[00:00:00] Welcome to Unpacking the Digital Shelf, where we explore brand manufacturing in the digital age.
[00:00:39] Where AI strategy engagements with their clients, and turn them into a framework called the Matrix, MAITRIX.
[00:00:50] Chris Perry and Oskar Kuzubsky rejoined Lauren Lee back in metre offer you the Blue Pill that will help you make order from chaos and align your organization on a meaningful AI path.
[00:01:03] Chris and Oskar welcome back to the podcast, we're so excited to dive into the Matrix with you.
[00:01:09] Thank you for having us, it's exciting.
[00:01:12] Thank you. I should probably explain why the Matrix. So Operation Operation Lizing AI is not for the fate of art, it's definitely in adventure and people are still figuring it out.
[00:01:25] While AI continues to evolve at this incredible pace and so we know so many people in the community are struggling with it, scared of it, trying it. And it's just going to be test and learn for a while and test and learning really requires a framework.
[00:01:42] It really does so that people can approach this in a very cross-functional, careful measurement-based way.
[00:01:52] And you guys had to go all the way to an alternate reality to come up with a framework that would work with this crazy world.
[00:01:59] And so it's Keanu Reeves might show up because it's called the Matrix Framework and it's spelled cleverly MAITRIX.
[00:02:10] So first question, in this scenario are we choosing the red pill or the blue pill?
[00:02:19] Definitely the blue pill.
[00:02:21] The blue pill, okay, all right.
[00:02:23] There are people that might take a red pill and then again they'll wake up as if nothing ever happened and they'll just go about their life.
[00:02:31] But those who are boldly the first movers out there, the early movers in this space who bravely take the blue pill whether it be for e-commerce, on me or AI or whatever comes next, they will now be forced to go down that rabbit hole if we don't spoil the movie for you.
[00:02:47] I love watching it's been out for a while, but it's definitely worth going back through the whole series to watch the progression and we're going to play to that storyline here.
[00:02:55] I love the way you always spice these themes up with a memorable theme.
[00:03:01] So let's dig into it.
[00:03:04] Tell us what sort of what was the impetus for you creating a framework at all and what is the Matrix Framework?
[00:03:13] So for a while now, again we work with a ton of brands.
[00:03:18] Again, whether it be on trainings or advisory or capability work or tech stacking and a few years ago I think we even shared it on our podcast here.
[00:03:26] We had put together that trillion value skate because there are a lot of these land skate visuals to show all the different players in media or in our case all the different digital commerce tech stack partners and capabilities.
[00:03:40] Not again to push anybody towards one company over another, but just to give everybody an idea of how they all fit into that ecosystem.
[00:03:48] And increasingly when we put that together, AI was just kind of a fleeting thought it was starting to be integrated early days, but it wasn't as height as it is today.
[00:03:57] And we realize there was an opportunity as people are now focused on what's the really, really about AI to lay out all the different players in an organized fashion onto an AI landscape.
[00:04:09] And so Oscar and I, getting to work with so many different companies on the brand side of starting to implement it with different test partners, all the different capability solution partners who are starting to implement this in to their solutions.
[00:04:22] We realize we could start laying this out again in an unbiased kind of independent perspective way.
[00:04:28] And we laid them out like a lot of retailers and tech companies and then obviously solution providers and data companies onto this kind of matrix as it ended up looking like.
[00:04:39] And then that obviously as soon as you said there were matrix and we thought AI, we immediately paired together the movie switch which was a very convenient connection.
[00:04:49] But we have that visual and anybody listening can I know it's hard to hear a visual but we have all this is available for you.
[00:04:57] To tap into after today's recording for free just for for democratizing great insight here, but we realize that laying it out just on kind of a map does it necessarily show you how to integrate right it.
[00:05:10] It shows the big picture, but it's not the process and so we kind of took then that movie theme and if you've watched the movie this doesn't swell in or if you have it, it won't swell at the end for you.
[00:05:22] But there's a little a little boy in the movie who in in the real world can bend a spoon he's called spoon boy it's very appropriate and then he when he was bending the spoon it kind of created this like infinity loop visual which then we took towards kind of this go to market.
[00:05:40] It strategy loop and we realize that there were actually eight keys if you will that and this isn't to make you know, trying to over complicate the four keys of sales of marketing but there are eight keys that all of those different capabilities and use cases really fall into that actually does help us mentally see how to like tie them all together and start to integrate them into our real go to market processes and so.
[00:06:04] So we obviously won't have time to double click in all of these peas but they some of them are more important and maybe lower hanging fruit than others in the short term, but basically we start kind of on the loop and you'll be able to see this too there's platform which is really though the through what or through whom do I sell what I offer as a CPG as a consumer good organization right that would be the retailers or any any platform I might sell device that I might sell through.
