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Our listeners and clients work in the agency world and they are faced with challenges such as cookies going away, mobile ID’s going away and more. All of these changes lead to relevancy becoming even more elusive. Relevance depends on data. So it stands to reason that AI will fill the gap lost in the endless quest to improve relevance, as less data flows through the industry.
The industry is a crowded landscape with many moving parts. But agencies have always had a uniquely essential place. A place defined by big ideas. Big creative ideas. Big media ideas. Big ideas that move the industry forward… culturally, technologically, even methodologically.
Join us as we explore relevance with a great group of guests:
- Grant McDougal, CEO and co-founder of blue ocean.ai
- Josh Ehart ad industry veteran global digital agencies, global creative agencies, he was Energy BBDO’s first ever Chief Innovation Officer and it’s first Chief Data Officer
- Jason Goldberg, Chief Commerce Strategy Officer at Publicis
- Rishad Tobaccowala, Senior Advisor to the Publicis Groupe and author of the best-selling book: “Restoring the Soul of Business: Staying Human in the Age of Data”
- Jeremy Lockhorn, Global Head of Partner Solutions at Ericsson Emodo, speaker, mobile marketing expert
Listen as Jake and his guests explore AI in five core agency services. Across all the value, performance, ideation and capabilities agencies provide for their clients, there is one common ingredient that will power a lot of future ingenuity in the agency model, AI.
The FIVE list:
- Brand tracking and research
- Planning
- Creative
- Media Buying
- And Measurement
Looking for some fresh bonus content, visit us here emodoinc.com/podbonus.
The Five podcast is presented by Ericsson Emodo and the Emodo Institute, and features original music by Dyaphonic and the Small Town Symphonette. Social media and promotional content was composed and conducted by Lyon Solntsev. This episode was edited by Justin Newton and produced by Robert Haskitt, Liz Wynnemer, and Jake Moskowitz.
Transcript of AI E5: AI is for Agency Innovation
Jake:
Hey, it’s Jake. Before we get started, I wanted to take a second to just genuinely thank you for listening. We’re humbled by the growing audience of the show, and we wanted to do something for our listeners. You know our episodes feature segments of insightful discussions with industry thought leaders, but we don’t have time in the show to include the full length interviews, so we’re posting some of them on a special page of bonus content.
This episode includes a segment of one of our discussions with Rishad Tobaccowala. You can find the full interview at emodoinc.com/podbonus. You’ll also find a link in the show notes for this episode. We’ll regularly add more interviews and other content. You might even find some free swag there too. That’s emodoinc.com/podbonus.
Okay, here’s the show.
Josh:
I think the agencies that will succeed using AI are the ones that in their core DNA are willing to allow the answer to be agnostic.
Jake:
Let’s talk AI. Welcome to FIVE, the podcast that breaks down AI for marketers. This is episode Five, AI is for agency innovation. I’m Jake Moskowitz.
You don’t have to be some grizzled ad industry veteran to recount multiple existential threats to the business of ad agencies, challenges that were ultimately met by agencies with innovation, resilience and reinvention. Remember it was widely believed that Facebook wanted to disintermediate agencies, now they employ a huge staff to service them. Remember, independent nimble digital agencies were going to make the holding company model superfluous, laughable today. Remember big agencies didn’t know how to buy digital, then trading desks evolved.
I’ve been in the ad business for a long time. I think it’s as creative as any industry in the world, not just because of ad creative, or the industry’s capacity for creativity at a strategic level, but also for its ability to continually creatively evolve behind the scenes. This industry is a crowded landscape, with lots of moving parts. But agencies have always had a uniquely central place, a place defined by big ideas, big creative ideas, big media ideas, big ideas that move the industry forward, culturally, technologically, even methodologically.
While their work sparks imagination, and tugs at emotions, operationally, they’ve learned to become incredibly innovative when it comes to new ways of working. They’ve implemented trading desks, data repositories, new technology integrations. And once again, agencies are already innovating with AI, getting their top strategic minds around the way AI can help them evolve and maintain that a central place in the value chain. A lot of our listeners work in the agency world. You guys know the challenges, you’ve got cookies going away, mobile device IDs going away, etc, etc. A lot of visionary agency folks are concerned that relevance is about to become more elusive. Unless, we do this one thing, which we’ll tell you right after these words from our sponsors.
No, come on. Seriously, there’s no magic bullet. If you’ve listened to the show at all, you know that I’m not a hyperbole guy. There’s rarely a single simple solution. But I will say this, when you look across all the value performance, ideation and capabilities agencies provide for their clients, there’s one common ingredient that will power a lot of future ingenuity in the agency model. That’s AI.
