The Path to Agentic Commerce Readiness, with Natalija Pavic, Product Marketing Leader at KIBO Commerce

Transcript

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Lauren Livak Gilbert (00:00):

Welcome to unpacking the Digital Shelf, where industry leaders share insights, strategies and stories to help brands win in the ever-changing world of commerce.

Peter Crosby (00:22):

Hey everyone. Peter Crosby here from The Digital Shelf Institute. In this moment, the existential threat is the do nothing paradigm. Well, that little harbinger potential doom is less depressing than you'd think. It's more of a representation of how quickly our topic today agentic AI is beginning to hint at the promise of becoming a real growth channel if you get it right. And the speaker of that teeny tiny doom saying, Natalija Pavic product marketing leader, a Kibo commerce, spends the rest of the pod on smart advice and practical ways to think about a path to take early advantage of this new era of commerce. Welcome back to the podcast, Nat. We are so delighted to have you here. Thank you so much.

Natalija Pavic (01:08):

I'm so happy you were willing to take me a second time. I had so much fun during our last conversation though. Thank you for having me.

Peter Crosby (01:14):

Thank you. And today's topic will be a lot of fun to talk about agentic commerce. I dunno if any of you out there have heard about this thing, I'm guessing, but we're all still trying to figure it out. How do our listeners need to alter their content? Should they build their own ancient, how will it change search? There's so many questions, but you are the woman with so many answers, so I'm hoping you have answers. So let's find out why is agen commerce so important for brands to understand They have so much else already going on, why?

Natalija Pavic (01:49):

Yeah, and I think it's one of those things where if you actually talk to a lot of brands, a lot of them are sitting a sideline trying to figure it out right now. And I think we technologists are doing ourselves a disservice because we like to brand you around new shiny acronyms and just slap on new terms and then assume everybody understands what we're talking about and that it doesn't help that AI agent some of these words in terms of blending. So lemme just break down the concept first I ThinkTech is our two different ideas. So an agent is an autonomous process that is virtual, that executes on behalf of your company or on behalf of your customers. And ai, meaning that it has an AI layer. And usually what we mean these days, when we say AI agents, we are talking about generative AI or LLM large language models.

(02:37):

So typically agented commerce really as it is defined is the use of AI agents for the purposes of commerce where they are LLM or NLP based. So they are generative in nature, generative from the perspective of understanding intent, understanding what customers and employees are requesting, but then AgTech from the perspective of being able to execute within a system what they're asking. So an example would be a merchandising agent that you can go to and say, please generate this product description for me. And it is able to do that using the product attributes within the system and then come back to you and say, how is this before I make these 30 edits? Would you like me? Would you like to review? So I think that's in a nutshell what ent, hopefully I've answered your question.

Peter Crosby (03:20):

You have. I think the second part of that is I think there's the, as you said, there's the creation side of it, but then there is this whole conversation based shopping where agents are talking to you or they're talking to another agent to get things done. And is it both those things together that we should think of as ag, agenta commerce?

Natalija Pavic (03:43):

I think they're both of Agenta commerce for sure. And I do also have to differentiate between generative and predictive ai. So predictive AI is this mode that we've been very used to working in. That's a lot of personalization technologies based on predictive, which is ak. What's the next thing that the customer is going to be asking for? What are the items that are most fit their criteria? What are they searching for potentially? So all of these things are driven by predictive, but generative is fundamentally different because it's not predicting or doing what we call regression analysis in technical terms, which is literally a line of best fit. So funny to me. But generative is, it's generating text primarily, but then it has multiple modes. It can be generating images, generating sounds, speech, et cetera. So it can be generating code, it could be generating analysis, it can be really generating any type of structured or unstructured data. And so when we think of agenta commerce, I think the shopper agent is the one that people are most familiar with, which is the thing that's supposed to help you select and byproducts as a consumer. And it is good.

(04:58):

It's sort of something everybody's talking about. I haven't seen it done right. I get asked this question a lot of times, like, oh, well gosh, who's doing this today? And I always punted back and say, have you had a stellar shopper agent experience somewhere? And the answer is usually no. So I think we're very much trying to figure this out right now. What you are talking about, which is agents interacting with agents is what I would call agent to agent commerce or a to a commerce. So this is a new emerging terminology

Lauren Livak Gilbert (05:29):

That's a new one.

