481. The Consumer Insights Revolution

Welcome to episode 481 of the Brainy Business Understanding the Psychology of why People Buy. In today's episode, I'm excited to introduce you to Steve Phillips, CEO of Zappi and co author of the Consumer Insights Revolution. Ready? Let's get started.

You are listening to the Brainy Business Podcast where we dig into the psychology of why people buy and help you incorporate behavioral economics into your business, making it more brain friendly. Now, here's your host, Melina Palmer.

Hello.

Hello everyone. My name is Melina Palmer and I want to welcome you to the Brainy Business Podcast. Creating products, developing ads and building brands that resonate is undeniably difficult in today's noisy, fast paced world. According to Harvard, more than 30,000 new products are launched every year, but 28,500 of them fail.

Yikes.

So what's a company to do investing in understanding people, Those humans buying and selling like we do here at the Brainy Business is a great place to start and they can also look to incorporate technology and efficiencies to be more agile in their consumer insights departments so they can make more consumer centric decisions easier and and faster than ever. In today's conversation, I'm joined by Steve Phillips. Steve is the co founder and CEO of Zappi where he leads the company's product and strategic vision. He has lived in and worked across four continents to demystify consumer insights and enable brands with accessible data to inform their next move. Since Zappy's inception in 2012, the company has leveraged AI with more recently Steve has been focused on using new AI first capabilities to new models to extract more insight and value from research data. Steve has spent more than 30 years in market research.

Prior to founding Zappi, he founded Tonic.

Insight, Tuned In Research and Spring Research where he led diverse research teams trying to uncover new insights into consumer behavior worldwide. You he's also a founding member of the Supper Club, a London based membership organization for entrepreneurs. He's been recognized by the European Society for Opinion and Marketing Research, also known as smr, the UK Market Research Society or mrs, and the Advertising Research foundation for his leadership and innovation in the market research industry. Steve is also Chair of the Market Research Society's Sustainability Council where he brings a passion for helping to move the world of insights onto a fully sustainable future. At major industry events he frequently presents on the evolving role of consumer insights and today we're talking about his work and background as well as his new book the Consumer Insights Revolution.

Really quickly.

Before we get into that conversation, I want to be sure you know that there are links in the show, notes for my top related past episodes and books, ways to get in touch with Steve and myself and more. It's all within the app you're listening to and at the brainy business.com 481 now let's jump right in. Steve Phillips, welcome to the Brainy Business podcast.

Thank you, Melina. It's delightful to be here.

Oh, absolutely. I'm super excited to be chatting with you today and your work and everything.

You know, for everyone who doesn't yet know you, can you share a little bit about yourself and the work that you do?

I've been in consumer insight my entire career, which is longer than I'd like to admit right now, but it's been varied. So I worked in Asia for about six years. I worked in the States for six years. And then I've been an entrepreneur in consumer insight since so and a combination of working in qualitative, creating qualitative companies, quantitative companies. I've done a lot of work on in innovation in the consumer insight space, trying to create new ways of talking to people, new ways of understanding them, integrating behavioral economics as much as we, we can. And I'm sure we'll talk about that more. And then in the last 10, 12 years, I've started a company called Zappy, which is a technology company, but it's a technology company in the domain that I know, which is consumer insight. So it was solving the client problem of all our clients love consumer insight. Of course you do. You want, you want you to know what your consumers think about your new product or your new innovation or your new advertising campaign or your brand. But you want it, you want it faster and cheaper than certainly it was 10 years ago. And my idea with Zappy was to make it so that instead of a project taking four weeks and costing $20,000, you could make it four hours and $2,000. So that was the initial idea of trying to do great market research, great consumer insight, but in an automated fashion. And that's what really I've been working on for the last 12 years.

And I'm sure everybody listening again, it's like, hey, solid goal, like way less time, way less money. I like that.

Exactly. Exactly.

But it feels like the, you know, thing that sells itself in that way as far as being able to, to talk about it as you're able to bring it together. So just for you, touched on it a little bit. I know there are plenty of, you know, consumer insights and market research folks that listen to the show. I do a lot of work with those teams as well. And for everyone who isn't quite in that space, can you share a little bit about kind of like what goes into consumer insights work? And maybe, you know, there's a bit of this, like, journey, I guess, of how the field has evolved over time and why that even matters for organizations?

