Our Shoptalk 2025 Tech Preview Podcast!

Summary

Omni Talk Retail - Episode Summary: "Our Shoptalk 2025 Tech Preview Podcast!"

Release Date: March 17, 2025
Host: Omni Talk Retail (Chris Walton and Anne Mezzenga)
Description: In this episode, Omni Talk Retail hosts a series of industry experts and thought leaders to provide an in-depth preview of the latest technological advancements and trends set to shape the retail landscape at the upcoming Shop Talk 2025 event. The discussions focus on AI-driven solutions, omnichannel data integration, marketplace optimization, and intelligent data platforms, offering valuable insights for retailers and brands aiming to stay ahead in a rapidly evolving market.

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Overview

The "Our Shoptalk 2025 Tech Preview Podcast!" episode features interviews with eight key leaders from the retail technology sector. Each guest shares their company’s innovations, explores current challenges in the retail industry, and highlights what attendees can expect at Shop Talk 2025. The conversation emphasizes the transformative role of AI and data analytics in enhancing consumer experiences and optimizing retail operations.

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Guest Interviews

1. Vinod Ramachandran - CEO, Big Sur AI

Timestamp: [01:32]

Key Points:

• AI Platform for Retailers: Big Sur AI offers a comprehensive AI platform tailored for retailers and brands, featuring specialized AI agents for sales, marketing, and data analysis.
• Agentic AI: The platform’s agents act as virtual employees, automating tasks such as personalized sales interactions and rapid content creation.
• Scalable Solutions: Enables smaller retailers to leverage advanced AI technologies without the extensive resources typically required.

Notable Quotes:

• “We are building the only AI platform for retailers and brands that they will ever need.” — Vinod Ramachandran [01:57]
• “Our agents act together; the AI content marketer looks at all the conversations that users are having with the brand...” — Vinod Ramachandran [07:06]

Insights: Vinod emphasized the importance of agentic AI in democratizing access to advanced technologies, allowing retailers of all sizes to enhance their operations and compete with larger players. He highlighted the immediate impact of Big Sur AI’s solutions on conversion rates and marketing efficiency.

2. Sne Parmar - CEO, Lucky

Timestamp: [17:11]

Key Points:

• Omnichannel Data Integration: Lucky partners with major retailers (e.g., Sephora, Ulta) to integrate inventory and attribution systems, providing brands with real-time data insights.
• Enhanced Store Locator: Offers brands the ability to display real-time product availability, improving customer satisfaction and sales.
• Marketing Attribution: Enables brands to track the effectiveness of their marketing campaigns, linking online actions to in-store sales.

Notable Quotes:

• “Lucky is here to help you increase retail sales.” — Sne Parmar [19:11]
• “We have a solution to how you can grow retail sales... making your business AI ready.” — Sne Parmar [22:20]

Insights: Sne highlighted the critical role of data transparency between brands and retailers. By providing accurate attribution and real-time inventory data, Lucky helps brands optimize their marketing spend and drive higher sales performance.

3. Mark Tack - CEO, Lilly AI

Timestamp: [27:50]

Key Points:

• Product Content Optimization: Lilly AI focuses on aligning merchant product descriptions with consumer search behaviors to enhance SEO and paid campaign performance.
• Relevance and Accuracy: Utilizes a large, proprietary dataset to ensure high accuracy and relevance in product content across various channels.
• Performance Metrics: Demonstrated significant improvements in PDP visits and conversion rates through AI-driven content strategies.

Notable Quotes:

• “Accuracy is really important, and Lilly absolutely tops that game.” — Mark Tack [29:53]
• “The consumer first nature of what we do at Lilly...” — Mark Tack [32:37]

Insights: Mark emphasized Lilly AI’s unique advantage in maintaining a vast, clean training dataset, which ensures superior accuracy and relevance in optimizing product content. This approach helps brands achieve better visibility and higher conversion rates across multiple search platforms.

4. James Toyakov - CEO, Syrup

Timestamp: [56:46]

Key Points:

• AI-Driven Inventory Management: Syrup provides AI-based forecasting and decision support for inventory allocation, replenishment, and product assortment.
• Complex Data Integration: Combines first-party and external data to deliver comprehensive demand forecasts.
• Retail Media Integration: Enhances retail media strategy by aligning it with inventory decisions, driving better marketing ROI.

Notable Quotes:

• “Our mission is to let the machines do the work that is repeatable.” — James Toyakov [46:24]
• “We see ourselves as the foundation for AI.” — James Toyakov [74:52]

Insights: James discussed how Syrup leverages AI to address essential inventory management challenges, reducing return rates and optimizing marketing spend. By integrating inventory forecasting with retail media strategies, Syrup helps retailers maximize profitability and operational efficiency.

5. Ethan Chernovsky - CEO, Placer

Timestamp: [57:18]

Key Points:

• Location Analytics Platform: Placer uses machine learning and AI to analyze retail visit data from millions of devices, providing insights into consumer behavior and market trends.
• Single Lens Data Integration: Combines first-party and external data sources to offer comprehensive benchmarking and context for retailers.
• Cross-Functional Utility: Supports various departments, including real estate, marketing, and merchandising, with actionable insights.

Notable Quotes:

• “It's reliable, it's a single lens, and it's accessible.” — Ethan Chernovsky [60:30]
• “Retailers are wondering how to interpret consumer changing patterns, and we help bridge that gap.” — Ethan Chernovsky [67:45]

Insights: Ethan highlighted the importance of unified data sources for accurate benchmarking and informed decision-making. Placer’s platform enables retailers to understand and respond to market dynamics effectively, enhancing their competitive edge.

6. Mark Tack - CMO, Treasure Data

Timestamp: [72:40]

Key Points:

• Intelligent Data Platform: Treasure Data combines customer data with Gen AI, machine learning, and personalization to deliver intelligent business insights.
• CDP Leadership: Recognized as a leader in the Customer Data Platform (CDP) space, integrating both real-time and batch data for comprehensive insights.
• Performance Enhancement: AI-driven personalization leads to significant increases in conversion rates and revenue growth.

Notable Quotes:

• “Treasure Data is number one in personalization and decisioning compared to all 17 vendors.” — Mark Tack [76:34]
• “AI is as good as your training data, and we have the largest clean training dataset in the world.” — Mark Tack [35:01]

Insights: Mark emphasized Treasure Data’s role in advancing customer intelligence through an integrated platform that supports both real-time and batch data. By leveraging their extensive dataset and advanced AI capabilities, Treasure Data helps businesses create personalized experiences that drive growth and profitability.

7. Alex Hazy - GM and CRO, Miracle

Timestamp: [85:03]

Key Points:

• Marketplace Enablement: Miracle provides software solutions for retailers to launch and manage online marketplaces, similar to Amazon’s model.
• Retail Media Integration: Integrates marketplace functionality with retail media, enhancing advertising opportunities and revenue streams.
• Vertical Specialization: Focuses on specialty retailers across categories like consumer electronics, health and beauty, DIY, and footwear.