You don’t have to be an insider at all to know that digital advertising misses the mark most of the time. In fact, anyone who’s ever ignored a banner ad will tell you that they’re still inundated with messages that are rarely relevant. Relevance is key, relevant audience, relevant context, relevant creative, and many agency folks believe that in a world with fewer cookies and device IDs, relevance is likely to become even more elusive.
Of course, relevance depends on data. So it stands to reason that AI will fill the gap we lose in the endless quest to improve relevance as less data flows through the industry. In our last episode, we learned that AI rewards scale. And that benefits the big data rich ecommerce platforms. Does that mean that large agencies and holding companies have a similar advantage because they have more data or better differentiated training data? Or does AI benefit the challenger agencies, as quantity of data no longer carries as much power as quality?
If you work at an agency, big or small, whether your clients bring their own data to the party, or your agency has plenty of its own, this episode is for you. In this episode, my guests and I explore some of the thinking behind AI in a number of core agency services. Oh, and when I say a number, that number is five.
Here’s what we’ll touch on. Brand tracking and research, planning, creative, media buying and measurement. As I talked to my guests, keep these five agency functions in mind, when you hear one of these key points, you’ll hear a ding like this.
Grant:
I’m Grant McDougal. I’m the CEO and co founder of a company called blueocean.ai. We’re based in San Francisco.
Jake:
When you think about that baseline of where a brand stands on their market before a campaign or before agency involvement, Grant’s AI based business is an interesting place to start.
Grant:
We think about brands as people, products or companies that write about themselves, have something written about them, and exist in the minds of a customer. And so what we’ve done is we’ve stepped back to really understand what a brand is, and we call it the blue score. It’s a number out of 50 to 200. And it really is a brand equity measure, but by only asking two questions, right? So we ask you who your competitors are and what your brand is.
We then go away and we look at five big factors and familiarity is the first. It’s traditionally a share of voice measure, how well are you known? And underneath that, we have a number of sub factors or metrics. The first being, you know, how much are you spending on the media side of the house? How much traffic are you generating? Really, what’s happening on the content that you’re actually generating? Is it shareable? Is it connected and then we compare you relative to your competitive set. That allows us to understand how well you’re known.
We then look at uniqueness and uniqueness is all about product positioning, right? And so we’ve broken that down into two big areas. The first is the functional elements of the brand. What are the feeds and speeds and how well is it performing? And then we break out memorability and memorability is the softer, more intangible elements of the brand. And what we’re looking for there is, how connected are you to your customers?
The third element is consistency. And you know, most of us as marketers, have heard this before: right time, right place, right message, but building your message over time. So we’re using things like personality models to understand how your content is performing across channels, how much volume you’ve got in the market at any one time and then, do you have stability across those channels. High consistency talks to really good excellence of marketing.
The fourth measure in the model is all about relevance and market share. And so we’re bringing in financial metrics, we’re doing things like SGNA benchmarks, revenue performance, changes relative to your competitors. And we really think that having those financial core metrics are essential to understanding a brand’s performance, because if you’re selling more, and you’re outperforming your competitors, obviously, you’re growing.
The final component is revered and revered is really about understanding sentiment relative to your competitors. And the conversations that your employees are having to understand how well the brand’s performing from an emotional connection to the product. That allows us to look left to right across the brand and index you relative to your competitors. And so we give you a really simple score out of 200.
Jake:
Awesome, that’s clearly an area relevant to lots of brands, could you maybe touch on some of the other areas of marketing you feel are most ripe for disruption as a result of AI?
Grant:
Yeah, I think the other areas that are going to be very much ripe for all of the kind of disruption we’re talking about is media planning and buying. I think that is an area we’ve obviously generated enough programmatic data. So you know, automated bidding. I think as we move out, you know, there’s going to be, you know, brand strategy as a whole. There’s going to be a real shift to brand strategy as a service. And so you’re going to see downward pressure on management consultants, and legacy providers that have been in that category as a whole.
Jake:
So your company has taken something that used to be manual and made it automated. But I imagine that the actual process of your clients using the product is not completely automated, I imagine there must still be some sort of a human element to it like a consulting type of an element to supporting your clients. Is that true?