Yeah. So if you, if you imagine yourself as a large, a large company that sells things to consumers that maybe it's a Coca Cola. Right. You are continuously trying to refresh your advertising campaigns, your brand. You're trying to make a new product, you know, release a new juice or a new water flavor or variant, change your pricing, change your packaging, trying to refresh things. Those things take a lot of time and cost a lot of money to produce. So if you're, if, if you don't know that it's going to work, then it's a big gamble that becomes very risky. So there are two things you want to do. One is you want to know as much as you can about the people that you're launching that product to. Do you want to understand what my consumers think, what they do, how they are, how they react, what they like, what trends they're interested in, what flavors they like in other spaces? So you want to understand the people you're trying to, trying to sell and market that idea to. And then the second thing is when you've got the idea, you want to test it with them to see if it's going to work. And, and it's not just is this idea going to be going to work, but how can I make it better? So, you know, the consumers really like the pat, but they don't like some of the ingredients, or they do like the ad campaign, but it's not very as funny as you thought it was going to be, or one of the characters isn't particularly attractive. So you can start playing with the idea and improving it over time before you take it to market. And then, of course, after you've taken to market, you want to see how successful it is. Not just immediately what the sales are, but are people enjoying using that product? What's their feedback? How can you iterate? How can you make it better over time? And then you go all the way back to the beginning and say, now what do I understand about consumers and what's my next innovation going to be? So that feedback that you get is just really important to companies, and they get it in multiple ways. But certainly consumer Insights and surveys is one of them.

Definitely. And knowing of course, you know where my first book is called what your.

Customer Wants and Can't Tell youl, which.

Is where the behavioral economics and behavioral science comes into all of this. I know you wrote an award winning paper having to do with behavioral economics and marketing. How did you find behavioral economics? And you know, what was the draw for you there? And you know, what are some of the, you know, tips and insights from that paper?

Yeah, sure. I think my background, my, my degree was in economics. I'm an avid economist reader. I enjoy economics. I know that's a weird thing to say. There are only certain places and podcasts. I think that I would admit that.

Welcome.

It's the right word, right? Exactly, exactly. So I was reading about behavioral economics before. I was thinking about applying it to consumer insight and I was interested in it. I mean, there was a lot of work in the 90s and the early 2000s around it, obviously, you know, Kahneman, etc. And it was when I think whether it was thinking fast and slow or whether it was one of the other books that I started thinking, oh, actually I could, you know, when you've got those behaviorly economic principles like anchoring, etc. I think I could introduce some of those ideas into the way we do surveys. And that got me thinking along the lines of how can, how can I use this understanding of how people behave better to make the output of the surveys we're doing more accurate, more reflective of what consumers actually think rather than they think you want them to speak. So that was the process. And this was a while ago, so this was in the late 2000s. And I sort of came to the conclusion that we had naturally, as researchers, we'd naturally be thinking about and understood some of these concepts without necessarily labeling them behavioral economics. But knowing that when we thought long and hard about the biases we see in consumers and we started thinking, okay, how can I overcome them? And we came up with many of the same types of approaches that some of the academics in the literature were in behavioral economics were using. And so to some extent I came away thinking, yes, we could apply these, but actually we already apply some of them. But there's a problem in that too many market research projects were done quickly, we had a client pressure, etc. So you didn't have the thinking time. And one of the great things running a technology company instead of a market research company is we're trying to build something that's scalable. So actually spending a lot of time thinking about the design in the first place is very Easy because once it's built, you're going to scale it, you're going to use it over and over and over and over again rather than reinventing the wheel every time, which you do as a consultative company. So it did, it certainly did help me think through what the design of the product suite that we use at it would be. Yeah, so that's, that's some of my background and interested in it and how I've been trying at least to apply it.

Oh yeah.

So one of the things that you.