Notable Quotes:

• “Retail media has this, like, is at this kind of like Frostian road diverged in the wood.” — Alex Hazy [91:59]
• “We help the retailers capture that opportunity.” — Alex Hazy [86:21]

Insights: Alex discussed how Miracle’s platform simplifies the creation and management of online marketplaces, thereby expanding retailers’ product assortments and enhancing their retail media strategies. This integration allows for a seamless approach to increasing traffic and monetizing advertising efforts.

8. Raj Ramanand - CEO, Signified

Timestamp: [95:36]

Key Points:

• AI-Driven Fraud Management: Signified utilizes AI and machine learning to minimize fraudulent transactions while increasing approval rates for legitimate customers.
• Instant Refunds: Implements technology to offer instant refunds, enhancing customer satisfaction and loyalty by reducing return processing times.
• Mission Control Dashboard: Provides comprehensive oversight of return reasons and customer behavior to identify and mitigate return-related losses.

Notable Quotes:

• “Instead of focusing on using AI to just protect the bad and help retailers reduce their fraud, what if we could turn that around and use AI for good...” — Raj Ramanand [98:37]
• “We have a chat layer that sits across the whole CDP, so in theory anybody can access and use the CDP now.” — Raj Ramanand [81:43]

Insights: Raj highlighted the dual benefits of AI in both reducing fraud and enhancing customer experiences through instant refunds. By providing a mission control dashboard, Signified empowers retailers to gain deeper insights into return patterns and consumer behavior, allowing for more strategic decision-making and operational improvements.

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Conclusion

The episode of Omni Talk Retail’s "Our Shoptalk 2025 Tech Preview Podcast!" offers a comprehensive look into the innovations and strategies that leaders in the retail tech industry are deploying to navigate the evolving landscape. From AI-driven sales and marketing solutions to advanced data analytics platforms and intelligent fraud management systems, the discussions provide valuable insights for retailers and brands preparing for Shop Talk 2025. The overarching theme underscores the pivotal role of AI and data integration in enhancing consumer experiences, optimizing operations, and driving sustainable growth in the competitive retail market.

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Note: For detailed questions, connections, and further engagement with the featured companies, listeners are encouraged to attend Shop Talk 2025 or reach out to the respective executives via their provided contact information.

Transcript

[Ann]

Foreign.

[Chris]

Hello, everyone, and welcome to Amitak Retail's Shop Talk must see tech LinkedIn live session. Chris, we have been doing quite a lot of promotion to get ready for Shop Talk over the course of the past few weeks.

[Ed]

You put ad. Well put.

[Chris]

Yes. You've been outside in negative temperatures talking about all the events and opportunities at Shop Talk. I've done my best and yet still incredibly terrible acting impressions. And as a result, we've been getting a ton of comments from all of you from our followers reaching out, asking us what we recommend they find out about what technology they look at while they're there and just kind of what to put on their list for the show. So, Chris.

[Ed]

Yes.

[Chris]

To simplify things for our Omni Talk fans to go above and beyond for everybody, we brought together in one digestible podcast session partners that we think you should have on your list. Right.

[Ed]

That's right, Ann. Yes. We're going to take everyone watching and listening later through a series of interviews with the folks we believe are the quote, unquote, must see technology providers at next week's Shop Talk so you can have all the info you need to plan your booth stops, your meetups, your sessions, and more. So with that, and I think let's get to it. Let's get to the first interview and let's get this party started.

[Chris]

All right. Joining us now is Big Sur AI CEO Vinod Ramachandran. Vinod, it's so great to have you. Welcome to omnitalk.

[Vinod Ramachandran]

Thank you. Thrilled to be here. Anne and Chris, thank you for having me.

[Chris]

Yes. Awesome. Well, let's give the audience a quick background. This is your first time on omnitalk, so let's give them a background on Big Sur AI and what you and your team do.

[Vinod Ramachandran]

Absolutely. So we started Big Sur AI about a couple of years ago. At Big Sur AI, we are basically building the only AI platform for retailers and brands that they will ever need. So we are building a set of specialized AI agents, each one catering to a different aspect of the retailer's operations. So think of it as a team of experts, each one handling different parts of your business, from sales to marketing to data analysis. But except that they're all powered with AI. So, for example, our AI sales agent sits on the merchant's website and it tries to recreate the personalized experience that you would get if you walked into a brick and mortar store and bringing it to the online world so that it can boost their conversion rates and sales. Similarly, our AI content marketer is like a member of the marketing team that can instantly create landing pages in minutes that could be used for paid campaigns or SEO. Today those things would take multiple weeks for the team to do, whereas now we can do these things in minutes. So it's just the beginning of the journey. We are continuously building more AI agents for other aspects of the business. So that's the path that we are on.

[Chris]

Well, and Vinod, what's your background? Like, how did you decide that this was the problem that you were going to tackle? And so boldly, I might add, like all the AI that any company could ever need.

[Vinod Ramachandran]

So big part of my career I spent at Google building some of the most foundational products, both consumer facing and advertising products. So my co founder and I originally built the Chrome mobile browser, which is kind of the foundation of like online shopping today.

[Sne Parmar]

Right.

[Vinod Ramachandran]

And then, and then I.

[Chris]

This is why I asked the question, this is why I asked vinod.

[Ed]

Nice.

[Vinod Ramachandran]

So I spent a long time also building many ads, products and shopping products at Google. So I've been on the other side where retailers and brands are spending a lot of money on these platforms, on ads. And it's very clear, especially those that don't have the deep pockets are kind of struggling to stay afloat. Right. And so to me, when the AI revolution came, it became pretty clear there's a huge opportunity to build something that can cater to brands and retailers of all sizes. And so it was kind of an obvious choice at that point.

[Ed]

God, I love this job, Ed. I love this job. We're talking to the guy that invented the Google Chrome browser. This is great. All right, so. So you're going to be in this startup pitch competition too, right? And you get like five minutes or something, three minutes to pitch what you do, what the company does. And you've already kind of done that to some degree, but we're going to give you a little more time here because what Ann and I want to know, and what our audience I think is wanting to know too, is of all the things that you can do, what capabilities on your platform do you think are going to resonate the most with the retailers or the CPG brands at Shop Talk?

[Vinod Ramachandran]

Yeah, absolutely. There are three primary capabilities in our platform that they can use to drive tangible results. Today, the first one that we talked about is the AI sales agent, which today, within minutes, any brand would be able to integrate this on their site and they would be able to boost their conversion rates almost instantly. We built this product, we launched this more than a year ago and it's doing incredibly well. So that's number one that can drive immediate impact. The second thing is any marketing team at any retailer or CPG today is spending a lot of time building content that ranks well on traditional search engines, on AI search engines for their paid campaigns and so on and so forth. We have made that process super simple by giving them an AI employee called the AI content marketer, where you can go and spin up hundreds of landing pages within minutes and that could instantly start driving net new traffic for you. It could start ranking in these AI search engines as your authoritative voice about your products. That's another one that they can immediately use. And the third one, and our newest launch, is called an AI data scientist, which is again an employee of the merchant's organization that can translate complex data into actionable insights. On Slack, you can go and chat with this AI data scientist and ask about any product or business metrics related questions and you will get those answers instantly. So instead of you going and figuring out dashboards and writing SQL queries and whatnot, you can now ask about your product and business performance just like you would ask any other human employee and get those answers instantly. So these are three things that brands today can adopt and really start shifting their business towards this AI era, right? It's almost like making your business AI ready and you need to take it in steps. But how do you find the products that drive immediate impact? And those are the three that, that we offer today.