[00:06:32] I'm in the future proposition is the what I sell right so it's my portfolio it's my availability it's it's my my assortment mix it's my pricing then then we get to presence which is the how I show up it's my content it's my search placement on that digital shelf or other shelves other placements.
[00:06:52] Then we get into promotion which would include obviously traditional trade problem but more importantly media retail media paid search.
[00:07:00] From that end and then we would get into performance which underpins all of this right the actual metrics and measurement.
[00:07:07] And then another thing that kind of underpins but on the visual it's the other upper part of the loop as it comes back around we kind of lumped people process and partnerships together it is they are separate peas.
[00:07:19] But they're not for all intense purposes we are all the people in these organizations who need to leverage AI within new processes and often need to be tapping partners.
[00:07:31] Not just our retail is but the actual third party solution providers because we don't produce AI tools we produce snacks or laundry detergent or beauty products so we probably really do need to outsource some of that at least in the early days to someone else.
[00:07:48] That can plug into some other partners on a process so and this again keeps feeding itself so this isn't to be high level theory there are a lot of use cases as well with each of these that are brands are actively testing today.
[00:08:00] And we have as it happened to them as we go through our discussion.
[00:08:03] And let me you know as it because you've been rolling this out now for a couple of months yes yes we've been doing it for a while before we put a matrix name on it before you actually yeah and so well when you introduce this to the teams around the table.
[00:08:21] How do you find them engaging with it like I'm just wondering whether having this is really providing them with sort of the guardrails the kind of map that they feel like they've been missing like what what are the constituencies thinking about where this might take them.
[00:08:42] I would say Oscar I'd love your perspective to on this I would say I think the first part is with any new area of change it's kind of like that original Microsoft screen saver of stars coming at you right.
[00:08:54] It's all over the place it's height it's headlines it's real use cases it's real challenges and again for that first mover leader of change out there who's been tasked to do AI overall or you know it's an AI's are or it's a.
[00:09:11] content lead or digital shelf lead that's being is actually tapping into AI because maybe that's one of the low hand fruits it's a lot to try to manage so the freight the matrix framework isn't intended to stay theory it's supposed to get actual what it is a way to organize it into what is arguably a go to market strategy loop that we all already had those eight p's were already there just what we use in those eight p's to bring to spin this fly wheel or loop as as we call it.
[00:09:39] And I think obviously I think by making it simple and kind of a fun.
[00:09:43] Catchy way it's helping create a storyline to share with executives or other stakeholders internally to get them to buy in but more importantly.
[00:09:52] Winnie double click into each of those p's that's where like the rubber meets the road right I mean that's where it's like let's talk about presence right and how AI can help from an end in content perspective from creating it to sent you to housing and organizing it to syndicating it.
[00:10:09] To measuring its effectiveness to optimizing yourself for search obviously within the the textual content as well right so before we even get to the measurement part of all of the digital shelf so.
[00:10:20] That's where like I think that's going to be the the greater values that double click in but the first part is trying to organize it ask what what what is your take on that.
[00:10:28] But I think you know I think you're absolutely right the problem that people have is with AI is that there is so much hype and it's really hard to distill.
[00:10:39] Where the truth is so in a way that's why matrix does work very well because you know we are talking about the truth and we are trying to basically break down the hype from the reality right and they also allowed to people to really kind of you know segmented and they say it's like okay I really understand maybe.
[00:10:56] The presence right but I really need to think about through like you know about platforms because platforms find it harder for me.
[00:11:04] To understand because you know I'm still stuck in a cell phone base ab base to world that I don't think beyond it right in terms of all of it so.
[00:11:13] I think it just helps to people to navigate it especially if they see some of the new vendors because we had a lot of the brand leaders kind of reach out to us and like you know what.
[00:11:22] I had just new company popping up I couldn't understand what's their value proposition by immediately started to put them in like an in a little bit of your AI box you know in those eight.
[00:11:33] Right factors in terms of all of it so I think that just helps people to kind of see at this way.
[00:11:40] And you know kind of understand a little bit better what's the value proposition of a lot of the solutions but it's you know I think we had this conversation.
[00:11:47] And we had this conversation in the last few years back you know when we talked about like 20 years ago when digital started we had this wild race into building digital products you know everybody wanted to be the second Amazon.
[00:11:58] We see the same thing with AI at the moment there is a lot of you know software companies coming up with the product there is a lot of venture capital investing in you know AI based product and it's not necessarily all of them are valid some of them are just purely marketing hype so being able to kind of trying to see.
[00:12:16] That building AI companies all about building a company that can actually fit in into ecosystem of brand world.