Said there reminded me of something I really liked in, in your book, which is co authored and of course a lot of what we're talking about in this consumer insights revolution. And knowing potentially I'm jumping like way to something that's at the very end. And so feel free to say we need to talk about other things first. But part of what you are saying there reminded me of, and I forget who the quote originally came from, but saying that you have, you know, there's the work before the work, the work and then the work after the work are kind of how you break up a job.

My co author, Deaf, earned grounds from Pepsi.

Okay, perfect. So, you know, I'm saying, you know, you've got the work before the work, the work and the work after the work and that in traditional kind of settings like you were talking about, of not having this, the space to be more thoughtful. Yeah, we end every episode of the brainy business with be thoughtful for a reason about where it's important to take that time to reflect, to consider, to ask good questions. And we don't tend to have enough of the, you know, work before and definitely not the work after the work. And so you, you know, talking about there's this like 40, 40, 20 split and that by being more efficient by having, whether it's through AI or systems and things like you've created with Zappy, you know, you can be more of like a 10, 10, 80 and have way more of that, you know, effective, efficient time in that work after the work, which blends into the work before the next work, I would say too. But can you share some more on this idea? Because I think that value proposition is so much as to like why any of this even matters.

Yeah, no, exactly. I think that that phrasing of work, the work for the work work and the work after the work is really interesting. And, and actually in some ways what you would like it to be is sort of 45, 5, 50 and that splits up into different domains. Right. So what you want the work to be as automated and scalable and simple as possible so that you don't have to spend time in it. Because. Because in so many ways it's the least interesting piece. And if you think about, if you think about a factory creating widgets, then what matters is, is the way you design the machinery up front. Because all of the widgets are going to come out the same and you want them to come out the same. But if they, if you have a poor workmanship in the design, you're going to have a million bad widgets, whereas if you have really good work up front, you'll have a million brilliant widgets. So certainly the work for Zappi is to make the machinery up front really strong, great quality data, great quality analytics, et cetera, et cetera. Now, in the case of our work with Pepsi, that we are not doing the work after the work. Pepsi are doing the work after the work, which is true with all our clients. So they are getting. So we've spent time designing the system to make great consumer insight. And then the work itself happens in a day instead of four weeks, as we discussed, then that frees their people up. So instead of them having to spend all the time managing a project and working with agencies and all that sort of stuff, they can just take great insight and go, okay, how can I maximal. How can I make the effectiveness of this maximized as I distribute it across the company? So if it's a new product, I'm going to spend time with the product teams, helping them really understand how, what the consumer mindset is, how the consumer works on this, how they think about it, how they would like improvements to be made, how they would consume it, what the concerns are at multiple consumption, what, how they're thinking about their kids consuming it, how it would be shopped for in the weekly shop, all of the really insightful things that the innovation team need in order to make this a great product. Instead of, in my old agency world, having long conversations with Steve about what should question seven look like and what analysis should we do, what, what multiple regression functions should we, should we have for the project and should the bar charts be yellow or green? When we do the presentation, you get rid of all of that stuff, which took huge amounts of time, and you concentrate the work in the place which is maximizing the value.

Absolutely. And as we dig in a little bit more on the, what I guess is more work before the work of building in the tools with Zappi and what you've been able to do with, of Course, Pepsi being the main focus in the book because, you know, the co authors are from there. Can you share a little bit about, I think the global and local problem and the issue that comes from siloed data and is really an important one and questions and insights and everything being in its own sort of space and knowing that this is a problem that exists even when you're not looking at things in China versus Mexico versus the US versus the UK being doing market insights for an organization that was all in one state, like running a marketing department. We had issues with the like things that came from this department doesn't speak.

To this department and they are literally next to me.

I can walk 10ft and be at someone's desk and we don't have, you know, data going across systems in a way that it just creates so much unnecessary conversation and, and on the wrong stuff and that you just lose so much because I don't know what they know, they don't know what I know. Problems all around. But if you want to expand on that of kind of that core problem and you know, founding of Zappi or, you know, however that all comes together in your brain, you run with it.