Natalija Pavic (05:32):

So you've got B2C, everybody knows B2B, D two C, B2B two C, right? B two G business to government to age and is something that we're probably heading to in the future. And as much as you have agents interacting with shoppers, you also have agents collecting information on behalf of the shoppers. So right now your website, you're probably getting targeted by other agents who are collecting information about your website. So for example, Chad, GBT, Gemini, Claude Perplexity, they are out there looking at websites trying to answer questions. And so your website also has to be optimized for agents to fine. You find that information. But eventually A to A could be the future, especially in B2B where you have a buyer and a seller where the opportunity for improving the process is tremendous when you introduce agents. That could be sort of the tip of the spear in my opinion, if B2B adopts it or uses it as a leapfrog technology. But I'm meandering now. What was your question, Peter? I don't know.

Peter Crosby (06:42):

No, you got it. You got it. I think part of what we're trying to do, to me all the things you are describing require a future where the ability to hold a conversation is so much more complex than the ability to just put some data on a page. And so to me, the turning point that's happening here is sort of a double-edged sword. Where is growth going to come from as this new era kind of gets its legs and start going, is that going to be a source of growth for my product out in the world? And then secondly, if it is, what are the things I need to prepare for in order to be able to win those conversations? I have my content win out the day for every use case, every context, et cetera. So that's how I'm trying to, for the purposes of today's conversation, think about how this changes the scale and complexity of what we're already doing for the digital shelf for this next round of consumer and shopping behavior or B2B behavior. Does that make sense?

Natalija Pavic (07:52):

Yeah, it does. That's a great question. And I should probably credentialize myself real quick. I do have three AI patents. One of them is in predictive and two of them actually are generative. One actually even the first one is in generative promotions, the second one was in generative personalization, and the third one is in generative content. So just to give you that background. But we've been talking academically, and I think your question is the so wide, and I think besides the fact that SEO is dropping for a lot of companies and consumers are leveraging GPTs for discovery. So you really have to start thinking about a EO or agen engine optimization as opposed to SEO. And that may potentially overtake SEO as the dominant way in which shoppers consume information on your site. So that's one threat to how we do business today. Another threat is personalization.

(08:54):

Personalization has largely been done through predictive. And if I had the option of going and clicking through the site to 2000 times to find the right dress, or just asking Gemini what would suit me best based on my prior shopping experience or based on the use case, what they would recommend, people are overwhelmingly preferring GPT or generative conversations as the main way to interact with technology. And that just speaks to the evolution of complexity in commerce. We went from, hey, you have a single channel, you have an e-commerce store, it's a grid like buying experience to omnichannel, which people are still struggling to execute. So I am a senior director

Lauren Livak Gilbert (09:35):

Of Well said,

Natalija Pavic (09:35):

Yes. Yeah, I'm a senior director of product marketing here at Kewell Commerce. And omnichannel is something that we do really, really well, I think better than our competitors obviously I would always think that, but it's still an area where people still need a lot of help. And that's really merging the store and the online digital channels. That's really where it's focused in. But consumers are moving beyond that. They're moving to commerce anywhere, meaning I want to be able to speak to my phone and have the Tide Pods show up on my doorstep when I need them. I want Amazon to tell me when I'm running out of lotion or whatever it is that I need. So Commerce Anywhere is pushing the boundary of complexity in terms of how vendors and technologists deliver commerce use cases. And so we do a lot of composable, modular headless because of that.

(10:23):

That's really where the frontier is. And we are leaning into agen commerce. Again because of that. It's one way that consumers can simplify how they're purchasing because even though they're ordering from anywhere or they want it to be delivered to anywhere from anywhere, they don't really care. It's sort of like the delivery becomes commoditized. They want one central place to funnel all their questions. And so that's becoming the pane of glass. Agentic is going to become the pane of glass. And that presents a threat to personalization engines because if you think about it, personalization engines today typically own the pane of glass. They own the website, they own the ad, they own the display layer where you get to use predictive to showcase the next best action. With generative, you can't use predictive, you're using generative. And so you can't plug into those personalization engines.

