May 11, 2019 | Written by: Amanda Thurston
Categorized: AI | Think Leaders
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Has AI raised the floor but not the ceiling with marketing? Have we over-indexed on having content at scale? And is there a way for marketers to understand when hyper-personalization will cross the line into creepiness? In this episode of thinkPod, we are joined by Kate Bradley Chernis (Founder & CEO of Lately) and Joey Camire (principal & founding team of Sylvain Labs). We talk to Kate and Joey about whether AI will replace human marketers, where we are currently with AI and marketing, the difficulty of getting marketers to write, and how AI can bring delight to consumers. We also get into the hot debate around a company’s responsibility with user data and imagine a future where each cup of yogurt is tracked.
Some of the questions we tackle include:
- Are marketers really ready to start implementing AI?
- How can marketers use data to push products forward?
- Are there brands that balance hyper-personalization with being human-centered?
Some quotes from our discussion:
“AI as it relates to marketing is raising the floor. It doesn’t totally feel like it’s currently raising the ceiling.” –Joey Camire
“I’m here to tell you that when marketing, it’ll never replace humans altogether because it just doesn’t work. They’re inherent components.”-Kate Bradley Chernis
“AI is not at the place right now where it’s saying like, well, based on my understanding of supply and demand economics, you should be changing your price model. What you choose to do with the understanding that the system is providing you is still going to land on someone’s lap. So your ability to be creative, your ability to write, your ability to wrangle concept and insight. What do you do with the information that you’re being provided from a system that is finding things that you might not otherwise be able to find.” –Joey Camire
“How can we consistently use that [hyper-personalization] in our messaging without compromising our brand? And so the way that we succeed in doing that is really being super emotional and human. And we look at AI as a way to enhance that and take the human work out of it.” –Kate Bradley Chernis
“I think with machine comes man and that creative and the beautiful part of marketing is still so critically important. To your point in order for us to be effective, you can’t lose sight of how important the human element really is.” –Host Amanda Thurston
About the panelists:
Kate Bradley Chernis is the Founder & CEO of Lately, an AI-powered marketing dashboard that’s reinventing the marketing process to give individual marketers the power to create and scale smarter, more consistent messaging. With Lately, Davids become Goliaths. As a former marketing agency owner, Kate, initially created the idea for Lately out of spreadsheets for then-client, Walmart. Well, not just Walmart. It was a partnership between Walmart, United Way Worldwide, National Disability Institute, and tens of thousands of local, small business and nonprofit affiliates who were all using her spreadsheet system – because they all had the same problems: a lack of coordination, widespread redundancies, no visibility and no organization. With Kate’s spreadsheet system, they achieved a 130%, three year, year-over-year ROI.
In fact, Kate found similar success with all of her clients, regardless of industry or company size. So, along with one heck of a superhero team, she created Lately to organize the mess, automate repetitive processes and eliminate the “overwhelming” feeling that every marketer she’d ever met had complained about.
Prior to founding Lately, Kate served 20 million listeners as Music Director and on-air host at Sirius/XM. She’s also an award-winning radio producer, engineer and voice talent with 25 years of national broadcast communications, brand-building, sales and marketing expertise.
After escaping from neuroscience and psychology, with a layover at the VCU Brandcenter, Joey Camire moved to New York to join the founding team of Sylvain Labs. Here, he leads innovation and brand strategy work for bluechip clients such as Google, GM, AB Inbev, Bloomberg, and more. Joey spearheaded several cultural projects including the documentary Instafame, as well as writing The Dots, a book deconstructing influence for brands and institutions in contemporary culture.
Along with a team at Sylvain Labs, Joey produces the weekly podcast Critical Nonsense, digging deep into cultural ephemera to inspire interesting conversations. A respected authority on the realms of social influence, strategy and cultural change, Joey has written for numerous publications including Wired, The Drum, McSweeney’s Internet Tendency, PSFK, The Egoist, and shots.
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Full transcript of the podcast below:
Amanda: Happy Friday.
Jason: Happy Friday.
Serena: We made it.
Amanda: Welcome to thinkLeaders. I’m Amanda Thurston.
Serena: I’m Serena Peters.
Jason: I’m Jason.
Amanda: And we just had a conversation about marketing of all things were on a theme, so we were joined by Kate Bradley Chernis and Joey Camire and talked a lot about humans.