Yeah, sure. So I, I think it. So Stephan Gantz, who is co author with us on the book, he, he came into Pepsi having had a background partly in consulting, partly as in, as an entrepreneur and partly in marketing, but not really in consumer insights. So he knew he was a user of consumer insights, but not a manager or producer of consumer insights. And I think that gave him the freedom to ask questions and think about systems in a way that lots of people wouldn't have done. And he came in and he described, you know, having, having a meeting with his team and saying, you know, great, lovely to meet you all, looking forward to getting stuck into consumers. Can you tell me, you know, what's the, what's the platform where all our consumer insights live? And, and they, they sort of had blank stares. And he's like, well, you know, like your sales data sits in Salesforce and you know, it's sales or CRN data sits in Salesforce. Nielsen data sets. Where's our survey data sit? And they were like, well, mostly in PowerPoint. And it just made no sense to him. And of course it makes no sense. But up until then no one had asked that question. So that was really the genesis of the process we were going on. And we at Zappi had been thinking about this because we had been thinking because we were a technology company and we were a data company, we were thinking about data in a much more sophisticated way. And we wanted to be able to answer macro questions, not just micro questions. And what I mean by that is yes, we wanted to be able to, you know, if a client wants to sell a product in Thailand to young men, yes, we want to be able to test that product or that advertising campaign amongst young men in Thailand and give them feedback that helps them make that advertising campaign better. But we also want to use our metadata asset to answer the question, what type of advertising works for young men in Thailand? So that's a much more strategic question that happens up front. But in order to answer that question, you have to have a much more robust data asset sitting in one place. Queryable, harmonized, systematized structure, structured. And that was the problem we were trying to, trying to solve. And obviously that also solved Stefan's problem. So the book Talks goes through the story of us working together to create neutral tools for the 21st century, but also having that harmonized systematized data asset, the access to that data asset. So you can answer many more questions. I think the thing that's so interesting about writing it with Pepsi is we have multiple clients, but they were the one who's driven us most in terms of new thinking, but not just on the technology and the design. They've also driven us thinking about behavior change. And the other co author from petc, which is Kate Shard, she did the hard work. So Stefan had the vision, we had the technology, and we had to update and implement the technology appropriately for them and use that system to scale for other clients. But her job was to create behavior change within the organizations to utilize these new systems. And that we all know that, you know, technology is one of the things that matters, but the behavior change, getting people to adopt the technology is much harder than building the technology itself. And so, and so that's the story of the book is going all the way through that, but then finishing with what the future is, which is once you have that robust data asset, once you have insights about people, young men in Thailand we under know, we understand who they are, what they care about, what they think, what they feel, how they react to advertising, how they react to products, how they react to brands, then we can use that data in a strategic way to empower AI models to help create experiences for them to create new products, create new campaigns, create new ideas. So it puts our clients in a very strong position to utilize technology because they've looked at that data asset holistically.

And I really love the way that it as you, you talk about here in the, you know, the book goes through the full story and not just so often any sort of books, advice, blog posts, LinkedIn articles, you know, it's very like just do this and it'll be amazing. Enjoy. Right? And it, there's nothing to talk about like getting the buy in the conversation. Communication really matters like. And so, you know, like I said, my first book is what your customer wants and can't tell you. The next is what your employees need and can't tell you because change management, getting people to buy in is so important. Right. And it the best ideas, there's so many of them that don't do anything because people aren't thoughtful enough in how they're going to be communicating information to do a change like this, which as explained in the book, it is, it is massive. It's a massive shift to go from whatever it is that you're doing and what tends to be very reactive, getting the investment that's needed to be asking those thoughtful questions up front. You potentially have to have a pause point that can be a long pause point, right. Like we can't do other work. We're not going to do some of these other surveys the way we've been doing them for a month or six months or whatever it is so we can be ready to do it all better. It's that, you know, slow down to speed up deal, right. And that can be a hard sell even when there's value on the other side. Because getting out of that status quo, so much of what we talk about in behavioral science can be hard for people when you aren't positioning the value of what is out there well enough. And as I said at the beginning, you know, going from 20,004 weeks to 2,004 hours like feels like that should just be enough in and of itself. And I know that, I'm sure you have many stories to share that that's not always enough, even though it should very clearly be enough. Yeah, yeah, go ahead. I was going to say.