(11:17):

So personalization providers have to rethink how they are providing those services and how they're going to do that in a sort of distributed technology way where they're connected to many things. And I think this is where, not to jump to sort of the next part of the interview, but this is where certain technical considerations, especially if you're evaluating vendors and if you're evaluating technologies that you're going to use, in addition to making sure that they have the right strategy and they're considering all these things that are fundamentally, I think upending the commerce order, they have to also have certain technical considerations, which they're probably not thinking about. And I'm sure we'll dive into that. I'm hoping you'll ask me the question. But yeah, hopefully that answers your question, Peter.

Lauren Livak Gilbert (12:02):

Matt, I have two follow up questions here. The first one, because we're talking about acronyms, it's a new space, there's a lot of things changing. I want to get your opinion on this. So you said a EO was agent engine optimization. I've heard answer engine optimization. I've heard GEO, which is generative engine optimization. I've heard L lmo, which is large language model optimization. In your opinion, I've heard all those. I've

Peter Crosby (12:28):

AO o,

Lauren Livak Gilbert (12:30):

I heard LM FAO as well, let's just throw that one in there. But in terms of those acronyms, all of them are referring, I believe to the same thing, which is how do you get your brand to show up in the answers that the agents are providing? Do you agree with that or do you think that there's differences? Oh, I've also even heard a

Natalija Pavic (12:54):

1. I've heard a IOI don't know why that one bugs me the most. No, that's a good question. They're all referring to making sure that you as a brand are showing up in conversations that customers are having with all of the known GPTs out there, chat, OpenAI, perplexity, cloud, et cetera, Gemini. So they're referring to that. So making sure your brand is being displayed. But here's the thing, the other sort of tip of the spear here is why are customers going to Gemini chat perplexity? So people are saying, well, nobody has a good shopper agent and why should we invest in one? But you're not competing against other retailers, you're competing against the generative providers who are already owning that customer relationship. So if you invest in a shopper agent, you will provide to your customers the experience that they're looking for that they're having to go look for elsewhere.

(13:53):

Because I had an experience where I was looking for an specimen machine, and at the time, I think as a new parent, you're willing to spend whatever it takes to get that espresso. Ivy and GPD had just come out and we were chatting with it trying to figure out what the best espresso machine was, but our favorite brand wasn't showing up in those conversations. And so I was really interested in them, blah, blah, blah. But whenever I would ask it, Hey, what's the best espresso machine? It would never list it. And so I had to go, okay, what's the best list? I had to be very specific, and then I had to go on the mail site and then look at it. And if they just had, this is like me, ping me if you need some help. But if they just had a shopper agent on their site, I would've preferred to use that because in my head, I had already created the brand narrative that I was interested in.

(14:42):

And I think this is the opportunity for brands. They're almost going to have to act like CPGs. All brands will have to think, how can I influence branding story without necessarily owning the pane of glass? And one way is to recapture that terrain and do provide some of the services directly. So people who are already bought into your brand, engaged with your agentic conversations as opposed to going to these open models because the open models will introduce competitors and then you won't have the opportunity to build that customer profile that you could if you were capturing that information through the ENT conversation. And I think there's also something to be said for, I think a lot of people don't know that there's something called context within the conversation. So your agent has a memory, it's not infinite. I think it's just very costly to manage the data center aspect of this.

(15:32):

So they don't remember everything about us forever. Thank God they reset. I know, but purpose has change. Do you know how I found out about this is because I read this story about how, I dunno if you've heard this, some people groom their GPTs to be their boyfriends and girlfriends. So they're like, if you can do, I haven't done it, Paris allegedly, you can do this. But the sad part was that I remember reading the story, they were like, yeah, but then it resets, then I have to groom them all over again. And I was like, oh, hey,

Peter Crosby (16:05):

That's like my marriage.

Natalija Pavic (16:11):

Thank you. Wasn't there a movie like that with Adam Sandler and Drew Barrymore 51 first dates or something like that where 51st dates, 51st dates? Yeah. Yeah, that's what it's like

Peter Crosby (16:21):

My husband. I'm kidding.

Natalija Pavic (16:22):

No, but that's what was talking gt gt.

Lauren Livak Gilbert (16:26):

Okay.

