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Deep Dive

The Future of PIM with Rob Gonzales and Peter Crosby

The product information management (PIM) category is at a pivot point with Forrester, IDC, and Ventana Research all releasing analyst reports in 2021. The report leaders have changed several times in the last 10 years as the evaluation criteria for PIM has been rewritten by analyst firms and buyers, reflecting that a new and volatile market has been emerging. 

In this podcast presentation of a recent webinar, co-hosts Rob Gonzalez and Peter Crosby discuss what has happened over the last decade, and what they predict will happen next.

Peter Crosby:
Hi everyone, Peter Crosby here from the Digital Shelf Institute. On this podcast, Rob and I usually steer pretty clear of talking about Salsify and our product. However, something unprecedented happened in 2021 that makes this moment a particular watershed to discuss where PIM is going over the next decade. Three analyst firms - Forrester, IDC, and Ventana Research, all published their PIM evaluation reports within weeks of each other. Those essentially simultaneous viewpoints give us a really cool array of historical and predictive analysis from the top analysts in the sector. And we did a webinar recently on some thoughts Rob has after spending 10 years in this sector, and thought it might be interesting for our podcast audience as well. Enjoy!

Peter Crosby:
Rob, it might be useful just to spend a couple minutes on sort of how you got into the gardens of Penn. What led you in that direction? What were you doing that brought this problem to your attention?

Rob Gonzalez:
Very accidentally. I was a computer science and math major and went to work for IBM and their advanced internet technology group in Cambridge, Massachusetts, and was there for a bunch of years. And then there was a startup that was literally right across the street called Endeca Technologies and Endeca invented search navigation merchandising for e-commerce. So they implemented the search and merchandising capabilities on Walmart dot com, on Target dot com, on Home Depot dot com, and abroad in places like TESCO and Carrefour and, at their peak, more than half of the internet retailer top 100 were running Endeca. So, anyway, they were right across the street from me, a hot startup in Boston, and I got a job out there in product management. And, the interesting thing about Endeca is that if you go to implement like a Home Depot, Home Depot has a huge product catalog, 8,000 categories at that time.

Rob Gonzalez:
And they were making changes to their site structure every day, because their site merchants with AB tests, things about the attributes, about the images, about the layout of the pages, and a constant search to make the conversion rate of the website greater. And, the big challenge to that was you needed complete product information to support the search and site navigation strategy. And, if you didn't have product content, it didn't work. So a significant effort went into getting the product content and Endeca actually licensed and became the exclusive North American reseller of the Hybris PIM system back in the two thousands. Ultimately Endeca exited to Oracle for about 1.1 billion in 2011 and, a couple years later, Hybris exited to SAP for, you know, somewhere around 1.6 or something like that. So, it's been since, maybe, the mid two thousands that I've been working in this space around this problem.

Peter Crosby:
So there you were with customers that had all of this technology that could drive amazing search. Like I want this faucet with brushed nickel, that's this big and this big, but you didn't have enough data to actually drive the search results. So you had to go spelunking for it, it sounds like.

Rob Gonzalez:
Yeah, and this problem continues today. I remember I was in a customer meeting a few years ago with a customer that makes a lot of the hardware that you find in a Lowe’s or a Home Depot — the washers and bolts and fasteners, and things like that. And they were having an argument as to whether product information changes that much for a washer. You know, it's a washer, is it stainless steel or not like what's it size? And the business team said, look, Lowe's actually just started asking if the washers in that category are dishwashers safe. They didn't used to ask it, and now they're asking it because they found that people that are doing dishwasher repair are searching for “dishwashers safe,” for the washers. So that becomes a new attribute that you've gotta manage. And that type of volatility has, you know, been persistent throughout the years.

Peter Crosby:
Yeah. And so that gives, I think, everyone a kind of a perspective on sort of what was brought to the founding of Salsify and what perspective you brought to it. Rob did just start digging in and something really unprecedented happened in 2021 that makes this moment, this year, a particular watershed to discuss where PI is going over the next decade.

Peter Crosby:
So three analyst firms, Forester, IDC, and a boutique firm called Ventana Research all published their PIM evaluation reports within weeks of each other, three essentially simultaneous viewpoints on this category. It gave us a really cool kind of array of historical and predictive analysis from the top analysts in the sector. And, that had never happened before, at least in my memory. So Rob you, of course being the kind of math detail geek, an analytical and endlessly opinionated man that you are, you had some thoughts about all this and you wrote a piece on the implications of how these reports have evolved over the years. Were you writing that piece sort of from a place of frustration or of warning or of hope? Where did that piece sort of come out of your being?