[Ed]

So Vinod, so because you said, because you use the term like it acts as your employee is, is what you're talking about agentic AI or you know, you know, tell our audience about that, like what is that concept and how does that fit in here?

[Vinod Ramachandran]

Yeah, exactly. So we are trying to recreate, like take the content marketer as an example, right? We are trying to recreate this experience where today a content marketer is using multiple sources of data to determine what type of content I should generate and which ones are going to perform well on my SEO or paid campaigns. You know, can I continuously optimize these pages, how frequently should I come and refresh these pages and so on and so forth. What we have done is truly utilize maximum possible amount of sources to automate this process so that the content marketer today can think about more strategic initiatives as opposed to doing the grunt work of actually producing this type of content. So to give you an example, our agents act together, they collaborate with each other. The AI content marketer looks at all the conversations that users are having with the brand, picks out topics that are important and automatically generates landing pages that could immediately be hosted on their domain for SEO purposes. So that if those users or any other user is searching for a similar thing on Google or ChatGPT or perplexity, you have an opportunity now to rank. Right? And so this is completely automated process with zero touch, we could produce a lot of content for you that is your authoritative voice about your product category, that when users are looking for meta search engines, they will be able to find those.

[Chris]

So yeah, it's so cool. Vinod, I was just thinking like we just heard a few weeks ago on our Fast five about like how Walmart's built something like this internally for their own teams called Wally. To start gathering this data in the way that you're talking about, you have to, as a brand not named Walmart or Amazon or any of these key players, these are the types of things that you have to be investing in and be ready for if you're going to win, right?

[Vinod Ramachandran]

Absolutely. Exactly. I think you're spot on. So that is the key aspect. There are very few businesses, very few retailers who have the resources to take advantage of new technology. You know, look, I've been working in tech for like 20 plus years. We have all seen a few technology shifts, but nothing as big as what the impact that AI is going to have on E commerce. But unfortunately, not every brand or retailer have the resources to completely leverage the technology to their advantage. And that's exactly what we are trying to do, is like, hey, we will be your partner and we are building out this platform that if you start utilizing it, you know, you don't have to fall behind the largest retailers. Right? Like, you know, you have an opportunity to compete well, and that's exactly what we're doing.

[Ed]

And so Vinod, going back to the whole AI and what's the problem that you solve? The problem that you're solving in this use case that you're giving is, is the SEO, is the SEO issue, right? Like that you can help the retailers rank higher in SEO and therefore drive more traffic, more traffic to their site. Is that correct?

[Purva Gupta]

Yeah.

[Vinod Ramachandran]

So we are solving basically three, three problems. Each one, as I said, each agent is solving a, you know, different problem. It's all burning for the retailer. The first one, the AI sales agent, is about how do I help increase your online conversion rates for users who are already landing on your site? As, you know, the customer experience, consumer experience, online shopping has been stagnant for many years. Right. Many people have tried to kind of recreate this experience of like this personalized guidance in store and bringing it online. With AI, we are now able to do that. So this is all about how do I increase your conversion rates for users who are already landing on your site? The second the content marketer is about how do I drive net new traffic to your store. Right. So by creating the right set of content that performs well for SEO or for paid campaigns, you're now able to drive net new traffic. And then the data scientist is about, how do I improve decision making and productivity in the retailer's organization by bringing the access to information to their fingertips. So instead of like imagine if you're an executive at a retailer and you're thinking about like, hey, how is my site performing? Or how is my, you know, product margins looking? You know, today you'll have to go and like dig through multiple dashboards to kind of get understanding. What if somebody was sitting next to you all the time who can answer any of these questions? The moment it comes to your mind, if that happens, then your decision making improves substantially. So it's all about improving that decision making and efficiency of the team. So that's what the data scientist is doing. So each one of these is important problem, right? I mean we all know that retailers, many of them are, you know, the number of people in the organization is shrinking, right? Like, you know, many of them are kind of like struggling. So how can new technology actually help them compete better? And that's why, you know, we are building this platform.

[Chris]

Well, Vinod, I know, you know, you've outlined these three categories where big Sur AI is already able to use. Have retailers use these agents to help their, them and their online business. What are the next things you think that are the most kind of critical components that are missing from the online shopping experience that you feel like you're going to prioritize as your organization to help provide to the retailer so they can, they can help create an even online and offline experience or get as close to that as they can for their customers.

[Vinod Ramachandran]

Yeah, I can talk about this for hours. But, but really I think you know, first on the consumer experience side. So first of all, AI is going to, as I said, impact every part of a retailer's business. Both sort of like consumer facing as well as the back office stuff. But as far as the consumer facing experiences are concerned, our platform is not just about recreating this in store experience and bringing it online. But how could you actually redefine the overall online shopping experience? So for example, I think within some time period, maybe a year or so, one could get to an experience where anytime you land on a merchant's website, every pixel on the screen is being generated and personalized for you. Yeah, that's the true power of hyper personalization, which is now possible with all the real time analytics that is made possible with AI. And so that I think in the near term it's quite possible that anytime you go to a website that everything on that website is being generated and personalized for you. This notion of having this old website which is being a set of static pages will go away and kind of create like everyone gets their own version of the, you know, the site and own version of interaction with the brand. So I think that certainly, you know, is within striking distance and will happen. Brands that embrace AI are going to demonstrate this and show impact. But there is a lot more. When I talk to customers, there are interesting problems that they bring to the table. Like certainly inventory planning and forecasting is a major area of opportunity. We are not tackling that yet, but we certainly want to. But then there is also more interesting problems like how can I design my next generation products using AI? So if you are an apparel brand thinking about what materials I should order for my next season, what design should I produce for my next season can help them produce more thoughtful recommendations and suggestions that could perhaps move the needle for their business. Those are all interesting areas that we certainly want to get in at some point. But most of our focus today is all about sales, marketing and the sort of the consumer facing aspect of it where there is still a lot of opportunity.

[Ed]

And it goes back to what Ann and I've been saying for a while now that the rise of AI is going to change the user interfaces by which we, you know, shop. E commerce particularly, you know, what we're used to is not going to be what we're. How we shop now is not going to be the way we're shopping, you know, three, five years from now, based on what you're saying. The other point I love too is the data science piece, you know, that you talked about too. Vinod. Like that's a real gap for, you know, 99% of retailers, like 99% of retailers don't have a data science arm stood up to the degree that they probably need to to compete with the big guys. And so that's a really interesting aspect of what you're doing too. All right, well, let's get you out of here on this. So we've been asking everybody, we got to ask you too. What's your favorite thing about shoptalk or what are you most excited to do while you're out there?

[Vinod Ramachandran]

Great question. So this is my third year in a row attending Shoptalk. Very excited. So you know the thing that I love the most about it is the vibe and the energy of the people.

[James Toyakov]

Right.

