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Peter Crosby (00:00):
Welcome to unpacking the Digital Shelf where we explore brand manufacturing in the digital age.
Peter Crosby (00:16):
Hey everyone. Peter Crosby here from The Digital Shelf Institute. More efficiency and more growth. The often conflicting pressures of business today seem unrelenting, especially on the digital shelf. Mike Monroe, managing director at Deloitte Digital spends countless hours in c-suites and with teams at brands defining the strategies, processes, tech stacks, and experience innovations that lay the foundation for a more profitable future. The ingredients to scale a content supply chain to both continually optimize for performance today while investing in an AI fueled future of true personalization and operational transformation. And according to Mike, what's at stake is that your brand will either win big or lose Big. Mike joined Rob Gonzalez and me to provide a journey map to that future. Mike, thank you so much for joining us on the podcast. We are super grateful, so excited to have you here.
Mike Monroe (01:13):
Thank you, Peter. I'm excited to be here. I've been looking forward to this conversation,
Peter Crosby (01:18):
Well in this economic time, sort of this new business reality that we find ourselves in the conversations with our DSI members and on the podcast really, and really revolve around the pressures of needing to simultaneously grow the top line, squeezing better performance out of the digital shelf and omnichannel, while also growing the bottom line IE lower costs and drive greater and greater efficiency. And that has a lot of implications for our audience, for the brand manufacturers that are trying to win. And I know your customers at Deloitte Digital, I think, so that's why I wanted to sort of check with you first. Do those themes resonate you and are they top of mind in your client conversations?
Mike Monroe (02:00):
Yeah, Peter, that's a great question. What we see across the board is with our clients is that growing the top line, protecting market share, growing market share and increasing profitability are top priorities and they're under a lot of pressure. And so enabling the teams and the brands to be able to create the results they're looking for, these are major activities and they always have been major activities, but they're just increasingly more challenging. So our clients are very focused on those things, and especially in the economy that we're working through now, it's especially important finding, especially a lot of interest, and we're helping a lot of folks improve those.
Rob Gonzalez (03:02):
So one area where you could in this theme hit the top line, and the bottom line is retail media, which of course is booming. People are spending crazy amounts of dollars on retail media. I saw a stat, I don't know if it's in 24 or 25, that retail media advertising is going to be larger than television advertising in the United States. It's just an ocean of money going in there. And for large manufacturers, it's one of, if not the largest line item relating to the cost of running their digital business. And one of the things that you've had a strong opinion on, and I'd love to hear you talk about this, is if you improve the customer experience and the brand experience of what shoppers are seeing online on the digital shelf, on those product detail pages, it can impact both the top line in growth and also the bottom line because it increases ad efficiency. And that's a story that I don't think that enough people are talking about or really understand. And I'd love to hear your views on the
Mike Monroe (04:10):
Matter. Yeah, Rob, it's true. We see that brands that improve the efficiencies in that conversion funnel, that engagement with their consumers and moving them through the conversion funnel to whatever conversion is for them, whether it's add to bag and check out or some other type of conversion brands that improve that conversion funnel, remove the friction and create and experience. It enables the customer to identify what they're looking for, discover what they're looking for, and add it to bag and checkout or whatever that conversion moment is for that particular brand. Folks that are doing that well are the ones that are the most successful. And the other truth is, is that most brands are not doing it as well as they could be. So there's substantial upside inside of that use case for a lot of brands.
Peter Crosby (05:13):
Yeah. Mike, can we dig into that a little bit? As you know, brands are often selling, they're selling through their own D two C sites, but they're also selling through sites that they don't control and yet that they can influence. And I know Deloitte Digital does a lot of work in the refinement of PDPs and also certainly in the quality and effectiveness of retail ads. So can you give us maybe some real life examples or blinded case or thoughts of in those moments that are the friction moments? What are some things that you've seen some brands be able to do really well?
Mike Monroe (05:50):
Yeah, Peter, what I would say is the mistake many brands make is they take a one size fits all approach to playing in these different channels. Oftentimes we see clients that they have a repository of content and that content was created to a certain set of specs. And then as they play in different channels and different outlets that have different specs, they try to use that same content without modifying it to take advantage of what's available to them on that new platform. So they take a one size fits all approach to the content that they're publishing on these sites. And what we find, one of the things that we do is we look for the opportunities to make improvements in how that content can better conform, can better take advantage of the features that are available to them in these different channels. And just by making small modifications, we see significant upticks in conversion that translate to immediate dollars, immediate and sustainable dollars that come to the bottom line dollars in the form of margin dollars in the form of average unit value, dollars in the form of larger transactions. So just by evaluating what's available to them on the different channels and ensuring that their content takes advantage of those features that are available, that are on par with what the rest of the shopping experience is like on that channel, really positions them to perform even better and drive more efficiency and profitability.