Rob Gonzalez:
I'm more analytical than I am emotional, I think about these types of things. So it was almost from a place of more academic interest. Looking back now over about 10 years of Forrester PIM waves and, and other type of PIM reports that have been out there in the market, what's changed? And the fact that all three reports came out within a couple months of each other gave us a really interesting snapshot, like what PIM means now across the board across a bunch of analysts that have different types of clientele that have different views on what they care about for the category. Some are more product oriented, some are more business-function oriented. And to see them all come out at the same time, gave us a unique perspective to be able to go back over 10 years and see what's changed. That was, that was the primary motivation I had in spending the time in the analysis.

Peter Crosby:
And so, kind of, so much of this is about where does innovation come from in a category and how does it get driven forward? Did you have a way that you sort of think about that that you brought to this analysis?

Rob Gonzalez:
Yeah. The way that I think about it for this analysis is as it pertains to PIM is Clayton Christensen's model of the innovator's dilemma. And for those of you who don't know, Christensen died a couple years ago, he was a Harvard business school professor. He wrote the innovator's dilemma in the nineties and it tells the story of technological disruption. And the idea of technological disruption is that a new technology is brought to market that is objectively worse than the leader in almost every way that matters, but is better in one small way. And what the new innovative technology does is it takes the part of the market that's cheap that no one cares about and eventually disrupts and replaces the incumbents. And they use examples of hard drives which I wrote about in the article.

Rob Gonzalez:
One of my favorite examples is the mini mill. So it used to be that when you're doing steel processing in America, you would have these really huge steel facilities. And there was only a couple in the whole country. So you would mine your iron ore and other minerals that you needed for the steel processing. You'd put them on trains, you'd ship them all the way to Philadelphia or Pittsburgh. And then you would process them in one place. And there was a new technology called the mini mill. And what the mini mill allowed you to do was to put the seal processing where you mine the ore but you'd process less of it at a time so you wouldn't have to ship it. Now, when they first came out, they produced really crappy products. And the only thing that they could really do is produce rebar and, you know, just really cheap products that the major steel mill manufacturers would not, they don't care about that.

Rob Gonzalez:
They're just low margin goods. They're like, we don't care about rebar. They can have the rebar market, but eventually the mini mills became good enough that they bankrupted all of the large steel mills. So, you know, that's basically it you come up with a product that has some advantage, but it's worse than every other way. And so for PIM, by even 2012, you had Informatica, you had SAP Hybris, you had PIMs like EnterWorks or inRiver that had been around for a while or Riversand. And these were systems that had significant enterprise capabilities for data management. Now, when new PIMs came on the market with different points of view, Akeneo, Salsify, the PIMS had a totally different perspective. They were worse than Stibo in every possible way in 2012, except that they were in the cloud, they were built for business users. And in Salsify’s case, they were built to publish, right? So they were better at publishing than anybody else. They were worse at data management. They were worse at workflow. They were worse at systems integration. They were, you know, know they were worse in every possible way, but they were better at, you know, this one thing, which was managing multiple different versions of product content for each channel.

Peter Crosby:
Who were the customers of that? Who was suffering from that pain? I mean, retailers at the time really were kind of only going to one place, right? Their website. It was, so it was sort of the brand manufacturer kind of pain, right?

Rob Gonzalez:
Yeah, that’s right. There weren't, you know, PIM in 2006 was mostly built for retail, you know, so if you're Informatica or you're Stibo and you're selling PIM in 2006 you're selling it to a retailer. I mean, even today, most of Stibo’s market is retailers, right? You weren't selling to brand manufacturers that much. So if you went to, you know, Johnson and Johnson in 2010, and you asked them, you know, where do you store your product content? They were just starting to think about that. They didn't have an enterprise system that was standardized. And that's true of basically every major manufacturer if you go back then because manufacturers were not doing active digital merchandising of their products, they didn't have any need to. Now, what changed was the rise of Amazon, the rise of eCommerce endpoints as important marketing and merchandising destinations. And all of a sudden it became important for manufacturers to get all their content at one place so that they could get it to a retailer. And that use case was not a use case that used to exist. So there was a change in the market dynamics that, first of all, expanded the PIM market to include manufacturers where it really didn't include manufacturers before. And second of all added this multi-channel dimension to it, which didn't exist before.

