Exploring the rapid adoption of Artificial Intelligence in marketing, we revisit conversations with recent guests, including Katie King, Renee Hartmann, Nick Wolny, Dave Kaye, Paul Sloane, Rohit Bhargava, and Martin Oxley. Conversations examine the ways in which AI is being used in sales and marketing, retail, consumer research, translation, and content creation with relevant examples and case studies. Links to the books mentioned in this episode are provided in the transcript.
Episode Transcript
Adrian Tennant: Coming up in this episode of IN CLEAR FOCUS.
Katie King: It’s about AI helping develop better products, as well as insights into what customers really, really want.
Renee Hartmann: There is a company that was using AI to optimize pricing and grocery stores based on the expiration date.
Nick Wolny: I think AI could do away with the need for human writers, but I don’t know that it could do away with the need for human editors.
Rohit Bhargava: We’re not using AI to replace the writing. We’re using it to make the writing better, and I think that’s the opportunity when it’s used well.
Adrian Tennant: You’re listening to IN CLEAR FOCUS: fresh perspectives on the business of advertising. Produced weekly by Bigeye: a strategy-led, full-service creative agency, growing brands for clients globally. Hello. I’m your host, Adrian Tennant, Chief Strategy Officer. Thank you for joining us. Today, we’re going to look at the impact of artificial intelligence-based tools on marketing and creativity. ChatGPT, the popular chatbot from OpenAI, was estimated to have received a hundred million monthly active users, just two months after its launch in late November last year, making it the fastest-growing consumer application in history. ChatGPT is part of a rapidly expanding marketplace for AI-assisted productivity tools and plugins. The excitement and momentum around all things AI helped chip maker, Nvidia, attain a trillion-dollar market capitalization. Mark Read, CEO of agency holding company WPP, recently announced that it will be building on NVIDIA’s Omniverse platform. It aims to produce content using generative AI tools from Adobe and Getty Images, trained on licensed data using NVIDIA’s Picasso engine. In January, I spoke with Katie King, CEO of the consulting firm, AI in Business, and the author of the Bigeye Book Club selection, AI Strategy for Sales and Marketing. I asked Katie how AI is currently being used to support marketing communications and sales functions.
Katie King: So you’ve got many marketers using AI-powered tools so that they can craft their social media messages, their email marketing campaigns, their web copy. So on the sales side, it’s helping organizations to come up with a pitch to a potential customer to keep the pipeline of leads warm with prospects. There are tools like Concured and Phrasee, and it’s saying to people, “How do I tailor my message to a specific audience so that I can offer the best value proposition every time?” So contrary to what people think of big, shiny robot coming taking our jobs, this is mass personalization. So I like to talk about augmented intelligence. That’s what AI can give us, whether we’re in Comms, PR, Marketing, Sales, CX. It’s a series of tools that we need to invest in that can give us big data insights on all different aspects of what we do, and that might be analysis. It might be, like I say, lead generation or lead scoring. It could be Brandwatch and it could actually be automating some of the more monotonous tasks that we do of creating reports and so on. But one of the keys is identifying trends and sentiment analysis and crunching data at volumes and speeds that our, albeit incredible human brains can do, but maybe across multiple languages all over the world, you know, and so on. That’s really the benefit at the moment of AI in the sectors that you mentioned.
Adrian Tennant: We often discuss shopper marketing on this podcast, so I asked Katie about the adoption of AI in the retail sector.
Katie King: Retail’s such an interesting place right now. I mean, the pandemic changed a lot of our habits. But, we haven’t given up on our old ways. So we’ve got some retailers struggling with, are we going all in on digital or are we holding onto some bricks and mortar? And so, what we’re doing is we’re seeing AI applied in a hybrid manner. So physically, you know, it might be delivering digital experiences to customers. They’ve come to expect that, and then it might be bringing something into the store, you know, for more of an omnichannel experience. So maybe the AI is part of the website for personalized product recommendations, and then maybe in the store it could be a sensor. So you’ve got artificial intelligence, but then you’ve also got the Internet of things. So these sensors could be used to track footfall, assessing which products customers are gravitating towards, so that we can offer them push messages and offers, and so on. And then, you’ve got smart mirrors and other kinds of areas. Even wastage, it might be a food retailer and the AI might be really predicting with great accuracy how many people are going to dine in that store or purchase that amount of perishable goods. So, you know, really, really useful information that is making us as retailers greener, and more able to offer our customers what they require and food producers and CPG brands aren’t any different. So, one that springs to mind is Nestle, and they’re using AI across their business from marketing to manufacturing to product development. So, you know, for organizations like that, for retailers like those, it’s about AI helping develop better products, safer practices, as well as insights into what customers really, really want. And I think in the long run, what we’re looking at here is a better, more efficient supply chain, less waste, and a better product offering.