Peter Crosby (07:52):
So in this time where you, because I'm keeping these twin pillars in my head, right? Sort of growth and efficiency and what you're talking about, probably the most efficient thing is one size fits all because I only have so many people, I only have so many cycles, et cetera, and so much money to spend, and so I'm just going to do the best I can with my top X products and call it a day. I think. How are you helping clients work through that tension and take the leap towards being more specific across channels? How are you inspiring that bravery?
Mike Monroe (08:34):
Wow, this is a great, really great question and it is a big answer. There's a lot that I could say about that, but let me try to be efficient with my answer. The clients, we'll call it content supply chain and the state of that content supply chain is a big consideration in terms of what solutions, what recommendations will have to be able to take advantage of the features that are available to them on these different channels. And the answer is not necessarily a binary answer. One size fits all is a framework to think about, but it doesn't mean that everything has to be changed to plan the channel. You can go through and often folks do go through and prioritize where they want to make changes, where they want to make improvements so they get the most bang for their buck. So there is some prioritization that can happen.
Then we have other brands that are very ambitious. They're really looking towards the future. They're thinking about how they take their systems and processes and teams that they have now and begin to position them for what's happening next. And so those brands are really looking at their content supply chain and identifying how they create a supply chain that is nimble and efficient and one that is well positioned to continue to learn and improve based on the market results that they're getting and to drive efficiencies within that supply chain at all times. So the answer is you can prioritize what you do and apply your efforts where you're going to get the most bang for the buck, or you can really take a look at your content supply chain and figure out what needs to be done to position it for the future while you take advantage of all the features that are available to you on the different platforms you play in.
Rob Gonzalez (10:46):
That aligns with the experience that we have working with some of the larger brands. What they'll do is they'll, like you're saying, they've got to make choices on exactly where they focus. So where you get the biggest bang for the buck tends to be the bestselling products in the bestselling channels. So they'll do a lot of optimization on the top X percent of products on Amazon, on Walmart, on target, on Kroger, on Home Depot, but you get to customer number six on their list and they're doing less of that work, or you get to skew number 100 on Amazon and they're not exactly doing a bang up job on every single feature on Amazon. And there's just only so much time in the day and so many humans, and there's a lot of work to be done on the content supply chain is often what we see.
And so I wonder, two questions for you. One is, are there ways for companies to get scale today to do more of what you're talking about every single product on, I don't know, the top 20 channels taking advantage of every feature? And then the second thing is, and this is a buzzword alert, the second thing is artificial intelligence. Does ai, does Deloitte see AI as being a scaling superpower here where you could take some of the strategic intelligence and operational effectiveness that you bring to the content supply chain and use AI to effectively apply it across a much greater variety of channels and products? So it's like the before AI efficiencies and after AI efficiencies in that world are the two questions I've got.
Mike Monroe (12:26):
Yeah, yeah. So let's talk, obviously, lemme try to address the before ai. Deloitte recently conducted some market research where we surveyed about 650 senior marketing executives to understand what are some of their priorities right now, how are they going about tackling those priorities as well as what are they thinking about? How are they exploring ai? The research we did showed that right now today, marketers are having to create more than 50% more content this year than they did last year.
Peter Crosby (13:08):
Mike Monroe (13:09):
50% more. And that half of those marketers are struggling to meet those needs now. So there is not withstanding what's coming down the pipeline, what's in front of folks right now is a predicament that they are struggling to work through, struggling to meet the demands of. So that is where we're doing a lot of work right now to help brands identify efficiencies to rethink how their content supply chain works to better go after all the opportunities that are out the mi. I understand, and I talked about the prioritization of work, but in the long run, that's not the way to grow your business because you're not going to give all of the products the opportunity to grow that they need. You're going to ultimately build a business that potentially is a little lopsided. So there's a lot of work that's happening right now to help drive efficiencies, to help build a more sustainable and agile content supply chain because of what marketers are experiencing.
Peter Crosby (14:25):
Hey, Mike, before you get to the AI phase, I'd love it if you could dig into the next level of detail on that. If you had a top three or top two or whatever of what you've seen some clients do with you that have unlocked that kind of efficiency. Do you have a couple of thoughts there?