[Vinod Ramachandran]

Like I think it's one of those very few conferences where people who are truly passionate about commerce, retail, e commerce, are all congregating with each other and you have an opportunity to have like face to face conversations. There is nothing that you know that can beat that. In fact, I would say for the last two years in a row that I have attended a single event that has been most productive for us from like product input, feedback, customer acquisition, etc. Shoptalk has been like the best forum for us. So really eagerly looking forward to it. And obviously as you we referred to earlier, we are also going to be presenting at a session at this year's Shop Talk. So really excited about the potential.

[Ed]

Well yeah, so if, if people, if people want to get in touch with you while you're out there or catch that session, like when is it and like what's the best way for them to do that?

[Vinod Ramachandran]

Absolutely. Our session is on Tuesday, March 25th at 4:05pm so if you want to hear about us and other innovative companies in this space, definitely come attend that session. We certainly would love to meet everybody who's interested to talk about our products or in general how AI can influence retail. So you can also reach out to us at my email which is Vinod Big Sur AI. It's V I N O Dixer AI. We'll be very happy to meet and we also have a few dinners and happy hours planned so we can make this a lot more fun.

[Ed]

Well, can't wait to see you there, Vinod. So joining us now is Lucky's CEO Sne Parmar. Sney, welcome back to Omnitalk.

[Purva Gupta]

Thanks Chris and Anna for having me.

[Ed]

Yeah. All right, let's start with this, let's start with this. Let's give the audience a reminder about what Lucky does and why do you guys started the company. Because that's an interesting story.

[Purva Gupta]

Yeah, no, absolutely happy to walk you guys through a little bit of that. I mean to kick off what Lucky is, we're a data omnichannel data company. So what we do is we partner with major retailers, think Sephora, Ulta, Nordstrom, etc. We integrate to their inventory systems and their attribution systems. We basically ingest that data, standardize it, clean it and then share it back with brands. So what brands get out of it is a couple things. They're able to showcase real time availability to their customers, track when customers are shopping from brand.com to retailer.com and if a brand is running their own retail marketing, they can finally get attribution on those campaigns to see which campaigns work. So we started this company actually because like me and my co founder, we were previously in the brand space. So we were helping brands launch on like Shopify, online, e commerce, you name it. We saw their growth, saw the data they were getting and then we saw like this change of brands going to retail earlier in their life cycle, especially post pandemic. But the challenge was it's not really that data driven. Like you're really beholden to beholden to the sales data that a retailer gives you. And that's about it. So our thesis was we could go partner with these major retailers, show them that hey, if you let us share this data through our pipelines because we're a tech company and we have, we know exactly how to do this in a very, very easy, lowlift way for both sides, then it actually drives more value and revenue to the retailer themselves. And brands are super happy because now that they're finally getting data that they never got before and they're able to showcase increased retail velocity. So we look at, we look at ourselves like a one liner is like, hey, Lucky is here to help you increase retail sales. That's what we do. And we have a couple of ways we do that.

[Chris]

Well, Snee, you just had a massive announcement with Ulta, one of my favorite retailers. Can you break this down even further for us? Like tell us a little bit about what you're helping Ulta do and like who some of the other clients are that you're working with and maybe just kind of walk us through kind of how this works between brand, retailer and Lucky.

[Purva Gupta]

Yeah, of course, yeah. And I think so much, yeah, Alto was a retailer we were working, trying to get for a long time. We were fortunate. We finally got them, show them enough value that they were like, hey, like let's, let's move forward with this part.

[Chris]

Let's dance.

[Ed]

Yeah, you and everybody else, man.

[Purva Gupta]

I mean, yeah, no, absolutely. And I mean and the way we work between like us, the retail and the brand. Yeah, that's a question. Is so what we do with like Ultra for example, is we obviously ingest store level inventory data from them and we have a direct link into their attribution and affiliate systems. So we take that data and then we Share it back with the brands through products that we sell to them. So as a brand you're able to utilize Lucky for three distinct reasons. So one is an inventory driven store locator. So imagine like you go into a brand's website and you go into their store locator. It's just typically like right now static store name, address of phone number, let's be calling the store. But hey, is this product available or not? We're able to showcase in real time every product and SKU available with quantity available right now. So that's amazing for a consumer perspective. And they actually end up buying from like let's say ulta.com through our experience. Then the brand actually knows that data and they can see the entire cart. On top of that we have like a PDP experience. If you're on a product page, you can also showcase, hey, find a near you right now. But it's filters based just off that product, which has been really, really helpful. And we've seen a lot of engagement and like honestly increased sales revenue for the retailer and the brand through that. And then the last piece that we offer to brands is a retail marketing attribution tool. So imagine like you're a brand running your own marketing campaigns on like let's say Instagram for example, like to hey, go buy my product at Ulta. Right now you're only getting click data on those ads. You're not able to actually see. Someone went to Ulta.com and bought, bought a product. We can actually do that through our end to end solution. So that's kind of what we offer to these brands. And then obviously the retailers are super happy because we're helping them drive more foot traffic and sales. Like everything is about how can we drive retail growth and scale. And that's kind of why all these retailers align really well with us, including Ulta. And then a few other players include like Sephora, Nordstrom, Bloomingdale's, even Best Buy as we look at category expansion. So it's been beneficial to both sides and we like to, we like to think of it as a win win situation. So a lot of people like working with us.

[Ed]

Yeah, yeah. One plus one really equals three in what you guys are trying to do. And the thing I love about it most, it's a great omnichannel solution that connects the brands to the retailers in a new way in so many levels from an inventory standpoint, from a data perspective too. Well, what do you, what do you anticipate is, is the number one challenge that that the brands are facing right now that you think they're going to come and approach you and want to talk to you about at shop talk.

[Purva Gupta]

Yeah. And I think it changes, right. Like every shop talk, I think, I think, does it? Okay. New problem that everyone's talking about. I think this year, I mean, at least we've seen like the demographic of customers and brands and partners and everyone that we work with. I think one of the biggest challenges that we see these brands having or these people having is how to like optimize their retail marketing or like retail marketing spend. And I think that's something that like we've kind of gotten ahead of. We've been iterating with our brands, retail partners for the last like six to ten months on this product. That's something that we've seen grown in demand more and more every single time we talk to a brand, especially as we go more upmarket, like we're starting to like knock down some enterprise brand clients. So because of that, we're starting to see that become a larger and larger challenge. And we're happy to say that we have a solution to that problem. But at the end of the day, I think everyone's wondering, okay, how can I grow retail sales? Right. It's a finite space. Everyone's trying to fight for the prime real estate in stores. So you have to continue showing performance and velocity, otherwise you're no longer there. So I think every brand or customer wants an edge and we're hoping that our platform provides that.

[Ed]

Yeah, that's a great point though. It's good to keep in mind if you're a startup DC startup brand or just trying to get shelf space, still got to figure out how to maximize that advertising roi. So I'm not surprised that that's something that you're, you're focused on with them. That makes a ton of sense.

[Chris]

Yeah, yeah. And, and to be able to like attribute those sales, especially when with the increase of people, you know, discovering products online and then being able to actually say like, yes, this drove me into this store or this added this to my basket, and here are the results. It makes those investments easier on the executive teams running those campaigns, I imagine.

[Ed]

Absolutely.