Peter Crosby:
Well, if you can, just before we sort of go into this journey of PIM, just, just give a quick definition from your point of view what a PIM should be that you enter the marketplace with 10 years ago. Like, what did you want it to do?

Rob Gonzalez:
I'm gonna say that, if you think about, forget the history of PIM and forget the future of PIM and forget the players. You need a place to work on your product content, right? It's like, how are you going to display and merchandise your product? What is the package of information and content that gets in front of a customer? You need a way to be able to store that and organize work around it and, and so on and so forth. That's, it's basically, collaboration around product information, images, attributes, romance copy, reviews and ingredient lists, like all the stuff that's around the product. These days you might call it a product cloud. You know, Salesforce has the sales cloud, their CRM system. The center of truth per customer data and customer data is not just, you know, name, email, address, phone number, it's a ton of stuff around the customers. It's the opportunities, it's the tickets that they've filed, it's the usage of the product. It's just, it's a really holistic 360 degree view of everything that you need about the customer. I think analogously, if you look at PIM that's what PIM should be. PIM should be a thing that masters a 360 degree view of everything surrounding a product that's required to collaborate around the product internally within your company, and then also get that product to market in a way that's compelling to the end buyer, the end shopper.

Peter Crosby:
So if, if it's getting all that data into one place, ready and set up to match the requirements of every channel and then out to that channel, and then hopefully over time, a continuous sort of cycle of improvement to drive better business. That's kind of the core of how you guys were thinking about PIM as you got into the business, right? And, so, when you think about, you came into business and the analyst reports had been covering, at that time, were covering a very different PIM market. And when you were coming in, what are the shortcomings, according to that definition that people like brand manufacturers were seeing when they were trying to implement those PIMs to solve this problem?

Rob Gonzalez:
Yeah, the traditional PIMs, PIM as a category came out of master data management, it came out of a special specialization of master data management. MDM is effectively you're, you've got data about a type of information domain like customer or sale or product or, or whatever. There's a whole bunch of different domains of data. They live in tons of different systems within your company. And the idea of master data management was, you integrate all the data into one place in a standard schema, so that you can have a single source of truth that you would trust. And then you would make that source of truth available to other systems downstream that would need it. So the use case is effectively integration into a central point and standardization, which they, you know, they call normalization of data, data space into a standard schema for ease of integration downstream

Peter Crosby:
Sort of golden records, right?

Rob Gonzalez:
Golden records. Yeah. So PIM was straight up an IT system. And so if you're, if you're looking at, when we were selling Hybris in the two thousands, we weren't selling Hybris to the, you know, the merchandising team. You know, we weren't going to the chief merchant or the chief marketing officer and saying “PIM!” you know, this is a place that you need to do your merchandising. This is, you know, you need your romance copy to be in this thing. That's not what we were doing. We were going to IT, and we were treating it as very much a data integration play. And, you know, we were looking at it from the point of view of the search scheme of the website. So it's, we weren't looking at romance copy. We weren't, you know, we weren't looking at, at everything you need to merchandise a product. We were really just looking at it as integrating lots of different attributes from lots of different sources, getting it into the site scheme-up of the website and then get it live. So, that was, I mean, that's what PIM's background was. It was an IT system that was mostly about data consolidation and data normalization.

Peter Crosby:
And the analyst reports reflected that, right? Like those were the standards upon which companies were judged as, are you a successful PIM or are you not, right?

Rob Gonzalez:
Yeah. If you're Forrester and you're 2012 and you're doing a PIM wave, and you're talking to people that have bought PIM you're straight up talking to IT, you know, full stop. There's almost no business leaders out there that care that much about the problem.

Peter Crosby:
And along comes the digital shelf, right? And so that started to, probably, sort of what rounds of reports did you start to see that use case start to creep in?

Rob Gonzalez:
So there was a Forester analyst named Nazare who did a wave in 2015, and he coined the phrase Walt Forester called product experience management. And that was the first time I had seen indication that the PIM market was evolving from data integration and data management into something else, something that was more consumer facing, something that's more business user oriented. And at first, what he was implying by it was that the PIMs are expanding to include other content. So, you know, in 2009, I think Hybris was one of the first PIMs that even had images in, but the DAM capabilities were expanding so that you could have more digital assets alongside the product attributes. You started in 2015 to see updated user interfaces. You know, inRiver, one of the older PIMs, they introduced a new UX right around then that was more business user oriented .