Adrian Tennant: Our featured Bigeye Book Club selection for March was Next Generation Retail: How To Use New Technology To Innovate For The Future, co-authored by Renee Hartman. I asked Renee for her take on AI.
Renee Hartmann: There’s so many different parts of artificial intelligence and I think what’s getting a lot of press right now obviously is things like ChatGPT, and like these types of virtual intelligence, and artificial intelligence, and how that’s getting involved. But I think there’s so many different things we’ve seen, you know, we talk about the core framework which is everything from communication to optimizing pricing, to rationalizing inventory, and then creating experiential retail. And I think that’s something, you know, that we’re seeing quite a lot. Whether it’s things like chatbots and every time you go online being able to get that quick customer service and the way that consumers are engaging with brands and virtual assistance personalization that’s coming through. I was actually just at a euro shop and I saw there is a company that was using AI to optimize pricing and grocery stores based on the expiration date. So I think you’re even seeing things like, how do you use dynamic pricing? How do you take data to make better decisions and optimize things like supply chain and inventory?So there’s so many different ways. I think there’s the kind of fun and creative ones that get the spotlight, but actually when you get back into supply chain and some of the real data intensive ways, it’s how do you take immense amounts of data and then how do you process it intelligently in ways that maybe humans couldn’t do before. I think that’s where a lot of the power comes from, really, disrupting the retail environment.
Adrian Tennant: Renee’s book includes several case studies of how well-known retailers are applying artificial intelligence and machine learning to their operations. I asked Renee if there were one or two that really stood out.
Renee Hartmann: There’s so many great ones. I think, you know, one of the ones that resonated with me- I’ve just been renovating a house and just moved and I think a lot of people during the pandemic did as well. One of the ones we talked about was Wayfair having a visual search where you could submit photos of items that you like and then find similar items on Wayfair. So when you think about retail, so much of it is the seeing and the exploring and sometimes it is hard as a shopper, I think, to know exactly what you’re looking for. It’s not necessarily something you’re searching for. And that’s something where browsing online sometimes can be a little bit different than say, like, when you’re walking around a retail store and having that sense of discovery. So I thought that was a really fun way to take AI and look at it from a visual standpoint, almost using different senses that you would use from online shopping. So I thought that was one just personally resonates to me because it’s something I’ve been doing a lot of is walking around furniture stores and vintage stores and trying to find fun things. You know, and then I think obviously one that everybody has used a lot is those chatbots and, the ability to even when I’m just online shopping and things like that, whether we talked about Lowe’s and Kroger’s and Nike. But, being able to create that really quick response and being able to answer people’s questions and really streamlining the customer service experience for consumers is ways that I think are really making everyday shopping a lot better for people.
Adrian Tennant: Making his third appearance on the podcast, writer and entrepreneur Nick Wolny joined me in January to discuss the creator economy. I asked Nick about his impressions of ChatGPT as a writer, and what his first prompt was.