(16:28):

I have a follow-up question here as well. So I like how you're talking about it as the pane of glass. And a lot of brands, excuse me, a lot of consumers want less options. So they want to go to one place and they want to get things recommended. But I don't believe, and I would love your opinion, that SEO is dead because think about this, in-store shopping was the first way of purchasing things. Then the digital shelf came along, the store didn't go away, it just evolved. Now agent commerce is coming along and it's not like the digital shelf and the in-store shopping experience are going away. It's just an additional way of shopping. Not everybody is going to shop through an agent. So how are you seeing all of these different pieces, whether it's in-store shopping, S-E-O-A-E-O, all working together? Because I hear a lot of people saying, SEO is Deb, and I don't think that's really the case. I think it's just now there's an and

Natalija Pavic (17:23):

I mean, that's a good question. And I think the middle path, the road is probably the golden rule here. Probably to your point, nothing ever really dies, and we still use vinyl. We've brought it back. That's my proof point. But when you go to Google, when you think about SEO, we literally mean Google. We call it SEO, but it's really Google engine optimization, and they've got a Gemini front end. So they have Gemini summary responses. It's a matter of time before they, it's really up to them. It's really up to them and their revenue model. And so we're huge partners with Gemini. That's what our agent stuff is built on. And actually, by the way, has the longest context out there. So if you think about OpenAI, they've got what's called 128,000 tokens, which are syllables. And Gemini has 1,000,010 million in research, which means that it can have 10 x the conversations of any other LLM, which is really helpful in especially complex purchases, large purchases, B2B purchases, they're already putting Gemini front and center. So it's really up to Google. It's not really up to us because can they fund it also having they pay, you have to pay for SEO services, you pay for SEM, they're probably not going to kill their ad spend, so they're not going to overtake the whole page, but they could migrate it or merge it into Gemini so that we could have a future Lauren where a EO and SEO merge and they're, again, one thing, right? Yeah.

Lauren Livak Gilbert (19:00):

Yeah. It'll be interesting to see how this all evolves because changing so rapidly.

Natalija Pavic (19:05):

Yes, it is. And I'll leave you with this. I think one of the backings of the technology that people that often gets sort of unspoken is, let's say you have a shopper agent and you have synonym search on your site, which is the most often kind of type of search that you could have. And you ask it a question as an lm, they can understand your question very well, but then it has to go into the commerce engine and search for your product. And if it's backed by synonym and keyword search and the search is not going to be very good. And so one of the things we've done is because a whole search spectrum, so you have no search, some people literally have no search, maybe they feel like they don't need it. You have very simple synonym and keyword search. Then you have the middle of the road, which is what's called AI vector search, and then you have overly personalized search.

(19:55):

So the Algolia, the constructors of the world, they're like, you don't even have to tell it what you're looking for. You say something, it's actually based on your profile. Here's what we think you're looking for. And it's probably more accurate than what you said to us because consumer, you don't actually know what you're looking for. So that's the high end search. But that can be, it can cost a lot of money to get there. And so in the middle of the road, AI vector search is kind of taking all your product attributes and merging them into a vectorized space. So you're putting them into you giving each attribute has a dimension, and each product therefore has a unique vector. And so when you're searching for your term, let's say I search dress shirt, a synonym or a keyword switch would look up red dress shirt, it would look up maybe red dresses as well as red dress shirts.

(20:46):

It would bring up both of those options for you because both of them have those keywords. But in vector space, it would know the difference between red dress and red dress shirt and it would be able to take out red dresses. And so basically my point is if you're not using AI vector search or higher, you're putting lipstick on a pig if you're launching shopper agents. But those are just one of the few technical considerations. I'll tell you more about the landscape in terms of genix solutions as well. But yeah, did I answer your question? I feel like I'm just like, thanks Lauren. Lemme talk about this other thing.

Lauren Livak Gilbert (21:23):

No, no, you're doing great. You answered the question. You're giving us a lot of great knowledge and insights. We know that you go deep into this. So a hundred percent, you definitely answered the question. My follow-up question here is brands are listening to this and they're probably like, oh my gosh, right? To a agent to agent, what happens with the brand? What happens when chat GBT is recommend only eight products and I want to make sure my product is shown? How are you talking to brands about this change? What should they be thinking about? What should they be doing? Because you're taking the brand really out of the loop if you're having an agent to agent conversation. So what is the must do from your perspective on the brand side to be able to compete with these changes?