[00:12:23] That helps to kind of also distill you know what's true what's not true what's useful what's not you know what's useful what's not useful.
[00:12:31] And this is hard for brands right adopting anything new at a brand especially a large brand can be difficult so as you're kind of going through this framework and you're working with brands.
[00:12:41] Oscar what do you think or what are you seeing as the big challenges whether it's legal or IT or data like what are the big things that are coming up and kind of how are you helping brands to navigate that.
[00:12:54] I mean the biggest challenge that AI currently have is that AI basically it's a little bit overhyped right.
[00:13:01] We are basically you can even see you know behind me is going to flash the Nvidia stock which is getting a little bit of a beating in the last you know few weeks.
[00:13:13] But the problem with it is like we almost like one a lit in 20 30 20 40 but we are actually in 2024 and there are some limitations to everything what we have so I think.
[00:13:25] The hype is a thing that had the hype on you know for example the mainstream media on like CNBC where they were basically talking about that AI agents will be here tomorrow.
[00:13:37] You know and it's going to fundamentally change the world you know that's a little bit dying down I think honestly I was so grateful open AI actually kind of released their five step pathway to artificial general intelligence which is basically everything what we would we need to build you know in AI.
[00:13:55] And we are like at the step number one and AI agents on that step number three so I think you know they are basically like resetting the expectations you know what's what's actually doable today.
[00:14:08] I think the last expectation we need to actually reset a little bit is that AI can today replace majority of jobs out there because we see a lot of brands that are basically just you know restructuring the team they are thinking that like Elon Musk they can basically run.
[00:14:24] You know entire company with only 20% of the people this is we starting to see is that this is the reality is actually hitting a lot of the cease with leaders that it's not going to be as simple as not going to be as quick.
[00:14:39] But I think in general the funny thing about AI and what's happening at the moment is that it's also revalidating the IT teams and a lot of the IT teams ironically are actually struggling with AI and there is on for it is because they are conditioned to allow.
[00:14:58] And they are actually ready for that hands on testing and hands on application.
[00:15:06] So AI is not something like you can just lounge and have a check box and basically just forget it.
[00:15:11] It's constantly needs to be eaten.
[00:15:14] Yeah, tuned and sort of monitored and improved over time.
[00:15:19] That's really interesting.
[00:15:23] So essentially you know the company of your name is FirstMover and you've been talking about that a lot.
[00:15:30] I'd like to sort of dive in on that because firstMover can sometimes there are a lot of companies that don't want to be the firstMover they're like no,
[00:15:38] let's let's figure out and then I'll dive in and sort of be the second round.
[00:15:44] So there's like what kind of companies should be digging into this framework and do they have to consider themselves FirstMover's to do it?
[00:15:54] And then secondly, do you view this?
[00:15:58] You're talking about sort of the opportunity for IT.
[00:16:03] Getting good at this is a career-making opportunity I would think.
[00:16:09] But so I'd love your impression on that sort of what companies are, what do you find the mindset is at the places that you're going in?
[00:16:17] And the qualities of their thinking about it that makes them willing to sort of dive in with this framework like what needs to be in place.
[00:16:25] I would throw in. So when we like to talk about FirstMover advantage right now, I mean so we don't talk about ourselves in a third person we actually just happened to call our company the group of people that we represent that we like to be ambassadors for it.
[00:16:40] But I was like, say, I mean obviously a really large enterprise CPG is going to be a different type of FirstMover in some cases then the challenger brand who only goes to market and e-commerce on day one pre acquisition or or scales it.
[00:16:54] And has a much more I do this because this is literally how I grow versus we're dabbling in this and it's still kind of a sidecar effort and we're trying to figure out how to integrate it in.
[00:17:04] So I don't think there's any one profile per se.
[00:17:08] I do think smaller companies, medium companies, especially medium ones and have resources but art so bureaucratic yet they got the agility and the resources typically see them pop up.
[00:17:20] And they're big enough the name is a company that they get you know they speak at events and so you hear about the things that they're testing there also little more willing to be the case study.
[00:17:31] Also for discount or deals or value exchange with some of those solution providers, so you see some of that.
[00:17:36] I did want to.
[00:17:37] Peter that made me think of one story as it just assured aside, I heard from a leader before they did not want it this was way before FirstMover became.
[00:17:46] A community but from a leader that I was when when it said don't we want to have a first mover advantage and said I never want to be number one, I want to be number four.
[00:17:56] And I'm like whoa that's unusually specific why number four because the first person is the disruptor, but they also break the rules and they often get they either they get blamed for the negative part of it and aren't necessarily seen for the positive.
[00:18:11] And the second one looks like someone trying to sneak in the third also but by four it's mainstream and it's okay we can say well others did it you let them do it.