Rob Gonzalez:
And so you saw, saw some of the PIMs that were showing up in the wave as, moving a little bit more towards the business and away from just strictly being IT systems. So that was the first indication in 2015 where things started changing.

Peter Crosby:
And that’s a pretty big change, right?

Rob Gonzalez:
It's a pretty big change. Yeah.

Peter Crosby:
For Forester to start to do that. I mean, that suggests Forester and, we've seen it in other reports too, but mainly Forrester, they were and are the first analyst firm to really focus on PIM. IDC joined a little later. When you think about, during that process, you start to see it open up. Now that we're getting to present day, what kind of features are now considered by the analyst firms that were not required in years past?

Rob Gonzalez:
Well, they came little by little. So in ‘15, you started to see more emphasis on the business user usability. You started to see more emphasis on support for images and what not. And then in 2017, the PIM analyst was a guy named Bruce, Bruce Eppinger for Forester. And he made a pretty large change, which was, what's the point of storing product data if no one ever sees it? That was kind, that was kind of his inspiration, which is, it seems so obvious when you say it like that. If you've got, you know, it's like if you cut down a tree in a forest and no one's around to hear it doesn't even make it sound, it’s like if you master a perfect golden record in an IT system somewhere and it never shows up on Walmart dot com, does it even matter?

Rob Gonzalez:
So that was his point of view. So he started, for the first time, looking at can you publish and get it in front of end users? Do you have workflow and user experiences that bring in multiple business teams? Do you have a user group system that is amenable to managing multiple business teams? So he started bringing in a lot more of the business of PIM and publishing it out there. I mean, you saw the leaders change quite a bit between ‘15 and ‘17, for that reason. You saw companies like, Salsify for example, we were just outside the leader quadrant in ‘17. But, you know, the fact that we showed up for the very first time and showed up just outside the leader quadrant really just had to do with the emphasis that they had on syndication and on getting the content in front of the end user. At that point in ‘17 if you were gonna rate us and on like enterprise PIM capabilities, like role in permission security on every aspect of the system, the ability to roll out globally, the ability to scale to large product sets. All kinds of stuff that does matter.

Rob Gonzalez:
We, you know, we did relatively poorly on most of those things. But the emphasis on the new business user capabilities helped us do pretty well. So ‘17, there was a big shift in the way the analysts were looking at it. And then there was also a big shift in the way that the market started buying it. In RFPs, we started seeing that there were at-bats available for the up and comers, you know, the Salsifys, the inRivers, the Akeneos, versus just the old enterprise standbys, the skis and Informatica that were always there. So the buying patterns were starting to move quite a bit around that, too.

Peter Crosby:
And so 2021, I mean, it's not like the need to do really sophisticated data modeling and all those things have gone away. You still need to be a great data foundation. Is that fair to say?

Rob Gonzalez:
Yeah, it is fair to say. What's interesting though, is the PIM market has expanded significantly, right? So the PIM market used to be really retailers and retailers because, you know, especially if, if you're Walmart, if you're Home Depot, if you're Target, you carry so many different products from so many different categories that the data modeling requirements for your PIM are significant. They're like every single data modeling requirement for every single category in the entire world, now that the PIM market's expanded to include manufacturers and there's way more manufacturers and distributors than there are retailers. There's tens of thousands of manufacturers in North America that are, you know, big enough and have large enough product portfolios to benefit from a PIM; there's only, you know, a couple hundred retailers. So, the adjustable market for PIM in this new world has really expanded quite a bit.

Rob Gonzalez:
And what that means is that a lot of the data modeling capabilities that seemed critical to PIM 10 years ago, actually aren't so critical. They're still critical in specific use cases, but they're not critical universally in the way that PIM was defined before. I mean, I'll give you one example in automotive aftermarket parts. There's a data model challenge where you've got a part that might apply to the 2010 to 2012 Corollas that are, you know, the standard not automatic, right? And like the, you know, so there's the relational aspect where you're, you've got this part, but it applies to the very specific year, make model configuration of a vehicle. And that's a, that's a, you know, unique data modeling problem. And, you know ,in retail that shows up because every retailer has some, some amount of automotive aftermarket section, somewhere in their store. But it doesn't show up if you are a CPG company, if you're an apparel manufacturer, if you're a beauty manufacturer, if you're a dental equipment manufacturer, it just, doesn't, it's not a problem that you have.