[Purva Gupta]

And what we've seen is like, I mean, I mean, everyone buys, everyone has their preferred method of buying. Right. But in beauty, which is a category that we're very familiar with and have very, very well dived into, like people love shopping at Ultrason Sephora. Like, like they, like, they go to brands websites to learn about their products. Like hey, educate themselves. See, like, let's say the UGC content reviews, all that. But when the consumer's like, hey, I want to go buy this product, they're like, well, my bullety points at Sephora Ultar are worth way more than trying to buy brand. So, like, they're going to go to those stores anyways because they also probably like, hey, I have three other things I need to buy, so let me just go there. So, like, we've seen like, especially in beauty brands, really liking the attribution and being able to showcase like, hey, we drove that sale.

[Ethan Chernovsky]

Because then they can go to the.

[Purva Gupta]

Retail partner and be like, hey, we actually are driving you a lot of revenue directly from us because that's the preferred method of buying in that category.

[Ed]

The other point, too, it's a validation point for those brands, you know, that you should have confidence as a consumer that they are legitimate and doing well and that you want to buy them. Right. Because you can see them available and the inventory available at any retailer that you particularly happen to like as a consumer. Is that right? Sn yeah, you're absolutely right.

[Purva Gupta]

And I hit the nail on the headquarters.

[Chris]

Yeah, well, and I think that's going to change too. Like we've talked about too, one of the tracks at Shop Talk is solely focused on changing how we're changing our search behaviors. And so that attribution is going to become even more important as we start to use chat GPT to search for things, or we're using Google Lens to search for things, like being able to one identify like, I have loyalty program points at this retailer, so I'm going to go there over another one. But then also seeing like, this is also the closest place that I could go get it, so when I have that intent mindset, I can execute on it right away.

[Purva Gupta]

No, absolutely.

[Chris]

Okay, well, snay, let's get you out of here on our favorite question. Snay, what is your favorite thing about Shop Talk?

[Purva Gupta]

There's so many. I mean, I think Shop Talk's one of our probably, if not one of our top three fair conferences of the year.

[Chris]

Why is it?

[James Toyakov]

Why is that?

[Purva Gupta]

I know that's a good question. If I'd have put it into one word, I think the serendipity of the conference. So, like, we've, we've always found, like, like we always go to conferences, like, with an agenda, right? Like, hey, these are the people we need to meet. These are these things, events we need to do. These are the things we need to get done. But what we found is like the time when we don't have anything to plan on our schedule or, like, either walking to show floor or just like out at the little cafeteria area or just like, talking or meeting people. That's when we actually meet the best people for us as a business. Like, that's when we meet someone like, hey, we're like, wow, this is the enterprise we've been trying to get in front of, like six months. We just met them in person and this is like their CMO that we're talking to and they love us. So I think, like, that, like, serendipity of just, like, running into someone that you never know could be super valuable or who they're connected with or what relationships they have. I think that's like our favorite piece about shoptalk. It's like everyone there's is valuable and, like, you just got to find out how.

[Chris]

That's a perfect answer. Sn. I love it. Thank you so much for taking time out to join us. And before we let you go, if people want to have those either serendipitous connections with you or they want to actually put it on their agendas, what's the best way for the people to connect with you at Shop Talk next week?

[Ed]

Yeah.

[Purva Gupta]

So, I mean, they could shoot me an email. I think that's probably always easiest to schedule some time, which is like, just snay, like sneh at Lucky Labs IO. So just shoot me an email, connect with me on LinkedIn, just sneypramar on LinkedIn and then shoot me a message. I'm pretty accessible on both channels.

[Chris]

Amazing. Thank you so much, Sney.

[Ed]

Thanks, Sney.

[Purva Gupta]

Yep.

[Sne Parmar]

Thank you, guys.

[Ed]

Hello, everyone. We're back again and this time we're going to introduce Lilly AI CEO and co founder Purva Gupta. Purva, welcome to omnitalk.

[Mark Tack]

It's so nice to be here. Thank you so much for having me.

[Ed]

So let's start with this. This is kind of becoming the theme of this webinar, actually, is. Let's start with the problem you're trying to solve when you created Lily AI and what the product actually does for retailers and brands as a result of that.

[Mark Tack]

Absolutely. So Lilly AI bridges the gap between merchant speak and consumer speak in retail. So, simple example, a merchant will describe a product as Midnight French Terry at leisure. I love this already is going to say navy blue hoodie.

[Alex Hazy]

Yeah.

[Mark Tack]

And they're not going to have a good experience, most likely, because those are the words that aren't. There's just a gap in that language. And now Chris, we actually live in a world where it's not just about the gap between motion speak or marketer speak and consumer speak. You also have the machine speak now, like, what about the machines?

[Ed]

Right.

[Mark Tack]

So that's the gap that we're bridging between the merchant marketer, machine and the consumer, where it's just so much more important now to understand what the consumer cares about and optimize for all these different channels. And so the way that I would now describe Lilly is we're a company that's doing product content optimization for all these different channels in and supercharging all different parts of your retail stack.

[Ed]

You're speaking my language. As a former merchant, I can remember, oh, my God.

[Chris]

I know.

[Ed]

You know, 100% where, like, I'd be like, guys, you can't call that on this. You can't use that language on the site. You got to put something that people can actually search and understand as consumers. But. But how would you say. How would you say, Lilly, AI differentiates itself from the competition because, you know, there are a number of companies in this space that, you know, are, you know, trying to solve the same problems that you just described. But how do you differentiate yourself?

[Mark Tack]

Absolutely. So, number one, I'll say we've been the OG in this space, and so we've not added AI to our name in the last two years in that company for a decade.

[Ed]

True that. Yes.

[Mark Tack]

So we understood this very early on that your AI is as good as your training data. And so Lilly today has the largest clean, proprietary training data set in the world. For a decade, we've been creating our own clean training data. And of course, back then it was like, this company is crazy. Why are they doing this? And now it suddenly is making sense to everybody. And it's that advantage, that just natural advantage that we have because we have the really good clean training data. And the overall bigger point here is accuracy is really, really important here when you talk about product content. So that's number one, accuracy is really important, and Lilly absolutely tops that game. And that's also demonstrated by all the largest brands and retailers that we work with and have been working with for a while, not just in the last two years. So that's number one. Number two is relevance is really important. That natural language of the consumer is constantly changing, and it's different on different platforms. What you see on Google Meta, what you do on a marketplace, what you do on Amazon, what you do on the own e commerce website, it's different everywhere. And it needs to be optimized like that for that channel. And so that relevance is really important. So what Lilly does is that we're listening to all this external signal from everywhere, all the way from literally your Google Ads console. We're looking at all the search terms and extracting keywords out of that and getting that additional signal to your first party. Data that we're getting from brands and retailers to say, here's our data now look at this and get the signal. And so relevance of what matters to the consumer is so much more important today to understand than what has happened in e commerce experiences over the years. And so relevance is the big muscle that Lilly has built over the years. And that differentiates us from not just the accuracy of what we are producing in terms of content, but also the relevance of that content and optimization for all different channels.

[Chris]

You gave a few examples. But I mean, what is it that your clients are really coming to you to accomplish? Like what's top of mind for them when they're using Lilly? And then maybe if you can talk about a little bit too about like where, where is a good place for them to start.