Grant:
Yeah, I think that’s a great insight. You know, over two years, we’ve recognized that when working with enterprises, what they want is, they want a real time solution, which is data driven. But they also want a person. You know, they really want the human connectivity between that number and the action. And so that was a revelation to us, because we thought we would just automate it and everyone would look at it, and there would be automated insights. We still got that. But there is a role for people in this. And it’s exciting to see that it’s creating opportunities.
Jake:
Grant McDougal of Blue Ocean AI, I appreciate you joining the pod.
Grant:
It’s been my pleasure.
Jake:
When I was talking to Jason Goldberg, Chief commerce Strategy Officer at Publicis for our retail episode, he also shared some insightful thoughts about large versus small agencies. Jason, obviously, you have a lot of experience in retail, but you’ve also spent many years in the agency environment. Many of our listeners are from the agency world, how do you see AI impacting agencies?
Jason:
Yeah, so again, it depends, right? Like so if you’re a small independent agency, and unfortunately, there are fewer and fewer of those left, you probably have that same math that that independent retailer or new digitally native brand has. It’s probably going to be too difficult and expensive and too much of a long term investment to build. So you’re probably in the buy space.
But if you’re a large agency, or you’re owned by a holding company, which most of us are, right? So you know, Publicis is a giant holding company, WPP, Omnicom, it probably makes sense for each of those to make some significant long term strategic investments to differentiate themselves from their competitor, right? The problem for that small agency is, it’s very impractical for you to differentiate yourself based on the quality of your AI, you can absolutely differentiate yourself on the quality of the tactical execution you do with that AI, right? But you probably can’t say, hey, pick me over my competitor because of the quality of my machine learning capabilities.
Jake:
But you can also differentiate on the quality of your data that’s being used to train them.
Jason:
Yeah. Although in the case of agencies increasingly, and maybe this will be controversial, I don’t think agencies should be claiming any dominion or ownership of that data, like we all work to serve clients. And it’s the client’s data, like I personally think it’s a pretty significant mistake for a brand to hire an agency and let that agency like own proprietary data, because if you’re Nike, and you hire someone, you know, an agency that uses ML to do your advertising campaigns, and you’re going to fire that agency or get tired of them in five years and hire another agency. And that agency is going to go take all that data and learnings that they use with you and sell it to Reebok, right?
And so I get how agencies would want to do that. If I were a client, I wouldn’t like that. That being said, like there are ways for agencies to bring data to the party that isn’t collected from their clients, right? And I think we’re seeing a lot of that. So like, obviously, I can speak most intelligently to what we’re doing at Publicis, but we have hundreds of PhD data scientists, we do try to build unique capabilities that we can use for clients that we can train with those clients’ data and deliver better experiences, right? And I would argue like most product development teams, we’ve had mixed results there, we have some phenomenal wins. But not every investment we have made in that space pays off. But I do think in aggregate that that’s a differentiator and a smart advantage.
But then what we did sort of interestingly is a number of us, including Publicis, have gone out and bought data companies, right? So Publicis acquired Epsilon. And so we now have access to data on 150 million consumers that are either new consumers to our clients, or that we have a lot of supplemental insight about that we can use to augment our clients data, you know, and all of that can be used to inform the machine learning models that improve AI. So I think, you know, again, those are advantages. You know, there’s only a handful of companies that can go out and buy a $4 billion data acquisition. So those tend to be advantages for the largest players in the ecosystem. But I do think those are smart investments where they make sense.
Jake:
Thanks again. Jason.
Jason:
Thank you very much.
Josh:
I think the agencies that we’ll succeed using AI are the ones that, you know, in their core DNA, are willing to allow the solutions that they develop to be agnostic.
Jake:
Josh E. Hart is one of those ad industry veterans, global digital agencies, global creative agencies, he was energy BBDO’s first ever Chief Innovation Officer, and its first Chief Data Officer. I spoke to Josh about creative versus media agencies, and about what will enable agencies to make the best use of AI.
Josh:
There’s a lot of bias in the agency world around this is how we believe we can build and grow brands using this finite set of tools. And you can see it at all different points in the spectrum. You know, whether it’s a creative agency that believes that that rich video storytelling is the best vehicle to build that connection, versus a digital agency that is going to think of an opposite solution of a more digitally driven experience. So the agencies that can be most successful are the ones that are willing to follow that data and that AI to its logical conclusion and to what those solutions are.
Jake:
Is the creative side of the house at a disadvantage in terms of using AI simply because the media side is far more experienced with depending on data to make decisions, whereas the creative side is more focused on the traditional human magic?