[00:18:21] And I did that is very quick rationale for which which so I don't want to say be I don't want to rename us fourth mover that just feels silly.
[00:18:29] But but but it was that idea of like you don't always want to be first but my point is if nothing else you don't I'm I like the iPhone and I like hitting the new iPhone, but I'm not going to sleep outside the store to get it the day it comes out or the day before it comes out.
[00:18:44] I can wait two weeks and get it the same way and I'll be just fine unless my phone was broken right I might then more urgently going so I would say first mover can be stretched to an early mover versus like an early adopter comes a little bit after that but again some of it is like early mover could be I tested it in one of those peas a few times right it doesn't have to be I completely scaled my business.
[00:19:08] Right by adopting a completely new process holistically and again to ask us point gutted everyone and reoptimize everybody the automated right so I think.
[00:19:18] Part of it though is is is and we have our whole change formula which I know we talked about on on the series before our shared eight factors of change but honestly if those factors of change aren't just for ecommerce and on me they're also for AI or any area of change and so.
[00:19:36] I know you mentioned like the IT team specifically but you're what all functions are starting to realize that is e becomes silent and e commerce.
[00:19:45] And AI is actually underpinning all potential areas of commerce and go to market strategy everyone has a chance it's no longer some brave sales or marketer sales leader marketer who said i volunteer is tribute to go into e commerce.
[00:19:59] Everyone has a chance to be a part of this change and figure out how to implement it for their company in their area and honestly they'll be heralded is heroes because.
[00:20:08] They tried it out like if you're category management maybe there's a way with the data partner to leverage AI to better analyze the data and find those insights if your IT it might be helping connect be the connective tissue between some of the capabilities of not.
[00:20:23] Tech stacking I mean but but i think there's there isn't one profile from a size perspective or a function i think it's just really being as a leader it's.
[00:20:33] Getting aligned to actually test and learn something on a small scale that will cause any problems get the use case study that worked then ask can we scale this little bit bigger.
[00:20:44] And and then so on right and so i think that doesn't sound as sexy but but that is that's how you build change over time and that's how e commerce really kind of came about to right like it's it's just the way that you should approach all things and I think with this.
[00:21:00] Not forgetting the level of change management and education like I mentioned legal right legal needs to educate the org on what you should be asking or shouldn't be asking when you're talking to vendors and then.
[00:21:12] The marketing team needs to know the same questions and needs to understand how I use you so i love that it's a simple formula that you just outline Chris that's like.
[00:21:21] Start small test and learn how we like to approach many, many things in e commerce it doesn't change when it's.
[00:21:28] This new and big and shiny object you should approach at the same exact way but let me kind of actually let's talk about something.
[00:21:37] Kind of related to it is like how people actually approaching the change right what they somewhat we are actually seeing as one of the challenges that we are basically seeing is that.
[00:21:47] The teams are basically and it could be I think would be marketing is they're not taking enough time to really understand this like how to work with AI.
[00:21:56] It's basically it's a little bit like this imagine if you took from 19th century just random people and put them in at one e century cpg that they never working organization they never got onboard at.
[00:22:08] They they didn't allow them to make mistakes and make full of themselves right because we live in a very impatient kind of a culture everything needs to be now I have to be an expert now no matter if I'm going to say the true for not true.
[00:22:22] I'm just going to keep on going right is like we talking about you know as long as you have a conviction in what you're saying you can actually succeed but the problem with it is is with AI is as opposed for example to e commerce.
[00:22:35] AI takes a lot of more iterative work that basically needs to happen like even if you look at the image generation oh my god like in the last two three years we went in from you know what Google was showcasing with image generation into like now we have a a to 16 actually.
[00:22:52] And we have a lot of options different options for image generation right with all of them pros and cons and competing with each other.
[00:22:57] Majority, grog, you know, dali etc and it's constantly changing is like and we have to keep on kind of figuring out what's the latest what's the best because it's also a massive competition at the moment without a lot of investment coming in into AI.
[00:23:11] Everybody's trying to one up each other right during the e commerce you kind of had to kind of wrap your head around it like you had to have this aha moment that you basically can buy something online and it can be delivered to you as opposed to going to the store.
[00:23:24] For me was like a very linear or process AI is a little bit more iterative you know where we actually have to like take everything under consideration.
[00:23:32] And the one thing is that we haven't even touched upon it is what at what type of a social change AI will actually introduce to our world and I give you an example.
[00:23:43] I think next month there is a product coming out for $99 which is basically AI friend and what AI friend is it's on on device AI that you can basically, you know almost interact the same way as you know interactive with the movie in the movie her so like you can have a conversation,
[00:24:00] you know, ask for advice, ask for encouragement etc. Like we don't know ready for that but the point of that is it's like we don't even conceive like what type of a change that's going to actually introduce to potential,
[00:24:14] you know shoppers the potential consumers right like we are not even thinking about this because we're going to probably see this you know within the next four or five years.