Nick Wolny: Of course the first prompt I entered was: “Write me an article about how to write better.” It’s like just to completely see ‘Okay, what’s happening here?’ But yeah, I think it’s really exciting. Here’s the analogy that I’m working with, just when I’m talking to people about it, is that about 10 years ago you had a tool come out called Canva. Which a lot of people are really familiar with, right? And so Canva, which has over 50 million users now democratized graphic design for people, right? It was just one of those tools. It’s kinda like Instagram suddenly made everyone a good enough photographer. It is a similar thing. Canva made everyone suddenly a good enough designer. And, from that though, Canva did not replace good designers. If anything, it increased the appetite for really good design because people got in there and they were able to work for a template, but you’re like, “Oh, you know what, this, I still suck at this” Right? And so I think that’s what’s gonna happen with ChatGPT as well, is that the people who were writing bottom of the barrel stuff, they’re gonna get automated out, for sure. But, I think also what will happen is people will begin relying on this automation and they’ll realize that the writing is just still not that good. Another point I like to make to people about ChatGPT, it can’t crawl the Internet. It’s not a search engine. So anything it writes for you, it will not be able to pull in any context, anything like that. So in terms of replacing journalism, replacing editorial, I don’t think it’s anywhere close to that. It might get to that direction soon. But, I think the other thing too is, as you just mentioned, journalism has already been experimenting with AI for quite a while. Most notoriously, this is so Jeff Bezos, but Jeff Bezos, when he purchased the Washington Post. One of the things he did was, let’s create an AI that can take care of all of the really simple local reporting that’s just kind of mindless. And so, they have an AI called Helio Graft that was proprietary that they built, and Helio Graph will do things like, it will take the scores of the local high school football game and it will just put them into a recap article. Think about that sports recap writing. There’s no actual, there was no interview being done with the lineman who made the tackle. None of that’s being done. It’s just a recap of what happened based on the numbers. So all of that gets produced automatically. And so as a result, the Washington Post is able to grab you, it’s interesting. It’s almost like Amazon, right? So that’s why I just think it’s so funny that it’s Jeff Bezos who implemented this, right? It’s just taking the Amazon playbook and basically applying it to the Washington Post. I really think that’s what happened there for a while. The Washington Post jumped over the New York Times in terms of traffic, which is pretty incredible. And it was because of this sort of long tail strategy. We’re gonna talk about everything, but a lot of these just simple recaps and stuff is gonna be totally automated out, just produced instantly. So it’s scary, but I think for many people it’s the first time they’ve interacted with an AI writing tool. And so I think everyone should get on it, everyone should tinker around with it. I think it has real implications for things that are very black and white, like seen examples checking code for errors. Adrian, I was a computer science minor for six weeks and I literally dropped out of the minor because I could not find the extra comma in one of the lines of code. And this was back, you know how it is. This was back when we had to etch it into a stone with a chisel. But, you know what I mean? It’s like I could definitely see helpful implications there, I think that’s an incredible use of AI. I think it’s gonna change the conversation about written content because so many people will just be interacting with an AI who have never interacted with one before, and they’re just gonna get curious and excited about it. So yeah.
Adrian Tennant: I asked Nick if he thought tools like ChatGPT could ever replace the need for human authors and whether writers should fear these AI-driven technologies.
Nick Wolny: I think it’s something to definitely watch and to keep an eye on. I’m not, not paying attention to it, I’ll say that. I’d love to not pay attention to it cause it’s everywhere right now. But ,I’m monitoring what’s happening. I think AI could do away with the need for human writers, but I don’t know that it could do away with the need for human editors. Right now. And that’s what I think is the distinction there, is that, when I receive an article draft from a journalist, or from a freelance writer, I go through that and I edit it based on obvious things like grammar syntax or context or whatever. But then also based on some of our internal objectives, and that’s what many other people do who own a business, who run a website, are gonna and do something like that. And so I think if you can get good at taking what ChatGPT spits out at you and cleaning it up and then getting online, then I think it’s quite a force to be reckoned with and I’m curious to experiment with that. I’m gonna experiment with that personally. If I had ChatGPT write the draft and then I brought my editor’s eye to it, is it quicker? And also the ethics of that. You know what I mean? If ChatGPT wrote it, but I edited 90% of it, who wrote this article? It’s interesting to sort of think about from that perspective as well. I just also think that people are starting to look for other more dynamic ways of getting the information that they want to get and be interested in. So yeah, if someone is just writing, they never do any editing, they never think about what they’re writing, then I think AI is gonna automate out those jobs or stuff that’s very dry and doesn’t need context, like policies and procedures that just have to be very highly accurate. Like I could see AI automating a lot of that out, maybe like instruction manuals and stuff like that. But, I think it’ll be a while before the intelligence gets to a level that it can automate out an editor who’s gonna be the person giving context or connecting it to sales objectives or, or whatever you’re trying to do with that content that you’re taking the time to produce and publish.
Adrian Tennant: In March, I spoke with Rohit Bhargava, co-author of The Future Normal, a book featuring ideas and consumer trends that could shape the next decade. One section of the book poses the question, “What if artificial intelligence could make humans more creative?” I asked Rohit how AI can change how we approach creative tasks.