Josh:
Yeah, I think so I think one of the challenges on the creative side is, is really sorting through where does AI sit in the process, right? Like, you could crunch a lot of data to get really specific around what should be in a scene for a story, for instance, or, you know, some other aspect of telling that story. One of the ways that we’ve talked about it with creatives in the past is early in the process, figure out what you want your story to be. And then maybe later in the process, use AI to help you determine what is the most effective way to present that story to a consumer or a customer? So it might be just a little bit of conversation around where to think about it.
Jake:
So along those lines, what would you recommend to young marketers in terms of planning out their careers? Like what should they be good at? What should they not be good at? What kinds of roles should they be looking for?
Josh:
I’m a big believer in range and sort of breadth of experience, just personally, it’s what I’m excited by. But I think there’s a practical benefit to it as well. I think marketers need to be well rounded, they need to experience different parts of that marketing landscape for themselves and understand the tools at different points in the process because it will give you the base of knowledge that you need to sort of truly manage a brand experience across a lot of different touch points.
And then I think, you know, the underlying expertise around understanding technology, understanding that data landscape, I mean, the last two years I spent really diving into, you know, that sort of media data, audience landscape. I learned a lot about how those things link up. And that’s of huge benefit to marketers. So I think, you know, really thinking broadly and sort of looking at different opportunities as what does this add to my arsenal of tools that I can deploy? And data being, you know, the newest and probably most future focused.
Jake:
You’re focused on broad experience, broad skill set. Is that a sign of the times? Like would you have said the same thing 10, 15, 20 years ago? Or do you think things are changing to the point where a wide range of experience and skills is more important than it used to be?
Josh:
I think it depends on who you ask. I think there’s been a lot of movement, you know, particularly in the agency world, there’s sort of this push pull between the role of specialists. So everybody had social teams, everybody had mobile teams, now you’ve got commerce teams, you know, really, that’s all digital marketing. And if you have strong sort of digital marketing fundamentals, you know, where does the specialization get you? In some cases, it’s speed and efficiency, because people understand those spaces.
But I do think, you know, as agencies and companies continue to evolve, no one has the resources to hire everybody. You know, if you’re running a brand, whether it’s on the agency, or on the client side, you’re not going to have somebody for every different thing. So who are those people that can really make sense of it all, understand where to deploy specialists, depending on the type of business. So I think that’s going to trend back towards that more general approach.
Jake:
Are there any specific examples you can give of where you’ve had success with AI? Whether at BBDO or elsewhere?
Josh:
Yeah, I think they were nascent. So we were really just starting to explore the datasets that we had access to a couple of example use cases. You know, we were looking at fast moving consumer goods and E-commerce and trying to understand how to better target within those platforms and customers and retailers. So one of the things we looked at as we sort of analyzed all of the keyword data and URL data that we could get our hands on to understand when people go and buy X products, what are the different search terms that they’re using in progression until they land on their products or the products that we’re trying to market.
So really thinking about that holistic experience of like, what are the adjacencies? What are those entry points? What are those words and phrases look like as a way to better align not only the the targeting, which is I think the obvious step, but really the content that we’re putting in front of them so that we’re really honing in on their needs and how they’re going to use the product or their thinking about that usage.
And then another one in a similar vein was really, you know, a lot of what we were doing is trying to understand context, and context around usage occasions. So really looking more broadly at semantic analysis to really understand, okay, when people are engaged in this occasion, this set of content, what are all of the sort of contextual clues that we can extract from that data that they’re seeing in the content they’re consuming? So again, align from a creative and content standpoint, what we’re putting in front of them, so less keyword driven, but more context. And then, you know, using more simpler algorithms around, you know, more trigger based modeling. So whether those sorts of things.
Jake:
So let’s get specific. On the creative side, where do you think AI fits and where does it not fit? Whether you’ve had success with it or not? Like where do you see it thriving? Versus where do you see it not having much of an impact?
Josh:
You know, I think it could, it could have a tremendous impact, I think it’s probably less of a technical barrier than a human organizational change barrier. I think, in my most recent set of experiences, where I saw a lot of potential was and really better definition of who brands should be talking to? You know, I think in a sort of world that’s now quickly moving past us, it was very easy for brands to just talk to everybody, and you kind of sort out who you really should be talking to because they’re in there somewhere. Brands just don’t have the money to really cast as wide a net as they used to.
So for me, things like AI and machine learning can really help brands understand, okay, in this vast universe of people I could talk to, who are the people that I should talk to that ultimately could be the most valuable to me as a brand and business. So I think, understanding that prime prospect or that consumer, and the differences and the different possibilities within that, I think is one big area of impact.