Natalija Pavic (22:05):

I think this is one of those situations where the existential threat is the do nothing paradigm. We are in a time uncertainty economically, politically, where we need to lean into cost effectiveness. And I think a lot of people are considering ai. I've even heard a customers say, we are not spending on anything. First, the conversation starts with like, we're not spending a dime. And then it ends with we have to buy this because we actually can't reduce our margins without it. And so I think the do nothing paradigm is very dangerous in this specific moment because the people that adopt the AI technology will leapfrog in a way that is tremendous. I think the big hesitation for brands is the predictive nature of these lms, meaning that when you're having a chat bot conversation, it's very like this and this and this. It's very tree oriented with specific responses, and only that specific response will elicit a specific response from the agent.

(23:10):

When you're getting into generative and predictive, there's variability in how they respond much like a human. And so a lot of brands can't get over that. They're like, well, I don't want it to say something different. What if it says something wildly inappropriate? And I think this is where implementation of these technologies is so important. So one of the things we do is we use, I think it's called Google Agent Space today, or it's called Google Agents. And in implementation, it's actually, I always tell my sellers it's infinitely customizable so you can have it. If it doesn't know the answer, say that he doesn't know the answer as opposed to hallucinate, you can define its tonality, you can define tell it what not to say. You can continue to test and launching A POC and then growing from there is probably going to be really a really important tactic for retailers to take.

(24:05):

But I think experimentation right now is really, really key in providing the services because we're entering an era where there's also a lot of competitive proliferation in retail. American retailers have a lot of pressures from international players, from marketplaces, from cheap machines and the team of the world. So there's, there's a lot of threats out there. And the only way forward is to innovate on how you're delivering goods and services to your customers and how you're communicating your brand, the power of your brand to your customers. And so there's a lot of different tactics by I think leaning into digital innovation and experimenting using these technologies so you can figure it out earlier rather than later is super paramount I think.

Peter Crosby (24:59):

So with that kind of, I'm imagining our listeners right now sort of getting that little area of heartburn in their chest. Fear or fear? Fear or kind of like,

(25:11):

Sure, you're a vendor. That's what you would say by my stuff. And I know you're not speaking specifically about kibo, but there's sort of an exhaustion of anxiety and hype and all the reports around AI projects are failing all over the place. And so when you think about what it will take, the kind of things that they need to focus on from a technical consideration, how would you prioritize what's necessary to be foundationally ready play in this area? I don't know whether it's, it's not like you need to get there next week or even, I don't know. I'm not sure what the first recommended timeframe is. Is it six months from now? Are you still going to be fine if you're adopting a year from now? I'm just wondering your sense of what path do you need to be on and what's the most important stuff to think about

Natalija Pavic (26:17):

As

Peter Crosby (26:18):

People try to form their path?

Natalija Pavic (26:20):

Yeah, I definitely started with a little bit of fearmongering, so I have to end with like here's what to do.

Peter Crosby (26:26):

Sorry, I

Natalija Pavic (26:27):

Got No, I have to. No, it's okay. Peter, I get it. I think of your options as a retailer, brand options in terms of vendors out there in three buckets. The two most common buckets that we're aware of are walled gardens. So we know that walled garden AgTech and build your own type of stuff. So the big vendors will say, here are all the tools to build as many agents as you want. For any use case that you need. Caveat, you have to use our entire tech stack. You can use any other tech stacks and you have to be all in with us, but then if you're all in with us, you'll be fine because you can do whatever you want. And that's a very common approach the larger vendors are taking, which is it can be effective, especially like say you're an all Microsoft shop, if you're already an all Microsoft shop and you want to go all in on copilot and you've got a very strong IT team that can start to activate these agents for you, I'm all for it.

(27:28):

Go for it. The challenge becomes is when you are in a more modern headless or composable environment, and a lot of people are turning to point solutions like, oh man, this one Gentech AI solution's, amazing, we should use it. That's all they do. They specialize. And the challenge with that, I'm sort of leading the horse to water here, but the challenge with that is you got this point solution that does it connect to your Microsoft backend, right? Does your Microsoft backend allow you to connect to that point solution? So you start to get into this sort of consideration of does this point solution give me the search that I need, or did I forget to ask about that because I have to have a different search service now I have to connect them. So you start to get into this. Now again, you're on your own.