[Mark Tack]

The number one thing that consumers are excited about with Lilly AI is our consumer first nature, right? So we're talking about natural language synchronization, understanding words that consumers care about. It's real time search intelligence. It's the, the continuous feedback loop. So what you're hearing, the signal that you're getting, you're putting that back on the catalog and making sure that that feedback loop is closed so that the consumer has a good experience. And then that shows up in the revenue that we are, revenue that we're generating, right? So macro micro trends, I mean, I'll use the very, sort of the very popular trends like quiet luxury, Barbie Core or Wicked or whatever it is that is going on. You've got to optimize for all of that and it go on your catalog and it cannot be done manually anymore. Look, it's, it's been done manually for all these years, but that's where you're leaving a lot of money on the table. It cannot be that it needs to be optimized. And this is where you can start listening to these trends six months before they become mainstream. And everybody's like, hey, do we have that in our catalog? It's too late. Like you need to be earlier on that trend curve versus when it's peaking or on its way down. And so you know those, those macro micro trends about what the consumer cares about is really, really important. So the number one thing I'll say is the whole consumer first nature of what we do at Lilly, where everything that we're building, we're not a company that's building cool AI stuff. AI is an enabler. It has been over the years. We're solving the core problems that these brands and retailers care about, which is about how to bring what the consumer cares about at the center of the experience. Everybody talks about that. We enable that for them. Right. So that's number one. Number two is data. In this new world that we live in now, everybody understands your AI is as good as your data. And so like I said, Lilly has the largest clean training data set in the world. And that lends to the accuracy that we are able to deliver. This is a lot of proprietary data that we have that you just cannot get unless you just start doing this today with tremendous amount of capital that'll need to be invested to do this.

[Chris]

Herba. I think it's really important to call out too that this is not just something that the major retailers out there are going to be investing in and doing. You work with a variety of retailers and you have this 10 years of history in and database that you are able to apply to a variety of business sizes. That's right.

[Mark Tack]

We're talking about, you know, the largest brands and retailers to anybody that is doing 20, 30 million in, in, in GMV, like anybody can do this today. Anybody Optimize and, and, and the important thing with, especially with respect to one of our offerings where it's the optimization of Google Merchant center. Everybody's spending money on Google. So that's the point. It doesn't matter how much money you're spending on Google. Great. If you're spending a lot of money, the gains will be more, but absolute value gains will be more. But all said and done, while there are so many other bots coming for your content on your product detail page, Google is still one of the largest spend of all of these brands and retailers, irrespective of size. And so for us that's important that wherever the world is going right now, you're going to optimize Google. And if it's something else in the future, you are ready for that. And make sure that you have AI generated content that is optimized.

[Ed]

And minimally too, you got to optimize for your organic traffic, right? I mean, you want to convert the organic traffic too, right? Because those are the people that want to buy from you the most. You don't want to let them go out the Door as well. In addition to the Google. Right Purvo.

[Mark Tack]

Absolutely. This is where the product detail page comes in. Because your organic traffic like all the way from SEO to now geo is all happening from content on your product detail page. Organic traffic. Chris, the most important word in that whole sentence is relevance. If it's not relevant, you are not getting the organic traffic. The headline here is for so many years lots of agencies, players have been doing a lot of technical SEO to make a lot of things right for that organic traffic to come, which is all great, but product content wise, on a per sku basis that optimization has just been not done because it was not available. This was very difficult to do over the years, but now available. So on every single product detail page you can have relevant content related to that product at scale for your entire catalog and get all of that organic traffic, you know, at a. In a whole different manner. Relevant because of the relevant content.

[Ed]

Yeah. Right.

[Sne Parmar]

Yeah.

[Ed]

And the last thing any E commerce merchant wants to do is, is have us have a product available on their site that someone can't find because they don't have this data set up in the right way. Right. And that happens all that, that happens all the time.

[Mark Tack]

Absolutely. We have this new way of describing this. Be found, be sold. Okay, like if you're not getting found, you're like, forget about the second part. And so the whole thing is interesting. Be sold.

[Ed]

And you guys measure that, like do you measure that with your clients too? Interesting. Like how does that work?

[Mark Tack]

Absolutely. Lilly is a performance first company. We're one of the very few AI solutions that is getting into a brand because we have already proven value and they have the option to walk away if they do not see value. So every single customer that you'll see on our website or whatever else that we talk about, all of these largest brands have experienced value. That's why they are working with us from the get go. And especially in this space, performance is absolutely paramount. And so in the case of, as we're talking about the overall performance metrics here, if you're talking about the PDP visits, the, the conversion or the incremental revenue, we're talking about like massive meaningful lifts. So in the case of, you know, PDP visits like 2 to 8% lifts in that in terms of conversion, we're talking about 3 to 25%. These are not made up numbers, real numbers from these larger brands and retailers and incremental revenue, 2 to 24%. And again the, the larger the brand is, when I see these numbers, I'M like just blows away my mind of saying wow, there's like tremendous opportunity where we are going up to their. We're basically part of their board narrative saying what are the top three AI solutions? And we are part of that saying lilly got us 24% lift in revenue from what we're spending on Google. That's just music to any founder peers.

[Ed]

Yeah, it's a definition of working smarter and not harder. And it's also why when Ed told me we got you for this webinar I was pretty excited because been following you guys since like you said, since you were an og. So it's really, it's really cool to have you and it is the definition of that 100% so. All right, I've been dying to ask you this next question. So there's an entire track at Shop Talk dedicated to the changes that in how people are going to search for products online. So with you kind of an expert in that space, what do you predict, what do you predict is going to happen in the field of product content and search and discovery here over the next say three, five, ten years?

[Mark Tack]

Absolutely. So number one, long tail searches will be the norm. Right? Like I'm, I didn't even have to say this like you, you already know this. This is just stating the obvious. Long tail searches because our consumer behavior has changed like we. And just imagine how fast that has happened over the last two years. If I just use November 2022 when ChatGPT came around as like just as a point in time. Look at how quickly that has changed. That one in three shopper online today has already experienced a search with an LLM like just a generative search. And so number one, long tail searches will be the norm. That is just going to be how it is going to be in the future. So that's number one. Number two, like I was saying that you know, consumer behavior has just changed and so there's going to be a lot of focus on GEO and AEO in the future because consumers want answers.

[Chris]

Purva define AEO and GEO for some of our listeners who might not be familiar with those terms.

[Mark Tack]

Absolutely. AEO is answer engine optimization and GEO is generative engine optimization. And they want pretty good relevant answers. And so it's, it's just going to be so much more important that brands and just overall commerce pays heed to that relevance is not going to lose its meaning. Like it's just going to be so much more important that you cannot have non relevant content and pay through it anymore. You have Got to have relevant content, otherwise you're going to miss out.

[Chris]

All right, we're going to wrap up with our final question. What is your favorite thing about Shop Talk Purva?

[Mark Tack]

So many things, but top of my mind is as a founder, just meeting lots and lots of customers. And Shop Talk has really good audience in terms of, for a player like us. And so just meeting lots of customers. When I say lots, meaning literally, I think it's the largest amount of meetings that we do at a retail conference. And so it's a really good conference that gets really good audience. And so my favorite thing is to just for non stop 3 days with my sort of running shoes on, just run and just meet customers and just do a lot of those meetings and still not feel as exhausted because it's so energizing to meet execs and understand what do they care about and what the problems that are top of mind for them.