And then I think on the creative side, you know, that’s a little bit harder to sort of divine, I think there’s a lot of sort of machine based, dynamic, creative opportunities. They tend not to have the sort of big sea creative impact. They can be very effective from a business standpoint. But I think we’re still looking for those sort of breakthrough creative examples. And I think as all sort of video based storytelling evolves and starts to better leverage data and AI to inform it. And the choices that are made, I think there’s some potential, but that to me is a little bit further out.
Jake:
So let me try to link a couple things because you mentioned segmentation. And when you said segmentation, I was thinking about the media side of segmentation, which to me is more about like, buy that impression but don’t buy this other impression, because that’s not in the right segment. Does segmentation also have an impact on the creative side too? Because you talk about this big C creative, like to come up with that big C creative, you’ve got to really understand your customer. And maybe AI allows you to do that way more specifically in a more detailed meaningful way than humans ever have been able to in the past.
Josh:
Yeah, I think there’s a natural sort of linkage there. And I think you could probably think about it in a really simple way. If I’ve got a good or a service that’s pretty universal. Let’s say it’s bottled water for instance. If I think about that bottled water, lots of different audiences, I don’t want to call them segments, I think you because you can think about audiences in a more fluid way using data. I think you have those different audiences, whether it’s, you know, athletic, whether it’s sort of the purity of the water versus regular tap water, you have those different things that obviously could influence the creative and that what you’re showing consumers and the stories you’re telling, you know, could be different. I think that makes a ton of sense. Where I was thinking is I don’t know how far we’re going to get into, you know, the details of those things yet.
Rishad:
Behavior is changing all the time and attitudes are changing all the time. And to a great extent, how a piece of advertising will react today is different because of COVID-19. Or the day after tomorrow, something basically happens.
Jake:
That’s speaker, author, industry luminary, Rishad Tobaccowala. I spoke with Rishad about examples he’s seen of successful AI usable by agencies.
Rishad:
So if you are running an advertising program on basically something to do with tea, it’s going to be feeling different today in Russia where one of the key folks that were poisoned by drinking tea, right? And you have to pick that up, because you have to constantly interrogate. The good news is most of marketing isn’t set and forget, because it involves this exotic thing called the human being. And I’ve always basically believed this, that it’s impossible to understand any one human being because we find it difficult to understand ourselves. But as importantly, one human being in a different mood is as different as two human beings. And that is what the machines don’t understand. They want to pin us into a corner and put us into a box, right?
Human beings cannot be pinned into a corner or put into a box.
Jake:
That never happens to me, I’m always in exactly the same mood. And with that, could you maybe speak a bit more specifically about examples of success in AI that you’ve seen?
Rishad:
So, you know, fundamentally, there are two or three areas that we basically see that sort of success. You know, the first broad success that we basically see, is understanding broadly patterns of behavior and figuring out what sort of either personas or scenarios we can think about. So it’s basically scenario planning. You know, you sort of let out scenarios, you plan scenarios and you back test scenarios. And you’ve also forward things, that’s sort of one area that makes sense.
Second is, we’re starting to look at this whole idea of can we get an understanding of a person’s emotional reaction to a piece of video? And how does that change based on who they are and where they are, but either geographically, but also who they are? And how does that change with different forms of video and what sparks off different people? So for instance, what we’ve now begun to realize is that any piece of video has triggering moments. Which is, triggering moments that either make you feel good about yourself, or make you remember something, make you remember part of your past. What does all of that mean? So we’re starting experimentation.
And then the last one is that we continue to find ways to use within Epsilon and other things, forms of sort of machine learning connected to media, to try to guarantee results, but in a strange and unusual way, where we actually, you know, are driving particular sort of outcomes we will be sort of marrying data, machine learning and media buying heft. And solving, you know, for those three particular things. Because when cost becomes one of the components you’ve put into something, but the cost changes depending on your decision, it becomes very interesting. Which is the cost of something continuously changes if you’re a large company buying media because if you start reallocating enough there, the cost can change dramatically. So this whole idea of like, what comes before the chicken or the egg? Which is could I basically decide that I’ve read a lot of money in this particular media platform driving down its unit costs. And because of that, making it effective, even though it wasn’t effective in the first place.
Jake:
Rishad, as always, thanks so much for your perspective.
Rishad:
Thank you very much.