(28:20):

You sort of on your own to develop and implement point solutions, whereas with the walled garden, you were on your own to actually figure out what you're even building from an agenda AI perspective because it doesn't come ready made for your use case. So that's a good option too, especially if you have a very strong IT department that has a lot of developers that's willing to build these integrations and build all these API connectors. The middle path or the middle approach, which is sort of what we are leaning into is we're primarily a commerce platform, but we are launching an agen tech commerce solution on top of our commerce platform. So it's already built in an integrated into our commerce stack, but caveat is we're adding API connectivity, API, flexibility, resiliency, and modularity to our agenda commerce, meaning that if you want it to use it as standalone, it's possible and have this sort of, you can do both.

Peter Crosby (29:12):

So when you're working with your clients, who are the people that should be in the room for this early adopter motion to be successful? So much of this is breaking down those silos and figuring out what your customers actually need. And so much of it I would imagine is discovery. What's the experience you're trying to create? So who are the teams that you would want to be in the room and committed to it and up for the journey that you would recommend? As we close out here,

Natalija Pavic (29:49):

I think actually, funny you should say that. This goes back to some research that Lauren did, which is fascinating. You're welcome. Call out to use an expert, which is that what should the future teams look like, right? So we're entering into this era. I think for a long time we've had business and IT kind of polar opposites. Business wants X, Y, Z cares about how they're going to achieve those business outcomes and it wants the best, most elegant, beautiful technical system they can get into. And I think one of the challenges with our commerce industry is that we've had two different talk tracks. The commodity commerce platforms have been talking to business. They're like, well, why do you need it? You just use templates, UI narrative sounds great. And then the composable modular platforms have been talked to it saying, oh, you want to have choice, innovation, speed.

(30:42):

And they've had two different talk tracks. What's happened is some customers realize that actually an overly templatized environment slows them down because they end up having to do even more dev customization on top of those storefront templates to get them to look like what they want it to look like. And so it's not all daisies and roses. I don't know what the phrasing is, but business and it have to come together. We have to have a kumbaya moment, especially when we're transitioning from, as Lauren put it, a team of specialists into a team of generalists aided by technology. So we'll see even the future teams that are taking care of this morphing and we'll see less delineation or less harder lines between store and retail operations and e-commerce operations. We'll probably see more of that customer experience, cross border kind of team functioning that's enabled and empowered by their ability to use AI to solve technical problems. So I would like to see both IT and business in the same room making these decisions, and I'd like to get that idea or prerogative of what is the business imperative? What is the thing that you're trying to achieve, what are the outcomes you're trying to get at? And then help it getting there by choosing the right technology because both conversations are really, really important.

Lauren Livak Gilbert (32:07):

Just take you with me now. That was well said. Well said.

Natalija Pavic (32:11):

I'm happy to be your assistant. I'll buy you coffee on your conferences.

Peter Crosby (32:16):

Well, I was going to say, for those listeners who are compelled by your clarity and logic and thoughtfulness on this topic, what's the best way for them to reach out and say, Hey, I got a question for you.

Natalija Pavic (32:31):

My whole name is Natalia Pavi. I go by Nat, but you'll find Natalia Pavi or you'll find Natalia Nat Pavi on LinkedIn, and if you just go linkedin.com/nat pc, you'll get to my direct account. I'll give you guys a link. You can put in the show notes. Feel free to connect with me. I'm happy to discuss or shoot ideas. Yeah. Thank you.

Peter Crosby (32:54):

Awesome. Nat, thank you for joining us. Again, that seems more like more torture than anybody should have to put up with, but we are super grateful that you came to share the outlook on what really is going to turn out to be a transformational additional, sorry, everyone. Additional thing you need to become good at to be able to achieve your growth targets.

Natalija Pavic (33:17):

Honestly, thank you for having me. I'm happy to come back again next year with whatever new thing we're going to be launching because I'm sure it's going to be huge. So thank you so much for having me.

Lauren Livak Gilbert (33:26):

Good. I'm sure there'll be a new acronym and we can talk about it. Thanks so much, Nat.

Natalija Pavic (33:31):

Thank

Peter Crosby (33:31):

You. Thanks again, Nat for the Bracing Reality Check and helpful wisdom. If you want a copy of the organizational report from Lauren that Nat mentioned, download it at www.digitalshelfinstitute.org/omniorg  You'll be glad you did. Thanks for being part of our community.