Mike Monroe (14:43):
Yeah, there are a couple of principles that really deliver the most value. And the first one is creating a factory that, and this is cultural, creating a factory that is one that learns from itself, that has a virtuous cycle where market feedback, market results, what worked, what didn't work is fed back into the factory and more of the things that work are done and less of the things that don't work are done. So this iterative factory concept where there's a regimen and there's a mentality and there are decisions made actively in an ongoing way about what to do more of and what to do better, that's one thing. Other, another principle that is super key is ensuring that the inputs into the factory, the brief, whatever those instructions are, but that kickoff the process of making something are very clear and very high quality inputs that way that the flow of work is one that can be as quick and as fast as possible.
If the inputs are not clear or they're incomplete or all the myriad of things that can happen, it really slows down the process. And then of course underneath all of that is the technology that enables the factory to sustain itself, that enables the flow and the storage of content and then the ultimate delivery and publishing of that content. That technology solution is super important and we find many, many clients have a patchwork of systems. Many folks are living off spreadsheets and things like that. And so the evaluation and investment in technology is super key here too.
Rob Gonzalez (16:57):
So before you jump onto the AI part of this, I've got a little tech joke, which is half of this is a venture capital said this about 10 years ago, half of the businesses he was funding were taking workflows from spreadsheets and building billion dollar SaaS companies for each workflow. And the other half were taking businesses and turning them back into spreadsheet processes.
And for ai, I've heard the exact same possible joke future. You've got the large language models do everything in a way. And the businesses that are coming out of Y Combinator and venture capital being funded, so many of them are taking, Hey, there's a generalized model that can everything and going specific on one workflow, one user, one task, and then obviously there's going to be the reverb, the pendulum will swing the other way at some point and come back to more general use cases. So anyway, I thought that was funny when you were just bringing up the people working in spreadsheets.
Mike Monroe (18:07):
I am very familiar with this concept. I would just say that if you are a leader of a business of a brand that manages this function, one thing that's I think very important to think about is ensuring that all of your users are using the tech platform, the tech investment that you've made, and that you're forcing your tech team to support the use cases as they arise. What happens in real life is that a lot of users just work outside of the system or use cases come up that were never considered, and so they just improvise something that's offline. And I understand the virtue of that, believe me, in the practicality of just you got to get something done, so you got to figure something out, but you have to require people to work in the system and you have to acquire your tick team to support these use cases. Otherwise you ultimately go back to spreadsheets because you don't have the flexibility that you need.
Peter Crosby (19:13):
That is really important insight that resonates deep. I dunno whether it's my soul, my gut, or wherever, but I totally hear that. And that's why, I mean, part of evaluating technology I would imagine is figuring out how flexible is it to accommodate those use cases you can't even possibly begin to recognize, and that's a tough thing to evaluate a technology platform for it sort of proving a negative like, oh, well this solved this thing that I've never even thought of yet. But it's really important to have that level of foresight as you do your evaluation, I would imagine. I imagine
Mike Monroe (19:52):
You hundred percent.
Peter Crosby (19:54):
Mike Monroe (19:54):
Peter Crosby (19:56):
All right. So tell us how AI is going to solve all this. Will you please?
Mike Monroe (20:01):
Yeah. The way that the research that we recently conducted showed that marketers are very interested in ai, that a large percentage of marketers are actively exploring actively identifying tasks that can be converted to ai, that humans are still very much involved in the process because the governance of the outputs as well as the management of the sources and the inputs require high levels of skills. So very skilled people are very much part of the process, very much part of the work that's done. And what we're seeing is marketers placing what I like to refer to as no regret betts. They're identifying areas where productivity can be raised and making the investments to use AI to drive productivity gains. And we're seeing the research is showing that big swaths of marketers are implementing these kinds of use cases now and seeing meaningful uplifts in productivity, seeing meaningful double digit numbers of hours being reduced from the process because of the implementation of ai, the utilization of ai. So really they're working on what I'm calling no regrets, betts, and then starting to think about emerging opportunities now that I can do more of something. How can I use that to do something I was never able to do before? How can I create content? How can I create experiences? How can I drive conversion in ways that I could never do before? So that's sort of the next stage where we're seeing marketers starting to think about and where we're helping marketers to think about how they would do that.
Peter Crosby (22:09):
Hey, Mike, what we're hearing from our DSI membership may, I know you could tell me, may represent a wider swath of customer size and complexity than maybe you deal with on a day-to-day basis. And we're hearing sort of a range of reactions to AI from, oh my gosh, we're all in all the way back to our lawyers, won't even let us. And I'm wondering if you are seeing that and on your no regrets, betts, if we have listeners that are sort of dealing with internal resistance and we talk a lot about keeping humans in the loop. Do you have advice around how to break that log jam in a way that's responsible for the company and can lead to victories that might be released, some of that resistance?