[00:24:23] Like in terms of the social fabric how is it actually changing so I think you know like we need to be a little bit more patience you know and a little bit more hands on like you know like this famous thing is like sometimes within CPGs we have too many people that want to lead but nobody really wants to be doing the grass with.
[00:24:39] So grass with work that's where we actually finding up we almost have to step back from the leadership role and it's like I'm just going to sit down today and just like experiment right.
[00:24:49] To get better to kind of understand is like you know how to put those different blocks together so I think that's what's missing at the moment.
[00:24:56] And I think that kind of takes good.
[00:24:58] So I was going to say there's one saying that I came back to me recently that represents what Oscar just said it's kind of an aggressive one but I think it I kind of say it because then once you hear it you cannot can't.
[00:25:07] I'm going to have to believe you.
[00:25:10] No you won't know it's just it's there's that saying that that kind of famous quote that everyone wants to go to heaven but nobody wants to die and that's the like in today's world everyone wants to heaven's benefits.
[00:25:21] What ever heaven you believe in or don't they want the end goal and not all that iterative work and honestly even even when Oscar and I are testing out.
[00:25:30] And I'm like just playing around with mid journey and creating our own imagery like there's a frustration it's like oh I didn't prompt it right or I didn't put that in like and even it's we're getting a little better out and we're not experts perfectly yet no one is but as you're doing like crap that didn't work that well everyone okay I have to do this and do that and so.
[00:25:48] But now the good thing is on a personal level you can fail as many times as you want nobody knows until you show them the final good but we're so used to just jumping from.
[00:25:55] Do the proven task get the proven result that test and learn or or you know or get fail fast like those are nice things to say companies don't always really want to let you do that.
[00:26:07] That's why honestly some of this could be test some of this as you can not with confidential company data anything but test some of this on your own personal.
[00:26:16] Tests home home care planning a trip just so that you get really comfortable with it so that you can already have the synapses connecting when you have to apply some of that type of stuff in turn.
[00:26:29] So the process of doing I mean, sort of this in order to do the test and learn here is some of it costs money.
[00:26:39] You know what do you see companies doing to fund this kind of and it not only cost money but it costs time as you're saying like it.
[00:26:50] Interrating and testing is takes up time it's not just I'm going to do my thing as you were saying so how are you seeing companies figure out there they're correct investment level.
[00:27:01] To to operate these experiments in a way that that sort of makes sense.
[00:27:06] Do you have any examples of that?
[00:27:09] Yes, so I won't name direct name of course.
[00:27:12] But this goes a little bit back to like and some of this sounds like brilliant basics and you're like yeah yeah but again the brilliant basics work that's why 50,000 New York Times best sellers have just reiterated the same leadership principles in 70 different books that have all become the top seller because it's all the same stuff that like Dale Carnegie.
[00:27:29] He told us like almost 100 years ago like it's the same stuff that always worked for all humans back to Socrates and the on right so it's like but that that being the case.
[00:27:40] One of the one of the things is we are kind of hitting and actually one of the things Oscar and I also are working on its parallel to AI pulling is bringing cat man right back into.
[00:27:51] He commerce right because he commerce to date has been focused on pulled the levers measure the leading metrics and you're like got it content search place you know search placement media traffic generation availability reviews all important things but that's just how you grow that's not.
[00:28:09] Why you grow right that's not I did content and media and a sort of and to drive bigger baskets is in way of incrementality or to drive more trips because I'm a snack friend and I want to create new occasions right so.
[00:28:20] It's all those traditional cat man principles that we applied to a mature in store business and often in decline in this thing shifted online that we're not yet fully applying to the online business that is actually also starting to mature for some it's so growing but starting to mature so we have to be a lot more creative so the to your question about.
[00:28:39] Bernoulli five is funny how do you get started actually in some cases brands almost have to could it's like what I've been doing isn't getting me what what I want anymore.
[00:28:48] I've gotten all this funding before I've gotten all these resources all these capabilities it's not that it's not delivery growth, it's not delivery as much growth the way I've designed it so thus I need to squeeze something else out different you do a little something a little differently.
[00:29:01] What might do it?
[00:29:02] Well, I know the hype is telling me AI.
[00:29:05] How do I actually get past the hype to how I contest it?
[00:29:07] And then that's where again, how do we use the AI tools out there
[00:29:13] that are helping me again if I use content?
[00:29:17] Every brand is trying to get accurate, complete content.
[00:29:21] And generally it looks really awesome because now we've got brands involved
[00:29:24] in those designers and we created these beautiful PDPs,
[00:29:28] the beautiful brand stores.