Jason: We talk a lot about bias in the system, centering humans in the system, other such things that marketers are either looking at or overlooking.
Amanda: We brought up the juxtaposition between personalization and branding and the soft parts of marketing versus the hard quantification part of marketing.
Serena: We talked about AI but not necessarily in terms of data mining and the way that we usually talk about it. We talked a lot about data and sort of the responsible use of data and who actually owns data.
Jason: One thing I found particularly interesting is they spent some time focusing on where in the development cycle of AI being a helpful tool for marketing. And that we are sort of in the baby steps stages of it despite the advanced conversations we have about it. And they seem to sort of, I think more more skeptical than maybe a lot of the other people we have through here about how advanced and ready marketers are to use these tools and these tools are to be used. Which was an interesting.
Serena: Definitely, they think that we’re definitely more on the automation phase and than the actual personalization and implementation of AI, which is different to other conversations that we’ve had in the past.
Jason: Yeah, cause everyone’s rushing to embrace the personalization as something that’s available to be done very well and very well by machines. And it is still constantly a challenge people are running into. So maybe it’s a more helpful frame to think about that we’re like very early in doing this well and so maybe it’s okay that we’re not doing it perfectly. As long as we acknowledge we’re not doing it perfectly.
Serena: And that we nail the basics first.
Amanda: Like writing.
Amanda: The importance of things like writing.
Jason: Human stuff. You know, communication. The marketing.
Amanda: And even in personalization at scale, there needs to still be somebody there making sure that we’re not, I think the term that was used as stepping in it.
Jason: Yeah, used a few times.
Amanda: Yeah. So it’s interesting. It’s a little bit different than some of the other conversations we’ve had and I, I appreciate that they are not writing marketers out of history quite yet. So we’ll let you hit listening.
Amanda: Hi everybody. We are joined today by Kate Bradley Chernis who’s the cofounder and CEO of lately and Joey Camire who is the founder and principal at Sylvian labs. Did I get those right?
Joey: Yeah, Principal founding team. I don’t want to step on…
Amanda: You don’t want to step on any toes.
Amanda: All right, well good that we have the qualification. Welcome.
Kate: Thank you.
Amanda: So we’re going to talk a little bit about AI and marketing. We started this conversation last week and are going to go deeper. One of the big questions is, are we as marketers ready to start implementing AI? Especially because it’s kind general consensus that we’re still not getting the basics right. So where are we on the data cycle and how do you feel about starting to think through artificial intelligence in the world of marketing?Joey: Real quickly, can we clarify what a target consumer is?
Joey: That’s part of the basics, right? Yeah, I was joking. You look very serious. [Laughing]
Amanda: But I actually feel like somebody needs to hear that there is a market are out there that’s like, hmm, interesting question.
Kate: Who we’re talking to. It’s just such a base. That’s one of the many basic questions that we find.
Joey: People forget to ask.
Kate: We’ve both been consultants before. So, yeah, I mean when you go and you do an audit of a company, like there’s some really interesting things that they often don’t know. And what’s been funny for us, and I don’t know if this happened to you as well, but so here I am like now the founder of my own marketing software company and the shoemaker often has no shoes, right? And it’s the bane of my existence. And I’m like, okay, key messaging people, right?
Joey: Yeah, especially in this like high tech type of world. There is sort of two models of like starting with the person that you’re designing a product for or getting some sort of fundamental genius to sit in a room by themselves and develop something incredible and then say, okay, what do we do with it? And I’ve been on both sides of that and sometimes it can work having that fundamental genius side of it. But it is certainly scary, I think in this marketing conversation, especially with AI and you’re mentioning the fundamentals, but ultimately if you don’t have a good product that people want, you can apply AI, you can apply everything, but it’s not going to matter. You’re sort of gaming the system or polishing a turd.
Kate: Yes, I use that phrase a lot. It’s pretty funny. You can use marketing to succeed as a company even if your product isn’t better than another product. It’s this interesting thing because obviously if you have that jumpstart from their product being better and then it’s a two-for deal, but the spin that companies can use is really fascinating. And it’s something I think that people dismiss about the power of marketing and it’s, it’s not lying, right? It’s just, you know, twisting the words or focusing in on certain emotions or whatever it is. And like as a small company has just starting out like Lately is, I mean we had to think about that a lot. Like what messaging can we possibly use to rise above the noise in the fray? You know, for us, we think about personalized branding a lot. Like, you know, how can we consistently use that in our messaging without compromising our brand? And so for the way that we succeed in doing that is really being super emotional and human. And we look at AI as a way to enhance that and take the human work out of it.