Rohit Bhargava: Well, I think the first thing we have to say about AI is that it could do these things if we use it in a certain way. And, and that’s one of the fundamental things that I think a lot of people and a lot of stories sometimes miss about the power of AI. That it really is driven by how we choose to use it. And as we started using it, which, you know, we’ll definitely get into, one of the things that was quickly apparent is that when you put garbage into it, you get garbage out of it. And when you become good at putting information into it, you actually get something pretty good out of it. And what that meant to me, pretty apparently, is that it’s going to become a skillset to learn how to use AI, for creative tasks or for mundane tasks. And, and I have examples of both of those things that I could share with you. Right? So it’s not only, look at what AI was able to do in terms of generating a painting or generating art or generating images or generating faces of people who don’t exist based on extrapolating facial features from pictures of people who do exist. It’s also, how can it make these tasks that we all need to do that sometimes we maybe don’t want to do, like writing a letter to get out of a parking ticket… How does it make those sorts of things easier for any one of us to do as well? I would consider those to be low stakes moments versus kind of high stakes or something that you put out there that has your name on it, right? Like ghost writing a blog post, for example, that has your name on it that just uses AI, and when you put it out there people are like, it doesn’t really make sense.
Adrian Tennant: I asked Rohit how, for The Future Normal, he used AI tools in the design of the book.
Rohit Bhargava: Yeah. Not just the design, but the writing too. What we didn’t use it for was to write the book or to write any parts of the book. But what was interesting about it is we used it in a couple of use cases. So if you do get the physical copy of the book, you’ll see that we have 30 trends in the book, and each one of them has an icon attached to it. And so as we were sourcing icons and finding them and deciding what icons to use, there were some chapters where we kind of hit this mental roadblock. “What should the icon be?” Right? Brainstorming roadblock, we’ve all had those. And AI was really interesting to use as an idea generation tool in that case to say, “Here’s the text of the chapter, can you suggest what some icons for this chapter might be?” And it would write some of the suggestions and we would go in and say, “Oh, that suggestion’s actually kind of interesting.” And then we’d start going and looking for it. And in some cases, for some icons, what AI had suggested inspired what the icon actually was. So AI didn’t design the icon, but it helped us to find it. That was one example. Another example that’s more on the writing side was we’d written a chapter and we put the chapter into ChatGPT, and we asked it to write a negative one star review of that chapter and identify why the chapter wasn’t good. And what it came up with in terms of spotting gaps in our arguments was actually useful for us editorially, to be able to say, “Oh, this point that we were trying to make wasn’t entirely clear. We need to go back and revise the writing.” So in this case, we used it as a critique of the writing, but then we did the writing ourselves and we used it as a layer to say, “What would AI spot as a gap in our argument that we now need to go and fix?” So that was another example where it was quite interesting what it came up with. We’re not using AI to do the creative or to replace the writing, we’re using it to make the writing better, and I think that’s the opportunity when it’s used well.
Adrian Tennant: Let’s take a short break. We’ll be right back after this message.
Adrian Tennant: Each month, in partnership with our friends at Kogan Page, The Bigeye Book Club features interviews with authors who are experts in consumer research, retail, and branding. Our featured book for June is The Solutionists: How Businesses Can Fix the Future by Solitaire Townsend. Featuring compelling stories from top entrepreneurs and businesses, the book showcases how Solutionists are addressing our planet’s greatest crisis through sustainable innovation, highlighting transformative examples, including plant-based foods, net-zero technologies, and circular platforms. IN CLEAR FOCUS listeners can save 25 percent on a print or electronic version of The Solutionists by using the exclusive promo code BIGEYE25. This code is valid for all Kogan Page products and pre-orders and applies to their free paperback and e-book bundle offer. Shipping is always free to the US and UK when you order direct from Kogan Page, and it helps the authors too. So, to order your copy of The Solutionists, go to KoganPage.com.
Adrian Tennant: Welcome back. You’re listening to highlights from conversations with IN CLEAR FOCUS guests about artificial intelligence and its impact on marketing and advertising practice. In addition to creative applications, artificial intelligence-based tools are also emerging in the consumer research space. In March, I spoke with Dave Kaye, an expert in smartphone-based ethnography and the co-founder of the qualitative research platform, Field Notes. I asked Dave for his thoughts on the role of AI in the design, collection, and delivery of consumer insights.