[00:29:31] But have we really measured them for effectiveness?
[00:29:34] Since most retailers don't give you an AB testing capability,
[00:29:37] how do I look at the effectiveness of it?
[00:29:40] While our target SAMs club, they'll measure your content
[00:29:42] completeness on their score curve, but they're not telling you how effective
[00:29:46] it is.
[00:29:46] And all I can normally look at is my what my row as is or my sales look
[00:29:52] like as a result of an update to my content.
[00:29:54] So tools that help use AI to measure effectiveness
[00:29:57] become a way to get more out of the thing I'm already doing
[00:30:00] that I need to show more results from.
[00:30:02] So there's a little bit of that, like I think attention
[00:30:04] to squeeze more juice out of the thing
[00:30:08] that used to generate more juice.
[00:30:10] If we said analogy, but there's also an interesting thing too.
[00:30:14] Like I think of like one use case I know a number of brands
[00:30:17] have been kind of doing, I was just talking to Oscar about this
[00:30:19] really, but not maybe formally or publicly
[00:30:23] is reviewing, I would say auditing the reviews, ratings
[00:30:27] and reviews for insight, not just for content,
[00:30:30] but for your assortment.
[00:30:31] Like what should I do with my renovation next,
[00:30:34] based on what people, and we'd had this for a long time
[00:30:36] that I almost think it went dormant, right?
[00:30:38] We'd had the bizarre voices of the world, the power reviews.
[00:30:41] We've collected all these reviews,
[00:30:43] we had this database of insight, did someone use it
[00:30:46] to get more incrementally, not always actually
[00:30:49] when asking around.
[00:30:50] So what's interesting now is the eat-com team
[00:30:52] or the omni team is now looking at AI,
[00:30:56] is like hey, we got some pretty win-using AI
[00:30:58] to look at what I can control.
[00:31:00] We got some other insights on what the product could be.
[00:31:03] And so now it's like I don't have the funding to do that
[00:31:06] and if I'm an eat-com leader,
[00:31:08] I don't necessarily have the purview
[00:31:09] to change my assortment or my innovation pipeline,
[00:31:12] but I can go back to the brand and say you had this
[00:31:16] real consumer feedback, it's been analyzed at a level
[00:31:19] that we wouldn't have been able to analyze it,
[00:31:21] look at the insight.
[00:31:23] And when we can connect this potential sales opportunity,
[00:31:25] your brand pipeline development opportunity,
[00:31:28] boom, now there's an opportunity to test something out
[00:31:30] through one of the quicker routes to market
[00:31:33] in some of the companies have.
[00:31:34] So and if you're a smaller company,
[00:31:35] I'm probably having more agile way of going
[00:31:37] to market with something a test product.
[00:31:40] So we're seeing a lot of those, I would say it's
[00:31:42] where you're getting pressure to show more results
[00:31:45] from the resources that have already been given to you
[00:31:47] because everyone's coming back around with their 10 cut,
[00:31:50] they want the money back if it's not going to deliver extra growth.
[00:31:54] This is a way to potentially drive extra growth
[00:31:56] and people are willing to see if it is
[00:31:58] because we think AI will bring that advantage.
[00:32:04] Sorry, I was just trying to figure out
[00:32:05] what question to ask next.
[00:32:09] Yeah, same here.
[00:32:10] So we had the budget question which I think you covered,
[00:32:15] but I guess the one piece was like,
[00:32:18] you can't afford not to do anything.
[00:32:19] Like if you could touch on that a bit from the budget standpoint,
[00:32:23] then the other question we had after that was examples
[00:32:27] of the brand striving real impact.
[00:32:29] You started to go into that with the ratings and reviews
[00:32:31] and things like that, but did you have any other specific examples
[00:32:35] you wanted to go into for that?
[00:32:36] Yeah, could we?
[00:32:37] If we could close with some use cases
[00:32:39] that people just to get them new towing, that might be good.
[00:32:43] So in terms of, Lauren, do you want to just have Chris
[00:32:46] or Oscar can tin you just add to that?
[00:32:52] Oscar can build on it.
[00:32:53] I'm sorry, I mean, that's okay.
[00:32:55] Oh no, that's okay.
[00:32:56] I think that's an important statement to say because it'll be a game.
[00:33:01] You can't afford not to statement.
[00:33:04] So Oscar, do you just want to, are you comfortable just jumping in
[00:33:07] with that?
[00:33:07] Something like you were building off of what I just finished?
[00:33:10] Sure, okay.
[00:33:11] So yeah, Chris, the other thing I would want to actually talk
[00:33:14] about is it's also Gen AI, right?