Kate: Because people get freaked out about AI and they’re like, oh, it’s going to take over our jobs and whatever. But like I’m here to tell you that when marketing, it’ll never replace humans altogether because it just doesn’t work. They’re inherent components.
Amanda: Can we talk about product a little bit? Because I think one of the things that we have been thinking about for the past few years is the expanding role of the chief marketing officer and what actually is marketing. And I think product is one of those areas alongside technology that the lines have become very blurry and we don’t often, or always I should say see a chief marketing officer own the product function. Oftentimes there’s a lot of influence that has to happen in order to actually get to the point where you either are working hand in hand with an offering manager or you’re actually feeding the data. And we as marketers are potentially the closest to the clients outside of like direct sales to understanding what their needs and wants are. So I guess my question, long winded way of getting there is how do we think that companies are dealing with this challenge of needing the product to be closer to what people want? And especially when we’re in the world of personalization, it kind of needs to be in order to be competitive. Well marketing doesn’t necessarily have direct ownership over that function. And in your consulting experience and your roles, how have you helped marketers just sort of influence outcomes, maybe using data to start to push product forward?
Joey: At Sylvain labs, we do innovation and we do brand strategy. And I think when you have a, to sort of product centric perspective on what your product is and how you’re processing data, I’ve seen a lot of times in companies where they have incredible data and they’ve processed it and you wind up in end case where you know exactly how people are using it and you’ve segmented using sort of advanced algorithms and all of this processing. And the result is like we have 10 segments and these people use it on the weekend and these people use it on the weekdays, you know, like it doesn’t land on something.
Amanda: It’s a closed loop, sort of.
Joey: And the potential in some of those cases when you’re not as close to people is to forget about motivation and forget about sort of the richness of the internal environment of an end user and only think about them in sort of what buttons they’re hitting in the UI and not about what was that person thinking when they use the app in this particular case and it failed them and they put like a failure report into the system.
Amanda: It’s just shocking that we haven’t figured that out.
Amanda: We’ve known for years in B2B that marketing to a building no longer work. We understand. Yeah. Like just because it’s a company doesn’t mean that every person in every function is going to think the same way about your product within that building. And yet we can’t get to the granular level of how are they using this differently and everyone is an individual and how do we start to use that consumption data to start to think about lifetime value of customer and actually build meaning with them in a relationship with them. If you’re lucky enough to have a platform where you can even see those things. Unlike, you know CPG where you’re lucky to know if they bought it off the shelf.
Joey: Start putting a tracker on your yogurt.
Amanda: That’s so, so many levels of creepy. [Laughing]
Joey: Yeah, but there is probably someone is thinking about it right now somewhere. Yeah.
Amanda: It does seem shocking that with all the information that we do have, we still haven’t gotten to the point where we inherently recognize that that’s where we need to be.
Kate: Because Lately is a marketing software company and I used to own a marketing agency. It’s in our blood as a company to understand and know marketing and every single team member must know that and so have a deeper knowledge than like your average person. I do a lot of internal marketing for that reason. Everything from making sure we all receive our own newsletters or even our own sales emails to I, I have writing rules that I taught to my whole staff and they all must follow them and so they include things like don’t ever use the phrase checkout or I will hunt you down and kill you. [Laughing]
Joey: You have, you’ve created an algorithm for your team to process how they’re doing their writing.
Kate: Yes. Yeah, we have, I mean we’re small enough to be able to still do that, but we had to write a mission and a vision for our company right in front of the daily. Yeah, it’s important to do. And as I was doing it, I thought about like how we do that internally and then how we do that with our customers. And they’re pretty much the same. So we are really big on customer service. This is a marketing technique that we use that we can use to win being a small fish in a big seat, right? So we do that through a lot of accessibility, like something that we were touching on earlier today. How can we take my marketing team and my communications team and my customer service team and have them talk to customers the same way we talk about the brand. Right? So that’s something we think about all the times, how to get that human element out, how to be connecting with customers, had to be warts and all, but represent the brand. At the same time because we are an AI company. You do the human part and we do the hard part. That’s a consensus for us.