Jake:
Before we go, hey, Jeremy, let’s go back through some of the key points we heard. Josh talked about analyzing keywords and URL data to get a sense for the usage occasions and the context for when people want products and are open to being convinced to use products. What did you think of that?
Jeremy:
Yeah, I thought that was super interesting. Everybody in the advertising industry has always been about delivering the right message to the right person in the right context. And then the promise of digital is that you can do that on a very one to one deterministic basis, at least for now, until IDs and cookies go away. But the reality is that the pre digital world relied on other forms of contextual cues. Things like what Josh was describing, what is the content that’s on the page? What is the weather at that current time and location? What are keywords that the user may have entered into a search and all of those things ladder up to a really important set of contextual cues that you know, using machine learning or artificial intelligence, you can really begin to discern the mindset of the consumer at that moment in time and deliver a really precisely relevant message.
Jake:
Yeah, when you said it, I took it into the context of planning, but I think that the way you’re describing it is sort of blends, planning and media buying? Because the same effort is important in terms of understanding who your audience is and how to target them and what messages to target them with. But also in the actual buying process in the real time decisioning, you know, specifying which creative, which message, which copy to put into a particular bid request, for example, so it could be both.
Jeremy:
Yeah, 100%. Answer your point. And it gets into creative as well, right? So it’s really three of the five all being influenced by those contextual cues. And, you know, I really liked how he was thinking about encouraging creatives to develop the story first, and then thinking about using artificial intelligence to influence the ways in which that story is told. And I thought that was a really interesting take on it.
Jake:
I thought it was really interesting when Rishad described that the acquisition of Epsilon enables Publicis to connect machine learning to media in such a way that you can guarantee results. What did you think of that?
Jeremy:
Well, first of all, I thought it was super interesting that both Rishad and Jason touched on the acquisition of Epsilon, obviously, being from Publicis and coming from Publicis myself, you know, that it’s clearly a key strategic pillar for those guys. So I think that vision of connecting dots in a way that enables you to predict performance is really compelling. I’m going to flip this a little bit, because I also thought that Jason’s comment about agencies should not claim ownership or dominion over a client’s first party data. I thought that was a really interesting sort of challenge, as you think about how do you leverage AI against all of these data sets. But I think his ultimate point was, it’s not that we don’t want the agency to have any data, it’s that we want the clients to own their own data and the agencies that are going to bring third party data or their own data to the party as well as a layer on top that makes everything work more seamlessly together.
Jake:
And then the one other thing I think we should touch on is measurement. Rishad described using AI to measure emotional reaction to different content. And I wanted to comment just for a moment, not just on that specifically, but that maybe that AI in the use case for measurement is going to grow in importance because of cookies going away and IDFA going away, there will be less ability to do one to one measurement. And maybe things like Rishad describes using AI to measure whether messaging is working is going to become more important over time.
Jeremy:
So I thought Rishad’s comment speaks to the ability of AI to have an impact on measurement in two different ways, right? One is in advance, before a piece of video or a piece of video creative ever sees the light of day and allowing the agency and the client to refine that message before they put it out in the wild, which I think is really powerful. And then secondarily is using AI once things are out in the wild to help measure things in a world where cookies and IDs have gone away.
Jake:
So to summarize what you were saying, I was talking about this in the context of measurement. But your point is that in some ways, the measurement itself is part of the creative process. And then you can use AI to leverage measurement within creative so it touches on two of the five and the five list.
Jeremy:
Yeah, exactly. Why wouldn’t you want to take the effort to measure the impact of that as best as you can?
Jake:
Thank you for doing this.
Jeremy:
Yeah, of course. Thanks for having me, as always.
Jake:
Talk to you soon.
Jeremy:
Alright, man.
Jake:
I’d like to thank my guests Rishad Tobaccowala, Josh E. Hart, Jason Goldberg, Grant McDougal and of course, our own Jeremy Lockhorn.
On the next episode of FIVE, we’ll take a look at best practices in marketing and selling AI powered solutions and what the takeaways are for the marketers who need to evaluate and purchase those solutions. Hey, and if you like the show, please write us a comment and give us a rating on your favorite podcast listening platform. We’d be super grateful. It definitely helps more people discover the podcast. Thanks for joining us.
The FIVE podcast is presented by Ericsson Emodo and the Emodo Institute and features original music by Dyaphonic and the Small Town Symphonette, original episode art is by Chris Kosek.This episode was edited by Justin Newton and produced by Robert Haskitt, Liz Wynnemer and me. I’m Jake Moskowitz.