Mike Monroe (22:59):
Yeah. Well first I would say I would encourage brands to really take this moment, take this capability very seriously and understand that it has the very real potential to be transformative, to be transformative of their business, and also to be transformative of their competition's business. And so if they believe that, and I encourage them too, then they need to create organizations inside of theirs that begin to think about what their charter is going to be with ai, what are the rules of the road? How does legal play a role in this process? How does legal get comfortable with any issues? The issues that arise from Gen A, there really needs to be a formal and agile structure in place that outlines what the rules of the road and the guardrails are going to be and ensures that they have buy-in across the board. And then we see once that structure is in place, once that sort of center of excellence is in place and they've created that framework and they've created that foundation, we see brands then challenge themselves internally to begin to identify the use cases that are going to deliver the most value for themselves.
So it's really taking it seriously, identifying that and believing that it's going to be transformative for themselves and their competition, putting the organizational framework in place to set up the guardrails and foundations and then challenging themselves to drive value using this technology.
Rob Gonzalez (25:04):
The interesting part of that that I've heard people struggle with and I struggle with sometimes is when you say this is going to be transformative in the business, it's hard for me to visualize exactly in what way. I'll give you things that are easy for me to understand. The use cases for generative AI are generative. So writing descriptions, writing SEO optimized descriptions, doing things like applying qualitative review to descriptions, generating a lifestyle image. There's things like that that they're task oriented, they fit somewhere neatly in a content supply chain workflow. They're taking something that's repetitive that a human does over and over again, and instead having a machine do it maybe with a human in the loop to review the output before it goes out in the world. And there's just so many of those clerical, repetitive white collar things that AI gives scale to.
They can summarize meetings in our podcast, they can remove the ums and make us sound more intelligent. They can do all those types of clerical things. But then if you're a large branded manufacturer and you've got operations in 150 countries and you're sitting on 20 billion of annual revenue across the world and somebody says, this is going to be transformative for you, transformative to your competition beyond just the clerical tasks, how do you think about that? Because it doesn't transform necessarily making the soup or making the drill or does it and on what timeline. And so I think that's something folks struggle with when you're engaging with the C-suite, what questions are you getting when they're trying to reason about that? And like you're saying, where they're trying to reason about the investment today and over the next 18 months and what are the guardrails and what's the ROI and all that? I think there's a future possibility, but it's kind of in the fog, if that makes sense.
Mike Monroe (27:09):
Yeah, and it does make sense. Makes a ton of sense. And what you've outlined Rob, is exactly the conversations that folks are having and what I would say, you asked about the c-suite, when we're talking to the c-suite, we're not talking about use cases, not that is not where the C-suite C-suite doesn't want talk about the use cases. They want to understand, they want to be able to envision how this capability can be harnessed and used obviously to drive growth. And so we encourage folks to kind of bucket the opportunities in three different categories. I used the term earlier, no regrets, bets, this is the use case level stuff that we talked about and Rob you described. Then the next level is emerging opportunities, or I like to think of that, of new ways of engaging with your consumer that you could never have done before.
For example, you could personalization, really truly creating one-to-one marketing truly becomes enabled through ai. I can market to Rob, I can market to Peter, I can create an experience. It feels very real and very personal to you that I could never have done before. So those are kind of the emerging opportunities. And then we think about the next level, which is really how can they transform the way their business thinks and operates, whether it's new ideas or in terms of how they research different ideas, how they deploy technology, how they drive their technology roadmap using ai, how do they really transform the way their business operates becomes the third area that we encourage people to think about that we talk about at the C-suite level. So at the use case level, that is the most practical and available place for folks to really sink their teeth into. But the true value and where the C-suite really wants to think is that these emerging opportunities and how to really transform their business. And that is why when I said earlier, once the client has the framework and guardrails in place, they can then challenge their business leaders to identify the most valuable ways to deploy this technology, to grow their business and to drive growth.
Rob Gonzalez (30:12):
The most compelling personal use case I've had with Gen AI in general is one that's really hard to quantify and exactly what you're talking about, that second bucket on big strategic possible changes. So for me, you ever see Harry Potter and the Chamber of Secrets, how Ginny Weasley gets the diary of Tomm Riddle and she writes in the diary and the diary talks back to her and it's kind of dire what that diary causes her to do. But in real life chat, GPT can be kind of like that. You can write in the diary and it'll talk back to you. And I found that when thinking through strategy or when thinking through tough decisions, it's more effective than journaling and it's often more effective than talking it out with somebody else. There's this thought processor that kind of makes me and my thinking better. And how do you quantify that?