Kate: And I think it’s important to, as a company have have that mission statement for example or whatever, like have this understanding so that everybody can direct the marketing and and implement it. Leaning forward, whether it’s through their product or in communications, et cetera.
Joey: AI as it relates to marketing is raising the floor. It doesn’t totally feel like it’s currently raising the ceiling. And I don’t want to say tha across the board, but it feels like it’s making sure you’re not missing things. It’s sort of attempting to guarantee that you have the right message through A/B testing and and sort of effective systems that are allowing it to raise the floor. But I think some of what you’re talking about is sort of the spark of insight or the, the sort of like wonder of poetry that can still come out from people isn’t going to come out from AI. And even when we were talking about sort of the predictive nature of what some of the data can present you, it’s still saying like, hey you, might have missed this, but all of the data that we have on our sales currently says this person actually wants that as well. Right? And so it’s saying like, don’t miss this. It’s leaving the low hanging fruit pulled down so that you’re able to focus on other things in. But in its current incarnation, at least in sort of my understanding of the market. I don’t feel like it’s sort of elevating the ceiling.
Serena: Are there any brands or companies that you’ve worked with or you know of that have sort of moves past using AI for efficiency and automation and sort of taking it to that personalization level, that human component that you guys are talking about in a meaningful way?
Kate: I don’t think it exists in AI yet. I mean we’re not, we’re barely at automation like compared to a human, what’s the lifecycle of AI right now? We’re like baby land, right?
Joey: Reaching out for things. [Laughing] I think there are some like very micro examples. Right? And some of the technology companies there are like these micro moments of delight that feel like sort of a learned behavior. I’m thinking within the Google hardware ecosystem for personal things of like recognizing sort of photos and putting the right photos in your Google home hub at the right time or arguably you can say that the Spotify discover weekly products that they have is somewhat of like an opportunity to be predictive and provide delight that they don’t know that you like the song that they have some assumptions based on the way that they’re processing user data to say that we think you would like this and if you’re hitting one out of three of the songs that you’re listening, that’s a pretty good batting average. Right.
Kate: I was thinking about that too because I was a rock and roll DJ for a bunch of years at XM…
Joey: And I was a wedding Dj with my dad and that was a lot less cool.
Kate: I bet it was more fun actually. But my job as the programmer was to get you to trust me so that the next song I play, you’re going to like it no matter what. Of course, it was my job to predict what you would like as a human. And so I was just thinking about Spotify and how well they’re doing at that because I don’t know if it’s fair to call it machine learning maybe, but there are humans back there still that are touching it. And like people like the human touch, they love it, they want it that way. But then when they’re doing the work for themselves, they don’t want to do any work.
Kate: So one of the things that we do is we take a blog or a newsletter or podcast or a video and we instantly turn it into dozens and dozens of pre hashtag and pre short links, social media posts. Awesome. It is awesome, right? But it’s amazing to me how many people will just then send those posts out. They’re pretty good, but you’ve got to put your eyeball on there. Consistently marketers, they just don’t want to write.
Kate: You know, it’s the most basic thing that you assume all marketing people would want to do.
Joey: Yes 100%. In the best case studies that you find out of marketers right now using AI to make some major breakthrough, right? Like surge pricing. Amazon does it, Uber and Lyft. That concept was shown to be sort of a viable concept, but the idea itself was produced by a person, right? Like AI is not at the place right now where it’s saying like, well, based on my understanding of supply and demand economics, you should be changing your price model. Like what you choose to do with the understanding that the system is providing you is still going to land on someone’s lap. So your ability to be creative, your ability to write, your ability to wrangle concept and insight. What do you do with the information that you’re being provided from a system that is finding things that you might not otherwise be able to find.
Amanda: Yeah. Kate, I think you bring up an interesting point about kind of where marketers are today and I think that there have been so many schools of marketing that have arisen throughout the years and we’ve had the brand marketer, which oftentimes is very different than the sort of innovation-focused marketer, which is then different than this analytics human that’s come into the scene in full force scale over the last decade. Right.