Dave Kaye: Yeah, it’s a question which is on everyone’s lips at the moment, I suppose, but it’s definitely making an impact in online smartphones qualitative. I can answer this question by basically saying what impact it’s already had for us as a platform. So, you know, we are still very early days of all of this and OpenAI’s ChatGPT has already impacted the way we do things. So, at the end of this month, we’re actually changing our transcription service completely and moving it to an AI driven transcription service, which is called Whisper. And we’re very excited going into that and working with them. And basically the quality of the output that we’ve seen, and we’ve already got it on our staging server, is phenomenal. It makes a massive difference. You’re looking at it. And you are, sadly, questioning whether transcription agencies are gonna not have a hard time of it in the near future. Human transcription has always been a massive role for it in research, but as this technology’s improved, you’ve got away with not using human transcription on a few. What we’re seeing now is that the level of transcription is becoming phenomenal. That’s also true of translation. So, you know, whenever I talk and give tips on how to run an international smartphone qualitative project, I always say, “Don’t get burned by translation because you’re not sure how much you’re gonna have, how much it’s gonna cost. It spirals outta control.” That’s where the hole is when it comes to managing it. And this, with the improvement in transcription, is allowing for, I think, really cost effective translation to come on the horizon. And I don’t think that’s gonna be as good. It’s a harder thing to essentially deliver, but it is still giving you a massive opportunity. I mean, it’ll be massive, massive differences in transcription and translation. We’re already seeing it as so in our business. And then finally, the other thing that’s already happening within our business is, once you’ve got all of that AI driven transcription in place, you can then start to begin to ask the tools to provide you with summaries of the actual content. So you are looking at, say 10, 15 minutes of video from a participant, which as a researcher would take you 10, 15 minutes to go through and then take notes, understand it. Take time on it. And now the click of a button, you can have a summary there of, 200 words or whatever, bringing to life in written text, exactly what happens in that video. And the quality of that, people say, you know, “How good is it? How effective is it?” I think the best way of thinking about is, it’s like having a junior, an extra junior team member, working with you for somebody who needs support, somebody who needs to, have a little bit of supervision in terms of what the output looks like, but fundamentally is doing a really good job getting through it. And that, if you think of the man hours when it comes to like going through all the content, it’s gonna save a huge amount of time. So, it’s gonna go way beyond that, I think. But just in the last three months, those are the developments we’ve seen on our own platform and I think it’s a really exciting time. I think people are gonna work differently. New jobs are gonna be created when it comes to analyzing the content, understanding what best to do with the AI. So I think it will evolve and it will change, we’ve already seen that. I think just technology has changed the role of research, but it’s made it much more accessible to a lot of people.
Adrian Tennant: AI in consumer research was a theme I also discussed with Martin Oxley, Managing Director of buzzback Europe. Here’s a snippet from our conversation from just a couple of weeks ago.
Martin Oxley: Well, we’re immersed in this with chatGPT and interestingly, the very much it seems a second to ChatGPT, Bard. Who’d have thought that Google would be second in anything related to technology? But, we seem to be talking about ChatGPT, rather than Bard. I must admit when I first came across it and I was first exposed to it, I struggled to get out of my seat. Not through tiredness, but through fear and trepidation and, “Oh, my word, what is this going to do to the world that I’ve lived in?” But, since I’ve settled a little bit more about it, I realized that it can be a huge asset and a huge opportunity for us in the world of asking questions to convert asking questions into asking good prompts. And I’ve even seen now there are jobs out there for prompt writers, which in market research terms is question writers. We’re really good, and should be really good, at asking questions. Instead of asking consumers, we’re asking the digital masters that are ChatGPT, and asking them for their views and summarized views. So, we should be really good at it. We should be really good at iterating our questions. You ask the prompt and then you keep prompting until you get a fine tuned perspective that then you can go on to test with consumers. But the other reason I’m very excited, what’s completely missing from the whole AI conversation, is the lack of emotion and the lack of ambition. The machine itself doesn’t have emotions, it simply doesn’t care. It doesn’t have any ambition, other than what you tell it to do. And, if I’ve learned anything in the increasing number of decades I’ve been in research, is if you don’t understand emotions, and you don’t understand motivations, and you don’t understand ambition, you rarely understand anything. And this is for me, a really key point, which is there is a huge opportunity for us to use this as a tool. Just as the people in the pre-industrial revolution in the UK used to smash up the threshing machines because they thought it would take their work, when in fact, the machines generated more work. Yet to see that, but I’m quietly confident that once we get our head around it will use this as a real help for us to do our agile research. So don’t fear it, understand it. As someone said on LinkedIn the other day, I’m sure you’ve seen this quote, which is, “You shouldn’t fear AI. You should fear someone who knows how to use AI.”