How do you put an ROI on that? And then I think if you're a multinational organization and you have, I mean there's a lot of VPs that have a huge amount of leverage on the success of the business and you're giving them a thought buddy to work through ideas with this. I mean that's a weird use case in a way, but you could see it actually making everyone better and you make VPs better. And my gosh, that's got a lot of value to a business and that's a totally different way of working and it could probably impact the strategy in major ways. And so I feel like the fog is that second bucket that you had listed and way of thinking about it is kind of use cases like that which are legitimately different than the way that folks have operated in the past. And therefore hard to imagine in a way until you're doing it or until you see somebody else doing it.
Mike Monroe (32:08):
Yeah, I love the way you frame that and I think having another partner, another point of view to bounce ideas off you to share with you, in addition to journaling, in addition to having your team that you brainstorm with and work with, it's another tool that can enable you and Rob, we're not even in, this is not even the bottom of the first inning. I know and obviously the level of adoption and interest in AI is very high, but truly there's so much more to go. And once teams get comfortable with this and begin to understand the strengths and weaknesses and all of that, then I think the real ideation, the next level of ideation and thinking will come and even better ideas about how to use this will be put to use.
Peter Crosby (33:22):
And to close out. On that note, Mike, one of the things you were talking earlier about sort of a 50% increase in the content that people are required to get for the digital shelf right now, even before all of this. And when you talked about personalization as new ways of engaging with your consumer, and it's probably not the holy grail anymore, but the holy grail that always came up to in my head was that on a retailer site, as soon as I arrive through whatever means, and maybe even everywhere along the shopping journey, that experience on when I sort of get first attracted to a retailer or to a particular product and then through to the product page would be a completely different experience for me than for Rob, than for Lauren, than for you. And when I think about that, the amount of content required to be able to personalize and data to be able to personalize on the fly in the shopping and decision experience is massive. And so do you see that if not the holy grail, the sort of at least a medium holy grail is actually coming to the fore, is the technology tech stack and the processes starting to come together and the AI to make that actually possible through a brand and retailer collaboration?
Mike Monroe (34:53):
Yeah, Peter, I really love that because I mean we've been talking about personalization for a long time. We the industry
Peter Crosby (35:03):
And it's always disappointing to be
Mike Monroe (35:06):
Yeah, it's true, it's true. And it is. We are truly on the brink of being able to really create one-to-one marketing. We are working with brands now that they've made the tech investment, they've got the data, they've got the decisioning, and now they're at the content supply chain level where they're working through how do they have content for Peter, how do they have for Rob, how do they have content for Mike? So they give you what they think you want as you want it. So it's truly there and it will truly be there. We will be there very soon. And the thing that I truly believe about this too is the first brands that figure out how to do these things well, this conversation we've just had about ai, the brands that figure out how to do this will win big. And the folks, the brands that do not, that lag behind will lose big. And so it is something that we are encouraging all of our clients take very seriously and to put really allocate a fair amount of bandwidth to figuring out,
Peter Crosby (36:32):
Wow, what a great way to close. So Mike, just to close, I'm going to put you on the spot a little bit. You mentioned that survey of 650 senior marketing leaders. Is that something that you can share publicly with the DSI audience? Where might they be able to find that?
Mike Monroe (36:50):
Yeah, Peter, I'd be happy to. You can find that survey on LinkedIn. We posted it recently. And if you look me up, Mike Monroe on LinkedIn, you'll see that I posted it yesterday also. And you can access the survey through the link in the post. It'll take you right to deloitte digital.com where you can also review the survey on your own.
Peter Crosby (37:18):
Well, Mike, thank you so much for joining us and I know you're about to become a grandfather, and I know that by the time this airs, you will have brought you and your family will have brought a wonderful new life and hope into the world. And so I just wish you and your family all the best in this time of joy.
Mike Monroe (37:37):
Thank you, Peter. That's very kind of you. I hope I was helpful and I really enjoyed speaking to you and Rob today. It's one of my passions. Thank you.
Peter Crosby (37:47):
Thank you. Thanks again to Mike for all the wisdom and to Rob for the Ginny Weasley reference. For all that and more, go to digital shelf institute.org and become a member. Thanks for being part of our community.