[00:33:17] And what's really happening with all of the different brands
[00:33:20] I're looking to implement Gen AI within their strategies.
[00:33:25] And what we are basically seeing is that especially
[00:33:28] for content completeness, especially for creating contents sets
[00:33:33] for not only the top retailers, like Walmart, Target, Amazon,
[00:33:38] Crogor, et cetera.
[00:33:40] People are starting basically build contents sets
[00:33:42] for other retailers.
[00:33:44] They're actually starting to address also the brands
[00:33:48] that they haven't had the law, but because they didn't have the budgets.
[00:33:53] And really it's being actually look upon as a way to scale it.
[00:33:57] The challenge is that we have is that from a text asset perspective,
[00:34:00] we can actually get it done pretty well.
[00:34:04] Of course, there are going to be some issues.
[00:34:06] Like for example, with legal reviews because AI is very creative,
[00:34:10] but it's not necessarily very well-adopt yet
[00:34:14] to basically create legal approved claims that are very specific.
[00:34:20] Right, think about it is like we almost asking AI to do two things
[00:34:23] to be creative and rigid at the same time,
[00:34:26] which that often creates a lot of those issues with the text assets.
[00:34:30] The images on the flip side, on the product side,
[00:34:34] to be frank based on where we are with all of the different image generation
[00:34:37] generators.
[00:34:39] What we really are doing is we are basically creating different layers
[00:34:42] for those images.
[00:34:44] We are not able to create that perfect prompt
[00:34:46] for a perfect product image,
[00:34:48] because AI has a lot of limitations.
[00:34:50] Like for example, understanding the pre-dimensional relationship
[00:34:53] between objects and it's very hard to generate
[00:34:57] like the exact copy of your actual product.
[00:35:00] The text generation got a lot better versus what we've seen in the past,
[00:35:06] but it's still those type of image production requires a lot
[00:35:10] handling by the designers and our directors
[00:35:13] to be able to actually get it to the right level of production.
[00:35:18] But it can speed up things like, for example,
[00:35:20] text to generation background generation,
[00:35:23] some of the setting generation people generation,
[00:35:25] because AI is very well-versed into generating a lot
[00:35:30] of the human assets.
[00:35:32] So it does help, but I think fundamentally
[00:35:35] where we can actually see the most success
[00:35:37] is to taking an asset that maybe had zero content,
[00:35:40] and suddenly create at least the full-fledged content
[00:35:44] that we can actually push,
[00:35:46] you know, for solstice, for example,
[00:35:49] to into the retail sites.
[00:35:51] The question that I will have is what's going to happen
[00:35:53] for example where the retailers will actually get their
[00:35:59] generative AI at scale that they would say,
[00:36:02] it's like, you know what,
[00:36:02] we can actually produce those continents using AI
[00:36:05] and maybe create a situation as very similar
[00:36:10] to what Chew is doing that all of those continentsets
[00:36:12] are basically thematically,
[00:36:16] basically fit in the store on their own brand,
[00:36:20] etc., so the true indication of the content
[00:36:23] is that going to become the Walmart's
[00:36:25] going to be doing Amazon's going to be doing, et cetera.
[00:36:28] So that's the question where the content
[00:36:31] Gen AI is going to lay,
[00:36:33] is it going to be brand driven, retailer driven, right?
[00:36:36] We already seeing that, you know, for example, Amazon
[00:36:39] is actually using some of the Gen AI into addressing
[00:36:42] some of the content, especially on the, you know,
[00:36:45] third part, marketplace items, et cetera.
[00:36:47] So it's interesting kind of a tug of war
[00:36:50] in terms of like, you know, what's happening on the moment.
[00:36:54] And I think a core message here is that this is,
[00:36:59] this isn't a time to just run into the wild
[00:37:02] and spend everything and hope for the best,
[00:37:04] but you can't afford not to do anything.
[00:37:06] You have to do something, right?
[00:37:08] So pick a P that's important to your business, right?
[00:37:11] One may be even investing on, but without AI yet.
[00:37:16] So you already know you've got some tailwinds boosting you
[00:37:19] and that you bought yourself a little bit of margin
[00:37:21] to try something different, which undoubtedly will help you
[00:37:24] if you're getting some efficiency or some more effectiveness
[00:37:27] out of it and try, right?
[00:37:29] Get some additional stakeholders internally.
[00:37:31] I'm not trying to promise this on behalf of the solution
[00:37:33] provider community, but I bet money,
[00:37:36] I bet my own money on the fact that some of them
[00:37:39] would be happy to do a case study with somebody
[00:37:41] if in exchange as long as you could share it with them
[00:37:44] at an event or share a public case study or parts of it,
[00:37:49] right? Because again, they too want the proof points
[00:37:52] of their developing.