Exactly. I mean it's so. It seems like a no brainer as an offer to me. But people are always resistant to change and some people agree that lots and lots of people are resistant to change. And there's a ton of reasons why that is true. They don't build as you know, never get fired for hiring IBM people were used to the suppliers that they use. They had made mistakes before. Before or they had, but they weren't critical. They trusted them. They knew the business they Et cetera, et cetera. So there is accumulated experience in one space and no experience at all in another space. And so where is the person going to be attracted to? They're going to be attracted to what they learn. So we understood that. And there are a lot of different systems and they were mentioned in the book. I mean, so Mars as an example. What they did is they wanted to adopt our system globally, but they knew they couldn't, it couldn't be a top down mandate. They needed to, they needed to have a behavior change system that was about creating excitement at a local and a regional level behind the change that this would make to the job. So yes, it meant change to your job. But they created a series of sparks. So they had a. They called them sparks. There were people in the teams in different countries all over the world. They got them together in New York. They did a big session with them. They got excited about the future, but their job was to go back and then sell the future, but also help, help implement the, the, the new system. Because the future was going to a world where you are much more strategic. So you're not reactive, you're no, no one wants to be an order taker. And as Stefan would say personally, we wanted to go from order takers to strategic business partners. If you say to someone, do you want to be an order taker or a strategic business partner, of course they'll stay strategic business partner. But unless you show them how that can happen and say of course it means change along the way and we'll help you will hold your hands through that change. You will just get natural resistance. So that to me is the most difficult nut to crack. It was a fascinating process. I mean, look, I'm a researcher. I love people, I love how people react and trying to understand them and that, you know, that's part of their, part of the process. So it's just a really interesting space. I just found that doing that genuine transformation work is. Yeah, very interesting.

Oh definitely. And I love this concept of the sparks. I find in. It's similar stuff of working for trainings on behavioral economics, behavioral science. And you have to have our clients where it works the best is where you need at least one champion is how we talk about it, right? Like that person that is, you know, fighting the good fight internally every single day and helping and you know, we do, you know, it's like train the big team so everybody has a little bit of something that spark, right? And then you have people but that like keep the thing moving when it Gets hard because it will definitely, it always does get hard. And if there's not someone there, it's easy to just let things slip through the cracks and do them the way.

We'Ve always done them and think that.

Next time we'll do a better job. So I loved that example from the book as well and thanks for sharing it here. One of the other things I think that people are probably going to be wondering about, right Is like, so I get this question all the time of like, what project do we start on? So if we're going to do something and we're getting ready to go and people feel like you need to do the big flashy, the huge splash of the biggest project is where we're going to implement this to show the value of what it is.

Thoughts?

Yeah. Yeah. So I'd like to say there is one answer. Unfortunately people, people are different and organizations are different and some, some organizations are very top down and very, you know, you do this and get on with it. There are lots of problems in those organizations and it quite often doesn't work. But that is one way. The other one is much more just getting people to bubble up and, and actually that's a lot of the way we work with companies. We'll get, you know, one business unit in one country to use it, get excited and then effectively do product marketing or account based marketing within the organization. We will help them. They'll champion some work that was done on an ad campaign that made it the best performing ad campaign in that country. And it was built and the ad campaign was created in half the time than it normally takes and they saved 20% in terms of the budget. So it was significantly better, it was cheaper and it was a lot faster. And if you champion those stories internally, then you naturally build momentum. That is absolutely probably the most common way we work. But you do need top down at the same time because what you don't want to do is recreate a system for every different market or business unit. What you want is a holistic company overview of what the system should like and it should be similar. It might not be adopted at the same speed in each market, but you do want the same system. You don't want a salesforce which is structured differently per country or per business unit. Then the data doesn't talk to each other. So you have that problem. So you need to think about getting champions and excitement and generating stories of success at the base of the user level whilst also having a strategic overview at the top level of what this system when fully implemented, will look like. And that again, it's a big challenge. But I mean, it's the same challenge that all the consulting companies are dealing with and charging clouds a lot of money for continuously, whether it's Accenture or Deloitte or McKinsey or whatever.