Rob Gonzalez:
So what's ended up in the way that the analysts are looking at it is they've acknowledged that the PIM market is huge. And by virtue of it being huge, not all of the problems are distributed universally. And, in a lot of ways, what Amanda, the current Forester PIM analyst has done is she's simplified the criteria significantly because of that. PIM is no longer like a checklist of here's a thousand data modeling capabilities and a thousand integration capabilities that you have to have; it's instead focused a lot more on business outcome. And so, you know, there's some categories for which PIMs are gonna be better than others PIM by PIM for that reason.

Peter Crosby:
So really when, you know, folks on this webinar out in the world are starting to think about what's the right PIM for me, really starting with what problems are you trying to solve? What are your use cases, what's critical for you to meet your business growth goals and your competitiveness goals when it comes to showing up on the digital shelf if multichannel, omnichannel experiences are important to you.

Rob Gonzalez:
Yeah, that's right. Yeah. I mean, and some of the old school players, Informatica as just an example for huge companies, you look at like a 3M, for example, just a huge company. Informatica can play a huge role in data integration, right? They’re still talking about hundreds of systems spread out across the world. You still need to solve that problem. It doesn't need to be solved in your business oriented PIM. It can be solved in like an ETL solution that feeds into the PIM. And so the world has just gotten complicated in a way that I think blows up the category quite a bit. And what the three analyst reports are doing is they're trying to redefine and recenter it in a different place than it was centered 10 years ago. 10 years ago, eight integration normalization. Today, business user tool for mastering really compelling consumer experiences. And that's a massive shift over 10 years.

Peter Crosby:
I mean, that’s really quite a journey for what had been previously a pretty relatively quiet tech category before this evolution started over the last several years. I'm guessing the next 10 will be just as interesting. You know, when you think about it the whole session is titled “Future of PIM’ so I wanna make sure we get to that. What are you seeing or what are you hearing from the analysts as being the core capabilities that will be added to the PIM category, expanding the PIM category over the next decade? I mean, besides NFTs, of course, because that's a given.

Rob Gonzalez:
That's right. We need to do an NFT on the podcast.

Peter Crosby:
Oh, totally.

Rob Gonzalez:
So the one that they're all trying to understand how it applies to PIM is artificial intelligence and —

Peter Crosby:
That's a big thing. What is AI, right?

Rob Gonzalez:
Yeah. I mean, what is AI? What's the rules? So the use cases that are in PIM right now for AI are relatively narrow. So there's a couple PIMS that integrate with Amazon that has a tool called Rekognition. It's spelled with a K in the middle so R E K, it's just, this is one of those like ‘too cool for school’ spellings. What Rekognition does is, if you send an image to Rekognition, it gives you all kinds of metadata tags about the image. So if there's a sheep in it, it'll say, “oh, tag it with a sheep.” Google has an API that does something similar. And so what you see PIMs doing is they're taking advantage of off the shelf APIs for categorization and metadata enrichment and integrating them natively into the PIM. Being in the cloud makes this really easy.

Rob Gonzalez:
The analysts are looking at patterns like that and trying to figure out, like, is there like a type of AI application in PIM that’s gonna be the next thing? You know, the last 10 years have been about business user, business users coming into the system workflows, user experience and so on and so forth and about publishing, you know, can you get those experiences in front of consumers?

Rob Gonzalez:
You know, AI's gonna play some role in the next 10. What is it? My personal view is the thing that's gonna matter the most is automation, full stop. If you're a large, I mean, hell, if you're a small manufacturer these days you're selling through a huge variety of channels. Channel fragmentation is crazy. There's all the traditional retailers, there's your direct to consumer site, there's social commerce. And now, you know, coming up now is all the quick commerce players, which are gonna be selling every single skew in the universe delivered to your door in 15 minutes, the DoorDashs, the Gopuffs and Gorillas and Deliveroos and Uber eats and whatnot in the world. With that type of channel explosion, even if you've got 10 products your challenge is every single one of those websites looks different so that they require different content. Every single one of those websites evolves at their own rate so they're making changes to their schema differently. And every single one of those websites requires constant monitoring. And so even if you've got 10 products and you've got 500 websites, things are changing on those websites in ways that are unpredictable. You've gotta have some way to monitor those changes. And then you've gotta have some way to automate the responses to those changes.

Peter Crosby:
And, and part of that, Rob, is that every one of those changes represents a potential merchandising opportunity that if you act on it first, you win the SEO game, or, you know, if you're faster than your competitors at delivering on that, that new attribute that could make a difference, the sooner you do that for the importance ones that matter, the better. So being able to surface those things and sort of choose among them, I would imagine, would be potentially a rich opportunity for automation.