[00:37:54] So you might be able to actually get a better deal
[00:37:56] than it, and you should ask your own partners, right?
[00:37:59] What are you doing with AI?
[00:38:00] Can we test something?
[00:38:01] Even if you get one sound bite,
[00:38:04] one run proof point on one small sub P of these APs,
[00:38:09] you can bring that back to buy yourself another P, right?
[00:38:12] Or buy another sub P. I'm making them all these.
[00:38:15] But it's about as Lauren, as you said,
[00:38:19] it's doing exactly what we did in e-commerce and Ami,
[00:38:23] a little bit faster because we've already been through it.
[00:38:26] We know it worked once again.
[00:38:28] I know that stinks to have to do it all over again,
[00:38:30] but we have to play about follow the plays
[00:38:32] and just be that leader of change, right?
[00:38:35] Because no one else is doing it,
[00:38:37] so you're still going to be like,
[00:38:38] you're going to get all the benefits of the success
[00:38:41] in the long-term impact of learning, failing,
[00:38:44] optimizing, doing better.
[00:38:46] But because no one else is going to do this instead of you,
[00:38:49] but if you don't do it someone might at some point take
[00:38:51] that lead role.
[00:38:52] So I think it's fine to stay colder,
[00:38:55] fine to sponsor a patron internally,
[00:38:58] find a partner that you're already working with.
[00:39:00] There are new one willing to try something,
[00:39:02] get a line that you can share some of that data
[00:39:05] as a case that you obviously have as a personal benefit
[00:39:07] because you might get out there with your own personal brand
[00:39:10] as a leader at that company, else with a pruning
[00:39:12] and thought leadership with retailers too
[00:39:14] that you're doing that kind of work.
[00:39:18] So start in one place, right?
[00:39:20] You don't have to do, you don't have the boil the ocean
[00:39:22] to start with AI on day one.
[00:39:25] But the one thing that we actually love about AI
[00:39:27] is that because AI touches every single part of the organization,
[00:39:32] it also uncover so many like basically
[00:39:35] rotten foundation that people don't have the right data,
[00:39:38] don't have the right processes.
[00:39:40] They have too many silos within the organization.
[00:39:43] So those AI projects are also a massive tweak
[00:39:46] to the way the organization is functioning.
[00:39:49] And basically it's like your annual checkup
[00:39:51] where it's like, hey, your cholesterol is too high.
[00:39:54] You know, maybe your weight is a little bit too low.
[00:39:57] You know, whatever it is, right?
[00:39:59] So those AI projects are really uncovering
[00:40:01] some of the underlying causes.
[00:40:03] And especially I'm very happy about it
[00:40:04] as a massive data geek that those inefficiency
[00:40:07] and the lack of data, it's being exposed.
[00:40:14] So AI will make you feel embarrassed about it.
[00:40:19] But that all good IT projects do that.
[00:40:22] It always exposes where things need to be filled in.
[00:40:27] And that, you know, I was thinking of that
[00:40:29] as you guys were talking, I was thinking,
[00:40:31] you know, once again it comes down to our audience,
[00:40:34] to our listeners, to our community of DSI and FirstMover
[00:40:37] to kind of be the ones to chart the course here.
[00:40:42] Which as I was talking about earlier
[00:40:44] can also be of extremely career-defining journey.
[00:40:50] So what I would certainly, I would leave everyone with
[00:40:52] is go to FirstMover.com.
[00:40:56] So firstMover, MOVR, no E.com slash matrix,
[00:41:02] MAI, TR-I-X.
[00:41:05] So you gotta get all those spellings right
[00:41:06] or if you want to, you of course can always go to LinkedIn,
[00:41:10] Oscar and Chris are very active on there
[00:41:12] and you can say, how the hell do you spell that again?
[00:41:15] But certainly, firstMover.com slash matrix
[00:41:18] and all of this framework, all of it's there for free
[00:41:21] for you to take advantage of it.
[00:41:24] We are so grateful for both of you.
[00:41:27] One for doing the hard thinking around
[00:41:31] how to make things like this approachable
[00:41:34] and organize and productive,
[00:41:37] taking what you learn from your clients
[00:41:38] and putting it into action.
[00:41:40] And then of course, sharing it with the DSI.
[00:41:42] We're really grateful.
[00:41:44] Thank you for having us.
[00:41:45] Thank you.
[00:41:46] Thanks.
[00:41:48] Thanks again to Chris and Oscar
[00:41:50] for the trip through the matrix.
[00:41:52] Before you take your blue pill, go to digitalshelfinstitute.org
[00:41:56] and become a member.
[00:41:57] It will be helpful in your journey.
[00:42:00] Thanks for being part of our community.