Yeah, well, I also like. Thank you for that. And one of the quotes from the book being to not use Live Fire. Right. In some of. As you're going for some of those projects. Right. So some. If it's, if there's a lot riding on it, if it goes wrong and you're not 100% certain and you just want to test like that can be problematic, especially if you're not bringing in partners to help with it. And you're just gonna figure it out as you go on a really something that has a lot of eyes on it. So sometimes, you know, getting some of those small wins that you can have still stories from and things can build some momentum and, and go from there. I'm curious.

That's exactly right.

As you look back, right. As you think about kind of this story, I'm curious on this like entrepreneurial mindset journey, I guess is how I will say this. Right. So you said you, you know, being a data type of a company and then there's a shift that you're going through there. So it's like this. I know from having a business and people you talk to, there was maybe like a company before the company, like of what you started and then realizing whether it's because Pepsi called and they asked a question that you think this is actually what we. How we should be doing it and it like helped to bring things together. Can you share a little bit about it? And it's however you want to answer on this and whatever comes to mind for you. But I, I think this, you know.

There'S a goal, there's something you want.

But not getting so dead set in the path. Right. So there's this like flexibility of how you frame the problem and, and whatnot that I think is just interesting.

Yeah, no, so sure. So my, my entrepreneurial journey I did this is my fourth company is by far the biggest, by far the most successful. And it's in, I mean the, the weird thing about it is that it's in technology. And I'm not a technologist. Right. So. So right from the beginning I just needed to learn and, and I'm sort of endlessly curious. I mean, again, being a researcher, it's sort of natural. So I really had to learn about Technology, which we ended up merging with Zappy ended up merging with a technology company that helped us build it. So we ended up with a CEO who had the domain expertise and then the CTO was the CEO of the previous company. So the two of us really developed the company together. And that was interesting because we had domain expertise and development expertise simultaneously. And I think we learned a huge amount from each other. So I knew nothing about what product looked like or how you code or what the outcome is or you have to think about when you're briefing it. So it and then also we were, we're both curious and read, read around as lots of other members of the team and I mean it's just silly things that some of the Amazon shareholder letters from Jeff Bruce were really inspiring. So there's one phrase that I go back to which is strong opinions loosely held that, that I think really, really shows the entrepreneurial mindset of I really believe this. But if you prove me wrong or show me the data that says I'm wrong, that's fine, I'll move on to my next strong beheld opinion. And I will, I will change my mind as I go. Because if you have one mindset and you just implement that, then you might be right. But there's a good chance that you'll be wrong at some point. That, that shows the passion that I think we all bring to the company of, I really care about this, I really believe in this, but I will listen to you and if you convince me otherwise, or if you bring along data that convince me otherwise, then I'll change my direction and I'll help you go in the other direction that you were thinking about. And that's not normally diametrically opposed. It's just different interpretations of the best way to get to where you want to get to, to its vision. So there are things like that. I mean, yeah, I'm an avid reader and podcast listener and just listening to other people and their advice. And then of course adopting that iterative agile mindset, which agile came out of technology came out of a way of building software instead of waterfall. And when you're in a technology company working with developers, you, you naturally, well, you don't naturally, but I, I, we naturally worked in a very agile way. And that approach just makes you think differently. I think about, about building a company and about, you know, silly things like most companies set a budget at the beginning of the year and then don't change it and then you beat the budget or you, or you miss the budget, whereas actually by far the most effective way of running a company is to have an agile budget where you set it at the beginning of the year as a vision and. But then you reassess where you are regularly and then you can reassess the resources the company has, the investments it's making, et cetera, et cetera. So working in an agile framework in multiple aspects of the business is much better way of running things. So I'm not sure if I answered the question, but that's my.

I love it.

I think these, I like to have these sort of choose your own adventure questions as we go. And so, you know, I don't know that I even asked the right question. Who knows what I even asked?

And we. The answer matches.

They did like two copper entrepreneurs, right? Make it up as you go along.