Rob Gonzalez:
Yeah, it's huge. I mean, we look at the example earlier with the washer and dishwasher safe for Lowe’s, and, you think, how did you monitor that and how did you know it? How fast were you to respond to it? And then the really interesting thing is, could the response have been automated for even some percentage of your portfolio? Right? Maybe dishwasher safe is text that exists already in the description. So that, you know, the system can figure it out on its own. So I think that there's a trend where the growing volatility and complexity of the market requires automation and requires that the machine be able to complete a lot of responsive tasks, independently, or at least semi independently. So I'm kind of seeing the beginnings of it right now and think that if you're gonna apply artificial intelligence to a problem in PIM and have it really make a big difference, it's gonna be helping to scale the top level responses to all of the changes that happen in the market.

Peter Crosby:
Yeah, and I think when you up level that to the real business driver here is that one of, one of the business drivers, I think, is that as digital in this time of COVID, as digital takes on a much bigger part of the revenue pie, and certainly influences a really big part of the revenue pie, then a lot of financial eyes are turning over to the work on e-commerce channels and social commerce, et cetera and going, how do we do this sustainably? How do we do it profitably? And where does the growth come from? And if you do believe that the product page, wherever it might live, that that content, that experience drives discovery and confidence so that you get conversion. If you believe that, then getting good at that across as many of your channels as possible at scale, is the driver of growth. And ultimately one of the drivers of growth and ultimately profitability. A: Do you accept that thesis? And if so, it feels like things like automation and making sure that teams and companies can collaborate seems like a rich area to help in that process.

Rob Gonzalez:
Yeah. Yeah. I mean, absolutely, I agree with that. I mean, you look at, I like to joke with companies, I say, “what gets more eyeballs? Your last TV ad or your Amazon product detail page?” Right? You know, I think US TV viewership penetration went below 60% recently. So it's, you know, more than 40% of US households don't even have cable TV. They got Amazon, they all have Amazon. So yeah, these product detail pages are the, you know, the key branding discovery value and communication mechanism of these companies. So, you gotta take it seriously. It's a big part of the way that the business works. And, you said something in the middle of there that's really interesting, I think is also part of the future of PIm. PIM used to be about one company within their company organizing their data. PIM has become, due to the publishing aspect, that was highlighted in the IDC market scape in the Forrester PIM wave and in Ventana’s value index.

Rob Gonzalez:
The publishing is all about connecting data between companies. Getting the data that you organized yourself within your company to Walmart, to Grainger, to anybody who might be merchandising and selling the product. And as soon as you do that, PIM is not about one company. It's about two companies collaborating. Now what's happened is that those connections have become two-way in a lot of cases. So Walmart, for example, if you send Walmart data and a human at Walmart reviews it, and they reject it, feedback can automatically come back from Walmart's system back and show up in a workflow in the PIM. So, all of a sudden, you're talking about workflows that involve humans, or robots, or both between two different companies collaborating across the supply chain. That's a totally different problem than historical PIMs, so that collaboration between companies to deliver excellent consumer experiences, right at excellent commerce experiences, wherever they're seen, that collaboration is going to become increasingly important.

Peter Crosby:
Success of both and the best experience for the consumer.

Rob Gonzalez:
Yep. And also, I mean, that just for me, goes to where AI plays in automation. Is that the scale of that collaboration can become very significant, right? It's gotta be done without just chat and email. It's gotta be somewhat automated. I just look at where Walmart has changed over the last 10 years, just to, just to look at Walmart as a retailer that's really evolved quite a bit. 10 years ago, the merchants were fully in charge of buying the products for every single category. Now, a lot of the buying decisions are influenced heavily by online product performance. So if a product wins online, it could be, you know, almost automatically by algorithm moved in store, or at least put on the consideration list to move in store. And a lot of that automation and intelligence is replacing previous human judgment that used to be in there. And so, the more complicated and volatile and large this problem gets and the more collaboration that happens across companies, the more you're gonna need a system to organize and to help automate some of the responses. So that's where I think the future of this is. Instead of, you know, individual inside of a company, you're talking about like a product cloud where companies are collaborating in real time and where there's a tremendous amount of automation driven by AI.

Peter Crosby:
Thanks so much to Rob for having Big Thoughts. If you would like to see or share the original source webinar, we have the link in the show notes. Thanks for being part of our community.