Kate: They scare me. [Laughing]
Amanda: And so for me, there’s a convergence now where you kind of have to be all those things at once, which is really challenging if you’re a CMO. But I think it’s also challenging if you were a middle manager or brand new into the field and can, I think it’s an interesting question as to whether or not we’ve overindexed on, we have to just spam messages out. We have to have distribution at scale, we have to have content at scale. Not that we’re not into AI and we don’t think it’s important, but I think with machine comes man and that creative and the beautiful part of marketing is still so critically important. To your point in order for us to be effective, you can’t lose sight of how important the human element really is.
Kate: I don’t think the school of CMOs has been around the poetry that you talked about earlier. Right. It’s been kind of lost, which is troubling because since marketing was invented, nothing has changed. Right. What matters is Chutzpah.
Kate: Right. Writing and then I believe organization. And for some reason like that old school of thought, it’s all, sorry I’m a data hater, but it’s gone so far to the data side. I get angry about it a little bit. [Laughing]
Joey: Well I think like for me a big part of this, is where’s the data coming from and who’s data is it and how are you mining it? You know, data’s the new oil. I think that was first coined by the World Bank. It’s true. And thinking about conversations as it relates to Facebook, like specifically their Pixel program. You run into these conversations where people are feeling very uncomfortable at the reactions and thinking that Facebook or Instagram or whatever is doing something that is sort of pass through the uncanny valley of now it’s creepy.
Joey: And they’re doing something that’s a little bit more insidious I think in terms of like a lot of websites that you go to our cooking you and then they’re connecting that to what your friends are doing and location and they’re sort of mining incredible amounts of data. And for me I about this, you know there was the conversation about Target a few years ago where a dad got really upset because they knew his daughter was pregnant before he did based on her purchasing behavior. And that was Target owned data, right? It was saying like you made sales here. We looked at the sales and understood that you were probably pregnant and so we gave you some recommendations or like a kit that we sent in the mail. Great. We weren’t following you around everywhere you went and making a map and then following a map of all of your friends, tying those together and showing up. And I think that’s where it starts to get uncomfortable. If there has to be a point where you say, that’s stealing, because if Facebook did the same thing outside of a digital environment, you would say that’s not okay.
Amanda: Well, I think there is a huge onus on tech companies to make responsible decisions, whether that’s how they’re handling data or that’s how they’re using that data and approaching you with marketing. And just because you have it does not mean that you should use it. And there should be somebody, I think to Kate’s point, sitting behind the steering wheel saying maybe we shouldn’t be messaging somebody based on their pregnancy when you know that might not be something that they know about yet or that’s public.
Amanda: Making jokes about it. A la, our friend Zuckerberg about the future being private…That’s not responsible either. And it’s not funny and it’s not funny to people. And yes, we’re putting our data out there and yes we’re getting something in return for it, but at the same time as CEOs, I mean I’m saying this as though I am one, but those…[Laughing]
Joey: My fellow CEOs…
Amanda: There has to be some sort of consensus on what’s okay and what’s not. Otherwise the government is going to start making the rules.
Joey: Decentralization is a big part of this too, so like Scripts right now, the health institute, is doing a ton of work as it relates to AI and deep learning around personal health data and the model that they’re building is you own the data and then you get to decide what you do with it so that there’s a level of agency involved in the decision making process of what are you going to do with this data. There’s increasing understanding for end users around the data value exchange and people are putting, can now conceptually put prices on their own data and saying like if I walked up to you and said, how much would I have to pay you to get your social security number right now? You would come up with some number, but you would be able to conceptually put a number around it. And that same thing holds true when you ask them, “How much would I have to pay you to get your text messaging data?” But people are understanding that that data has value. I mean that’s why Facebook has lost 15 million users in the US is because people are creeped out.
Amanda: Yeah. I Mean, they came up with a number, right as to what your data is worth to them and it was not very high. It was a shockingly low number. All I know is that they can’t pay me in Bitcoin. [Laughing]
Kate: As we move forward, there’s an onus on the user to have the awareness into companies or work with companies that have that same philosophy. Because I think that you can’t just throw up your hands and say, I’m totally innocent all of the time now. There’s really evil things happening, no doubt about it. But I think that’s important as as we figure out how to solve this problem as a community of whatever people who are willing to put their lives on public display.
Kate: You know, how can we cooperate with these companies because I think that’s they got us, right.
Kate: So we’re sucked in and there’s no way that we’re all not using these things anymore. Right?