[Ed]

Yeah, that's a great point. Yeah, you gotta have good shoes. That's a good, that's a really good point for this conference. You gotta have good shoes. All right, well, so if, if people want to get in touch with you either watching this now or they're going to be at the show. You mentioned you have a lot of meetings. Generally speaking at Shop Talk, what's the best way for them to do that?

[Mark Tack]

Absolutely. We, we have a booth. So our booth is called. Is. Is number 1914. That's easy to remember. I'm sure it has relevance, which I can't think of right now. But anyway, 1914 is where we're at that you can find us. And also I will be speaking alongside one of our amazing customers and sharing their story of what they were doing and looking for and their AI journey. So there's lots of ways to meet us and I'm excited to meet folks at Shoptalk.

[Ed]

Wonderful. Well, hey, yeah, I mean, if you're, if, if you're not on the content train already, that's what I'm taking from this conversation. And if you're not on the content train already, with all the changes that are coming with Generative AI, it's just going to become even that much more important. So thank you so much, Pervert, for joining us today.

[Mark Tack]

Likewise. It was a fantastic conversation. Thank you for having me.

[Chris]

Joining us next is Syrup's co founder and CEO James Toyakov. James, welcome to the show. It's exciting to have you here.

[Ann]

Thanks for having me.

[Ed]

Why don't you share with our audience for maybe those that didn't listen to Our first podcast with you. Tell us a little bit about what Syrup does and also why you founded the company.

[Ann]

Totally to think of Syrup as being an AI decision support system or an AI brain that gives you as a brand retailer, manufacturer recommendations on how to optimally make your inventory decisions. So for brands like Abercrombie and Fitch or a Deckers authority, we're helping them forecast their inventory, forecast their demand and then take the next best possible action. So how do you optimally allocate inventory, replenish inventory, buy the right product and yeah, we're doing that for, for a couple dozen brands and retailers and I found the company in the summer of, of of 2020 after having consulted, you know, a couple dozen brands and retailers and seeing, seeing these inventory processes. Right. And, and really seeing how a lot of this decision making is just based on past performance and on averages and averages of averages and the averages of averages of averages. And I have this deep rooted belief that we as humans, we should be doing the things that are not yet repeatable. Let the machines do the work that is repeatable. We humans just focus on the not yet repeatable and there just seem to be this huge opportunity leveraging the fact that we have access to more data than we've ever had before and that we're living through this Cambrian explosion of, of, of AI.

[Chris]

Well, and James, this is you, you're pretty, you've been doing this for a while. You're pretty early on the forefront. But what, what was it that had to be true for you about founding Syrup to be different than some of the other solutions that were out there? And, and really what was it about your experience that you were like, I want to nail this part of visibility and accuracy and being able to do this the right way.

[Alex Hazy]

Yeah.

[Ed]

A lot of people have tried before you. James too, I might add.

[Ann]

Yeah, yeah, totally. It's the age old problem in retail, right. How do we get the right product, put it in the right place at the right time? I think the two things that were true at the moment of fan and continue to be true today are data access, which means both first party data that lives within our customers four walls. So you know the classic transactions inventory levels, but also very interesting data points like E commerce behavior or E commerce analytics and marketing and plans and spend, which are huge indicators of, of of demand. But then also external data. Right. Our ability to understand, you know, the Internet.

[Ethan Chernovsky]

Right.

[Ann]

And whether that's social media or events databases or, or social demographic information that, that access to that data is something that we've never had previously. And then second is, is it's just this, this explosion of AI, right. And it's a very different ball game today than it was even three or four years ago. And even, you know, go back seven, eight, nine years ago. Like what we're able to do today of really sifting through nuances and making sure that we understand how does the stock out of one product, what does that lead to the demand of another or what does a certain, you know, feature of a product that we can identify through images, what's that mean for demand? It's just absolutely mind blowing what we're able to do today. And that's, it's a real jump, right? And it's a really, it's a different, different ball game than it was even just a few years ago.

[Chris]

Yeah, I can imagine. Well, and James, do you think like, so Shop Talk's coming up, you all are going to be out at Shop Talk. Do you think that that kind of question from retailer, is it going to be that, like how do I use AI to properly apply that to my day to day operations? Do you think that's going to be kind of the top question that you're going to get asked coming up or what, what topics do you think are going to be really top of mind for the retailers and brands that you're going to be meeting with there?

[Ann]

Yes, and I think so we get asked this a lot around, right? What, yeah, what does AI really mean? And there's, you know, there's a frustrating amount of, of noise as well around, around AI that I think is really confusing and frustrating for brands, retailers and manufacturers. You know, we at, at nrf, we heard this one company speaking about, hey, we've been doing, you know, machine learning for 30 years and these machines learn and imagine, imagine how good our models must be. And with all due respect, that's not how the technology works anymore.

[Ed]

Right?

[Ann]

So there's just so much noise and confusion. And so we get asked this a lot of like, you know, how, what, what, what does the AI actually do? Like can you explain to us like what, what does AI actually mean? And I think it's a really, really important question, right that I would hope that any, that any kind of, you know, software play has a good answer to but then they can also link to actual business outcomes, right. And business results. Like what does, what does the power of the AI actually do to help you with forecasting newness products, right or, or handling data sparsity or accounting for the fact that you have A complex omn like there's real business problems that at the end of the day all, all bubble up to top line and to bottom line. That AI can help you answer. But yes, I think, I think that is the, that is the, the, the, the, the zeitgeist or the question of the zeitgeist.

[Ed]

Zeitgeist. Nice. All right, James, I want to go a little bit deeper into that because, you know, having been a former executive in this space, you know, being responsible for the inventory, the planning and allocation at multiple companies, I'm curious and also having seen a lot of executives who think they're pretty smart come into Booth and ask the tough questions to prove your mettle. What is one or two of the toughest questions you ever get that proves that you at syrup know what you guys are doing?

[Ann]

Yeah, I think we get question. I think the really good questions that we get are the ones that, that make us illustrate how the AI tackles certain business problems. Take data sparsity for example, right? The, the, the question is, hey, our average unit sales of a product in a point of sale in a week is or 0.2. Like how on earth do you forecast that? Right? And how does your super smart AI help you with that? Right? And that makes you actually have to explain the workings of the model, right? And in our case, the way that it works is that you're, because we're not just using transactions, we're using all of these other demand sensors is actually there's a whole bunch of data that we can use. And then because the modeling is, is inherently hierarchical, you can go up and down the stack and kind of use that so you're not just looking at, you know, this, I know this beige linen blazer, but you can look at a navy blue blend laser or a, or a beige pant and you have all of these kind of, you know, demand signals across your assortment, which means little like a chat GPT does, right? You have this massive blender of, of information that you can then use kind of for hyper granular predictions. But I think these kind of questions that come with real business problems, right? And then ask you how does your, how does, how do your models, how does your software actually solve them? Those are the, those are the hard ones and those are the right ones to be asking as well.

[Ed]

So those are the questions you like the questions where they ask you say, hey, how do, how do I actually forecast what I'm selling? 0.1 unit per store. That's essentially that, that's your wheelhouse. That's the questions you love to feel. That's great.