Yeah, hey, you know, I'm talking, you're talking. Are we talking to each other? Who knows? We're in the same conversation with that. Well, no, I really think you did answer the question. And I also love that strong opinions loosely held I think is just so well worded as they're, you know, they're oft quoted for a reason. Right. The other one I like that that made me think of, reminded me of is that, you know, even if you're on the right track, if you don't move, eventually you're going to get hit by a train, right. So you're going to get run over. So you got to do something. And I would say at this point, AI and ChatGPT and all these things are really the train that's kind of coming in into the world here for.

People who are feeling still a little.

Bit scared or skeptical. I know we talked about the, you know, the work and the work before the work and whatnot. And where you're saying, you know, in the book it talks about this idea of like, but if I'm not doing all of that stuff, what, what are my team and I gonna even do? Right? And that is the real fear that's at the base of it. Like, what job is there left for me if I'm not doing all the work? Because it's, I'm so consumed with the work, I don't even have this space for other stuff. And knowing that, you know, if you have it to where the work takes up, you know, 5 or 10% of your time that I think in a way can make it so that the, this like looming fear of, of AI is actually lessened. Because if you build the right skills of being thoughtful, you know, before and after the work and all it does is this little bit of the work, but it allows you to do so much more. There's a lot of opportunity there. But what advice, you know, would you give for people that are maybe anxious or stressed or rebelling against, you know, the technology AI aspect?

Well, I, I wouldn't rebel against it because it will just going back to the train crash thing and it'll just go over. You've got to, you've got to jump into it. I think it's like any technology revolution. It will displace some activity but also create other activities. And I don't know the impact. I mean, I'm very interested, but I don't know the impact it'll have broadly. But I do think I have strong opinions, Lucy Held, about what it will do in consumer insight and certainly a vision for where it can go. So because it makes the work so much simpler and so much better, and some of the work before the work and some of the work after the work can be done by AI, then if you start thinking about what is the root of consumer insight, what it is, is to help people make better decisions. And then you say, okay, how many decisions does a company make a day? 100,000. How many of them are informed specifically by consumer insight? Maybe two or three. Well, why don't we take the other 900, sorry, 97, 99,997 and provide consumer insight into those decisions? Because we can do it so much faster. We can do something cheaper, we can use synthetic, we can use AI to help it. So suddenly we can become a much more important function within the business because we're enabling better, smarter decisions that are based on understanding of consumers. But I think that's a wonderful place to be. I think it makes us much more important. It means there's much more work to be done. But what is that work? That work is thinking work. It's about how the organization works, it's how you deliver that insight, it's how they interact with it. It's how we learn as we go developing systems that worked on top of really great quality data. So I think the activity that will happen in a consumer insight department at a large company will be very different in two or three years. But it doesn't mean it's less people, could well be more people, could well be more people, and it could be way well be more important. And I think that's the process you've got to go through of not thinking, just that this makes things more efficient. And so there's less work to do. But this changes the nature of the thing and so it can create a lot more work. But that work is great work that makes your company better and makes decisions you make better and makes the products you make better and making advertising campaigns you make better. You know, just it changes things and that's what you've got to think about and adapt to and it can be a wonderful place to be.

Oh yeah, definitely. I love that. And I think it's back to that, you know, making a great case for the opportunities that exist when we have more time to be thoughtful about those opportunities. Right. Instead of just in that like day to day we can't see past the next task or the thing we're already behind on. And by having that opportunity to pause, there's a lot more that you can be doing and help to actually be more valuable if you get ahead of it. Right. If you don't.

Exactly, exactly. Then the train analyst comes back.

Perfect.

Well, as we go to, you know.

Close out the conversation, are there any last like key thoughts or insights that if you were going to share for the, you know, the world of like a great place to start, in addition, of course to getting their copy of the, of the book and learning about consumer insights revolution. You know, what's, what's a great last tidbit?

I love playing and exploring and a Sora is released today, so happy Sora Day. Unfortunately, it's not released in the eu, it's released everywhere. It's in Zimbabwe, it's in the Gabon, it's in Venezuela, but it's not in the EU because of various data law problems. But anyway, I think Sora will be one of the, one of the next wave of incredibly disruptive, exciting AI technologies. So if I, if I wasn't in the uk, I would be piling onto Sora and playing with it and developing my own videos. And I must say I'm equally excited that the, you know, the Google geometry and The Google Maps AIs will hopefully come out in Q1 or Q2 of next year. So pile in and play would be my advice.

