get information and be in the relevant places where they do get [00:31:00] information. If there is a buying committee. Are you influencing the buying committee at the right time?

So for me it's never about a Super Bowl ad. Although maybe there'll be a time and a place that I do a Super Bowl ad. But it's more about that deep understanding of the psychographic of my enterprise buyer and ensuring that the channels where they spend their time, the people that influence them, the information that takes away their pain points, the content that makes them feel like a hero. That's what I wanna be part of. And it takes a lot of work on the research side to really understand.

Where the right media mix is for that buyer, and every buyer has a different strategy. So you can have a framework that you can generally apply, but there's never a one-size-fits-all, because every buyer group has a different pain point, [00:32:00] has a different psychographic and demographic view and spends their time in different places with different influencers and your product can have a variety of product market fit. You know, either great product market fit or some challenges. Or not differentiated. Or differentiated.

And so you've gotta be able to look at all of those vectors and really build a go-to market strategy that speaks to that buyer. And don't get caught up by the trends or what's in, because at the end of the day, reaching your buyer is your number one concern. Understanding your buyer is your number one concern and their ecosystem.

So I think sometimes it's easy to kind of get caught up on all the things like we cannot cut through the noise anymore. It's just impossible, right? We can't capture attention anymore. Earned media doesn't have the same value that it used to, paid media absolutely does not have the same value that it used to. So how do you find the right place at the right time [00:33:00] and the right mix that influences your people that you're trying to sell to?

Erik Martinez: Yeah I totally sympathize with that every single day for every single one of the clients that we work with. It's definitely a challenge to cut through all the noise that we're getting bombarded with, let's bring these two things together now, and, just kind of thinking ahead, what do you believe is the most significant opportunity for leveraging AI to enhance digital customer engagement while still maintaining those authentic connections that we just talked about?

Kimberly Storin: I would say it's all the things that we talked about at the beginning, in terms of using controlled experimentation to find the tools that work best for your team. If content is a place that you can see the uptick pretty quickly, like picking those things and leveraging it as a superpower, but not thinking about it at a replacement for human [00:34:00] intervention.

Like if you write a blog, 100% on chat GPT, or a enter content tool here. You will not create a connection with your buyer. If you create an outline through those AI tools and your content team helps write the first draft, and then you use those content tools again to refine and simplify and, really build clarity into the content. You will end up with a great piece of content that moves faster through the workflow, that still creates that connection. So I think it's playing around with the technology and your organization to find that right mix. How do you ensure that you're not replacing the elements where you do need those connections in order to drive, the next level of relationship with your customers?

Erik Martinez: Yeah you're really talking about how do we accelerate the process and not completely overhaul the process, right? You probably have a good process in place, but you can leverage the [00:35:00] technologies to enhance it. As we move to close what last piece of advice would you like to leave with the listening audience?

Kimberly Storin: I think the last piece of advice that I have is. The same three attributes that I said are critical in your spiritual leader are critical for you as a marketing leader. Embrace curiosity, be agile, lowercase A, look back, see what's working, see what's not. Iterate, right? Experiment, and then start getting comfortable taking those calculated risks.

We are in an era of time that technology is changing so rapidly that we have to be comfortable, and we also have to be comfortable saying, no, that doesn't work for me or my team right now. And I'm okay with that. Like, we gotta get rid of that FOMO attitude. But we also have to embrace taking calculated risks.

Erik Martinez: [00:36:00] Awesome. Kim, thank you so much for your time today. If somebody wants to reach out to you, what is the best way?

Kimberly Storin: Find me on LinkedIn.

Erik Martinez: Awesome. Thank you again for coming on the show. I personally have learned a ton, so I really appreciate that and I know the audience will have a lot of good takeaways from our discussion today. So thank you for listening to today's episode of the Digital Velocity Podcast. Thank you and have a great day.

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