Joey: Yeah. I mean I don’t use Amazon, I don’t use Facebook anymore. I don’t use Amazon. I think like there is a burden of understanding to making those decisions, but when you understand that these behaviors seem predatory as it relates to AI, then you can make a decision, do I want to stay or go? And I think the problem with this overall AI marketing discussion is a lot of the practices aren’t predatory, right? Like being able to build the user segmentation based on your sales data is not a predatory practice…
Amanda: Inherently predatory.
Joey: Yeah…automatically predatory. It’s saying like we could make our sales system or pipeline more efficient and so how do we do it? But I think a lot of why people are scared in this conversation is because there is a whole camp of the way that AI is being used within marketing that feels fundamentally predatory.
Serena: But when there are brands like the Target example, they weren’t setting out to be predatory. They were sort of just like, this is the data we have and we’re trying to give you recommendations to make your life easier…
Kate: And to make more money.
Joey: Yeah. Yes, absolutely.
Amanda: Which is not inherently evil. Making money, totally okay. Go for it.
Serena: So I’m just wondering, are there ways for companies like can creepiness be quantified? Is their tooling out there that companies will be able to use to test whether they’re being too creepy or you know, read the air a little bit better so that they’re not scaring customers away.
Kate: It is annoying to me to have commercials in any feed. Right. It’s annoying, but more of becoming used to it, I’ve gotten accustomed to it. Right. But every once in a while like it was up desk I think. And I was like, Huh. And we looked at it and my husband bought one and so like I didn’t want that ad but it turns out that I benefited from the ad.
Joey: Those situations like the Facebook Pixel program and whatever. Right? Like I had people on our team researching a chair. They needed to incorporate a chair into a particular project that they were working on and they were doing tons of research around chairs.
Amanda: They were only getting chair advertisements from now on.
Joey: And so then I had stopped using Instagram, how to daughter. So obviously now I’m back on Instagram, I got an ad for chairs and I’m like, I haven’t searched anything for chairs. I have. And I think that’s when you’re starting to get into like there was this chair conversation happening in my life and when you’re making these leaps and connections that feel like, why do you know this about my life? Like should you know this about my life. And I guess they know that those two people at work that I’m connected to on Instagram, know me, whatever. Like it’s sort of the similar type of thing of like that uncanny valley is like you don’t know when you’re in it until you’re in it.
Joey: But it’s problematic.
Kate: And the Facebook…You know how like inside you can, it can tell you what it is, the things that you’ve liked and so it has a whole chart and you can delete them all and it actually audit auto-populates them right back up and it’s based on stuff that you’ve liked. So say for example, I like somebody who was celebrating Easter and now it says that like I’m into Catholicism, which I’m actually not.
Amanda: It’s highly possible to confuse the algorithm. My issue currently is that I do not have children, but everyone around me is having children, and Zuckerberg and his cronies are utterly convinced that I am pregnant. I get so many baby things on every single one of my platforms at this point. And I mean I’ve purchased things, obviously you go to 10 baby showers a year, and that’s where you are. But you know, just totally thrown them off. And, the thing that is challenging with that is let’s say I actually was going through a fertility struggle or you know, there’s something personal in your life that all of a sudden they misread the algorithm and you’re in it and it’s, you know, emotionally triggering. So I think there must be, we’re not there yet, but at some point to Serena’s point, there’s gotta be a way to read the room more accurately because we’re just, we’re going into the deep end.
Kate: When you have human eyes on the data, like you use the data to do the hard part and then you know, a human has to like make the final decision. And I believe if there was more of that, then we wouldn’t be having some of these discussions.
Kate: Right. They just, they got a little too carried away.
Joey: I think the flip side of this is a business model shift and they’re stirrings in that direction. Whether or not that ultimately happens, right? Like the efficacy of popup ads have always been questionable…
Kate: And annoying. Yeah. Banner ads, like, you know, showing up in your feed. The flip side of…
Amanda: The guy who created pop-up ads has publicly apologized.
Joey: “I didn’t mean it, I’m sorry.” [Laughing] I have a Hulu account. I pay the extra $3 a month or $2 a month, whatever it is to not have ads and I feel happier as a result of it. I think fundamentally we’re on that messaging side of this conversation. We’re in this sort of attention economy like brinksmanship and that’s why we need AI in these conversations to like eek out, you know, these minuscule fractions of efficiency in a system where you’re already investing a lot of money. I think the conversation on the flip side of Ai within marketing, around sales, pipeline segmentation, these things, that’s actually sort of a more functional utility where you’re able to improve your product, right? Like where you’re able to say, I can now understand what users want better and I can serve these different segments based on directionally knowing what they are going to talk to them and informing a way to innovate the product. I think in the attention economy at some point, like…there’s only so many hours in the day, right?