Adrian Tennant: In February, I spoke with Paul Sloane, the author of the Bigeye Book Club selection, Lateral Thinking For Every Day. I asked Paul if he thought AI could ever rival human ingenuity.
Paul Sloane: That’s a very interesting question, and I think the answer is yes, it will. We’re getting there slowly, and at the moment, what I say to people is the one thing that computers can’t do is ask intelligent questions. They can give answers, but your job as a creative marketing professional is to ask really smart questions, and searching questions, and questions that other people aren’t asking, and that will help you come up with creative ideas. But, ultimately, I think AI will come to that level where it can ask really smart questions based on masses of experience. And what you’ll do is you’ll give it a problem, global warming or inflation or something else and say, “What ideas have you got?” And it can model all sorts of different things in great detail in a way that humans can’t do. So if we raised interest rates and we raised taxes, what would happen? So it can model all of these things. And similarly, in a marketing sense, it will eventually be smart enough to create models of consumer behavior. Which says if we raise the price and double the pack size or whatever, what would be the effect on our sales? So, I think artificial intelligence is gonna be an amazing addition.
Adrian Tennant: As you’ve heard, artificial intelligence-based tools have been top-of-mind for many of our guests so far this year. For a final perspective, we’ll return to my conversation with Katie King. After discussing the rapid adoption of tools like ChatGPT and DALL-E, I asked Katie if marketers and creatives working in advertising agencies should fear AI.
Katie King: Not fear it. Not fear it in terms of it’s going to take away all of their jobs, but if they aren’t using it, then they’re going to get left behind quite quickly. So of course I’ve seen all the discourse on it and yes, it’s amazing what both can do, but they still are fairly limited. That’s the reality. They operate within the parameters we give them. So ChatGPT, they can only write what you tell it to. And DALL-E can create what we tell it to create. So we, the creatives, we are required to come up with the ideas, to analyze them, to be the person that interacts with the client about it. So, you know, AI is great at producing the insights following our lead, but it lacks that well-rounded knowledge to truly grasp what this information is about. How do we transform those insights into a strategy? Now, it’s interesting when you think about creative strategy. AI is not sentient, it isn’t creative, but it can turn creativity into a process. For example, IBM Watson working with Lexus luxury car brands and the AI studying many, many years of award-winning TV adverts, and then understanding what is it that makes it award-winning. Is it the setting? Is it the wording? Is it the people? Is it whatever it might be, the colors, the imagery? And it can then break all of that down and come up with an award-winning TV advert. So yes, we do need to be mindful of being left behind and not using these tools and our competitors will, and others might turn to them as a result. So I think we have to get on board with it, we have to continue enjoying maybe more of the strategic aspects of what we do, and leave the AI tools to do more of those analytical data driven tasks that we can then oversee. And I think it’s a very exciting space to be in and not to be feared.
Adrian Tennant: Thanks to all the guests who’ve joined us on IN CLEAR FOCUS so far this year. In this episode, you heard Katie King, Renee Hartmann, Nick Wolny, Rohit Bhargava, Dave Kaye, Martin Oxley, and Paul Sloane. You’ll find links to these contributors’ books, biographies, and contact details in the transcript accompanying this episode. You’ll find it on our webpage at bigeyeagency.com. Just select ‘podcast’ from the menu. And a reminder that you can save 25 percent off print or electronic versions of the books by Katie King, Paul Sloane, and Renee Hartmann, when you order direct from Kogan Page. Use the promo code BIGEYE25 at the checkout. Thank you for listening to IN CLEAR FOCUS, produced by Bigeye. I’ve been your host, Adrian Tennant. Until next week, goodbye.