Awesome. Well, I love that and it'll be interesting. So now we'll have for anybody can go back and look and know exactly when we, you know, recorded based on when the episode comes out that, you.

Know, for those who want to dig.

In but you know, we'll be good to look back when this comes out and say what, what all has happened and who has access. I always think that it'll show how quickly things change and evolve based on these launches in our world today. So awesome.

Well, thank you so much for joining.

Me on the show. It's been really delightful to chat with you. For everyone who is, you know, now super excited to connect, to learn more, to follow you, what's their best path.

To do so LinkedIn is probably the easiest. Just connect with me on LinkedIn. It'll be delightful.

Perfect. And we'll have links for that and for the book and to Zappy. We'll have it all there in the show. Notes for people. So thanks again for joining me and yeah, delightful to chat today.

It was a pleasure. Thank you. Melina.

Thank you again to Steve Phillips for joining me on the show today. What got your brain buzzing in today's conversation? For me, one of the most common questions I get is on how to pitch the idea of using behavioral economics and psychology internally at work when you're potentially the only person who's interested or you need to get a new job role. That includes be. And I think this conversation around incorporating technology into consumer insights is a great parallel and shows some of the aspects of where people can get hung up and things like status quo bias can get in the way of something, even if it's objectively better. Specifically, I'm thinking of the discussion around.

The work, the work before the work.

And the work after the work, and explaining that so much work gets done in the work and setting up that work that there isn't much time for the analysis and other work after the work. But all of that is so important to ensure you're working on the right things, being more efficient and effective in the upcoming phases, and getting the most value out of all the work that you do in that department of insights and just across the whole organization, instead of having a ratio like 40, 40, 20, where you have so much time and manually doing things and supporting the idea of what the work is even going to be, and then doing the work, you don't have much time to understand what happens and do the work after the work. You could Instead have that 10-10-80 split, meaning you don't have to devote human energy to a lot of the work, saving time and money and leaving lots of great space for asking better questions and being more thoughtful and creative, which are such great wins. But when it's you and it's your job, it's easy to feel a little hesitant asking questions like will we be replaced? What do we do if the work we spend our time on is being done by a machine? I'm guessing in Seeing it this way, you can see the human behavior response and where someone might say they like the idea but then subconsciously make it hard to implement. You can see how framing when sharing the idea makes such a big difference. For example, if you pitch that by saying you know 80% of the stuff you do every day, most of your job, and the jobs of everyone on your team, well, we want AI to do that, so can you help train it? No thanks. When you miss the why and don't properly frame the value, it feels really bad and scary. If you can share instead about the importance of asking better questions of why you value the expertise of the team and devoting their time and energy to the fun stuff that they'll be able to do more and have a better work life balance or whatever term you like. That they can have more space between projects or maybe even asking people about the parts of their job that they hate doing that are mundane or repetitive and that they wish they didn't have to do so that they had more time for other great work. Then you can use those insights to help build out the first pass on integrating AI so people can be excited and on board, and then you can gradually add in more as they get comfortable with it. This shows how behavioral economics can be used to get people on board with projects and internal communication. Like I talk about in my book what your employees need and can't tell you. There are links for you to get your own copy in the show Notes, along with links for the Consumer Insights Revolution and my other Top related books.

Episodes, ways to get in touch with.

Steve and myself, and more.

It's all waiting for you in the.

App you're listening to and@the brainybusiness.com 481 and thank you again to Steve Phillips for joining me on the show today. It was a delight to chat with and learn from you. Join me Tuesday for another brainy episode of the Brainy Business Podcast. It's going to be a lot of fun. You don't want to miss it. Until then, thanks again for listening and learning with me, and remember to be thoughtful.

Thank you for listening to the Brainy Business Podcast. Molina offers virtual strategy sessions, workshops and other services to help businesses be more brain friendly. For more free resources, visit the brainybusiness.com.