Kate: If we can have the conversations and use marketing to do that, right? That’s where it is really it’s at its best. Is getting you to trust me to give me information willingly and for me to understand like how to help you before how to sell you. Right? Don’t you love that when people actually help you? And then you’re like, that was so awesome. Here’s a tip or I am going to buy this now because you were just nice to me. And so I think marketing is more art than science. It always will be. And it doesn’t matter how much measurement you do, you’re never going to get to the end all be all of all the data or, and you’re not even going to have all the time. That’s just part of the deal.
Joey: Digital systems move fast inherently, right? Like a computer processes things faster than we do. The question is whether that’s better or whatever, but like even agile, agile is a great system for questions that you can approach with an agile approach, but you are removing the ability for like slow thinking, right? Like the idea that you can as a human computer that you develop insights and intuition over a longer period that can…you can’t quite figure out how you got there but you know it to be an inherently true and slow thinking is sort of at odds with the current environment.
Serena: I kind of want to go back to something before we wrap and it’s the idea of the unintended consequences of hyper-personalization. So at good example is Netflix images. They have thumbnails for different audiences. So like a show like Riverdale could be seen as like a comedy and it could also be seen as a thriller that raises uncomfortable questions around stereotyping and who’s getting served, what kind of advertising when AI comes into the play and they’re making algorithms about this stuff. So how can marketers balance hyper personalization without crossing the line into things like stereotyping where you are essentially losing consumer trust?
Joey: There’s a couple of components to this, right? Like the thing that we talked about a little bit is it like if you’re demonstrating that you know something about me that I don’t think you should know that I think crosses a line. The other part of what you’re talking about is the social mores component of the discussion, right? Like the current cultural conversation has a very particular perspective on race and where the country is trying to move in the conversation on race. And so building thumbnails that allow for racial stereotyping within the system is sort of the issue. The algorithm didn’t build the thumbnails. The algorithm is doing A/B testing. People are sort of the pulse check. They can also be sort of the tone deaf ones in the way that the algorithm can be tone deaf.
Serena: So how can we, you know, when we’re building strategies or AI models, how can we keep our own biases out of out of it?
Kate: By nature as humans we stereotype. That’s how we survive.
Joey: Put things into categories.
Kate: That’s what we do. It’s all living beings do this so they can like not get killed by the bear and that’s part of the deal. It’s how you use that stereotype, right? That’s the problem.
Joey: Whoever is designing the product needs to have the reflective moment and a lot of the conversations that have been had around AI in particular are that they’re not placing people on the development side that are thinking about people. Right? That whether it’s psychologists or ethicists or sociologists or anthropologists…
Amanda: Or even just marketers.
Joey: People who are on the soft side of the conversation there. I think there’s a bias. Speaking of bias, towards technological expertise and capability chasing with regards to AI that’s not considering the fact that you’re building a system that is still going to be talking to people. And so I think there is a conversation that needs to be had about checking your bias and I think that if you’re not addressing them and you’re not being like reflective enough to say I have biases and I’m designing a system that’s going to be used for people and inevitably you’re going to have blind spots. And I think some of that is diversity on the teams that are building anything and representation. I think representation is also important in the same way that we’re talking about of expertise representation in addition to sort of cultural demographic background like all of that. I think people step in it. There’s a new story where someone is stepping in it every single day and a lot of times the solution to not walking in it was just having a team that was more representative.
Amanda: CIOs, engineers, all you people, bring your marketer into the conversation with you.
Joey: No bias in this representation. [Laughing]
Amanda: No, definitely not. We are not biased point of view. Thank you guys so much for joining us.
Joey: Thanks for having me.
Kate: It was awesome meeting you.
Joey: Yeah, great.
Amanda: Thanks for listening and we will have more content out to you next Friday.
Serena: We need you guys to like subscribe, review. Also, one of our guests, Joey, he has a podcast called Critical Nonsense, which you can find.
Amanda: Yeah, give it a listen. all.
Jason: See you next Friday.