[James Toyakov]

All right, so you're going to be.

[Ed]

You'Re going to be at Shop Talk and what, what can Ritos and brands expect to see from you there? And if people want to get in touch with you, like what's the best way for them to do that? And, and also what, what, what's on the docket for you all this year? I mean you had the big write up about Abercrombie and the Wall Street Journal if I'm not mistaken. What's, what's next for you?

[Ann]

Yeah. I think there's two big things that we're really excited about this year. One is just these really jaw dropping like advances in the underlying, the underlying algorithm and the underlying modeling and what that allows us to do. Right. That we've built this web of neural networks, we call them LDSMs, large demand sensing models. And just the pace of innovation that we're able to do there. It's amazing, Chris. And there's going to be a lot of announcements around that. That's one. And then number two is really the breadth of modules or of use cases that we're applying this AI brain too.

[Mark Tack]

Right.

[Ann]

Like historically it's been very focused on allocations, replenishments, rebuys. We're expanding that set ever further. A lot of work on kind of pre season forecasting, newness, forecasting the buying process. So there's a lot there that you know, now that the, that we've got this, this, this, even if I say for myself, pretty sophisticated and very well functioning core brain, the set of use cases that we can apply that to is going to grow really, really quickly. And so yeah, those are the big two things that on the docket for us, for us this year.

[Chris]

James, I have a question and I'm not sure if, if tariffs are impacting you at all or if they come into play with how people who you meet with, how these retailers and brands are making decisions about even styles or sourcing or all these kinds of things to, to hit these newness goals that they learn from collecting the data when working with syrup. But have you seen any impact or do you anticipate any questions about that when you're meeting with retailers at Shop Talk coming up here?

[Ethan Chernovsky]

Totally.

[Ann]

I mean 2025 has been called, I think the Economist was the one that called it a terrifying year.

[Ed]

Terrifying.

[Purva Gupta]

Oh, that's great.

[Ed]

I hadn't heard that.

[Ann]

So it's definitely top of mind.

[Ed]

Right.

[Ann]

And it's very important for many of our Customers as well of production all around the world. I mean we work a lot in apparel. The apparel supply chain is one of the most globalized in the world. And the, the way that we work through this with our customers, it's, it's through a. Configurations logic effectively. Right. It's a similar, similar way of saying what's the cost of shipping an item from location A or location B? You're, you're introducing another cost function on location sourcing on location that stack that up versus lead times and versus other costs. And it's, it's kind of this, this you know, complex multi echelon optimization. But it's, it's, it's one more, one more reason, right why like AI is so well suited to help brands and retailers in this incredibly complicated day and age.

[Chris]

Right, Right. It adds so many more factors to take into consideration. Well, James, I am so excited to see you out at Shop Talk. We, before we let you go, we have one non, non business related maybe question for you. But James, what is your favorite thing about Shop Talk?

[Ann]

Las Vegas.

[Ed]

Las Vegas.

[Ann]

I'm joking, I'm joking.

[Alex Hazy]

Are you?

[Ed]

I don't know.

[Ann]

I think what, what I really think about Shop Talk is it just creates this amazing like you know, ambience where people from across the spectrum, both kind of software players as well as, as well as brand meet and they can meet in a fairly relaxed setting. Right. Which is really, which is really, really nice. I think Shock Talk does an amazing job there of, of, of creating that setting of you know, grabbing a bite to eat or grabbing a drink or like going for an activity. Like those things, they're, they're really, really fun and that's probably, probably my second favorite thing after Vegas.

[Chris]

I love it. I love that Vegas. You are enthusiastically pro Vegas and I'm sure that all the people from the Shop Talk team listening are, are thrilled to hear that change. Well, thank you James so much for joining us. Before we let you go once more, where can listeners find you at Shop Talk next week?

[Ann]

Yeah, find us, a bunch of us from our team are there. Find us on the app. You know, come, come, come come meet us and I'll be there as well. So you know, find me on, on LinkedIn if you like or shoot me an email and Jamesirup tech, you know, we'd love to meet up.

[Chris]

Excellent. Well James, thank you so much. Thanks for joining us today. And with that we'll bring on our next interview.

[Ed]

Hello. And joining us once again for his God knows how many times appearance is one of Omnitalk fan, one of Omnitok's favorites. And yours too, place your AI's SVP of marketing, Ethan Chernovsky. Ethan, welcome back to Omnitok. I think you are officially our most interviewed member or our most interviewed person that we've ever had on the show.

[Sne Parmar]

I'm the Steve Martin of. You are of Omni Talk.

[Ed]

That's right.

[Chris]

That's a great, not quite Alec Baldwin yet. You need to be. You need to be on a few more times, but then you'll be the Alec. You'll be the most attended, most popped in most cameoed guests that we have on our show.

[Sne Parmar]

Ethan, I want to show up one time as an interviewer and just like randomly appear, ask a question and then leave. Like that's my dream.

[Ed]

How much time do you have today, Ethan?

[Chris]

Yeah, right, right. We might have a job for you.

[Ed]

We're interviewing a lot of people. All right, well, let's get to it. What is, you know, for, I mean, many people watching probably have know of you or have heard of you, have heard of Placer. But for those maybe that haven't, what is it about? What is it that Placer does? What's unique about it and what, what is it about the data that you provide?

[Sne Parmar]

Yeah, so Placer's location analytics platform. And we show visits to retail locations across the country. We use machine learning and AI on top of a panel of tens of millions of devices to show that. And the cool thing about that data source is, is think about it like crude oil, right? It can be, it can be plastic and it can be gasoline like that. Once you have that single perspective, there's so many things you can do with it. So there's these core elements that we can bring to the table. Both having this accurate, reliable understanding of visit trends, but also true trade areas. And because we can understand a true trade area, we can understand the psychographics or demographics of a specific location. And because we can see these traffic patterns, we can look at things like co tendency, cross visitation and a whole lot more. And so all the ways that you can kind of nuance that data set are things we bring to the table. I think the things that make it unique and special. I think there's actually kind of four core elements. The first is it's reliable, it's stuff that you can use. Hundreds and hundreds of retailers are using it today, hundreds of players within the commercial real estate space, customer goods companies and the like. And so I think that reliability is critical. But then the second piece of that, it's this single lens, right. So it's, there's a lot of data sources that are, let's be honest, are better if I want to understand what's happening in my own four walls. So I know more if I imagine I'm the CEO of Target, which I'm not surprised. I know more about what's being sold in my stores than Placer would. Right. But it's really difficult for me to compare that because I have great data about myself, but I don't have about others. So having a single lens allows me to have this real effective ability to benchmark and have context to what's going on. So I see visit declines in my location, but everyone else is seeing visit decline. So there's just something going on that week. I see visit increases. Is my competitor also, am I seeing something special? What's going on? That kind of single lens is critical. And the cool thing about that single lens is then it can be cross functional. So your real estate team, your marketing team, your strategy and operations team, merchandising team can all be using a single data set to understand the world. Both how I'm performing, but also how I'm performing in context. And then that last bit is it's accessible, right. One of the key things we've always focused on was making it a product that people can actually use and go quickly from question to answer to potential solution. And I think that's something we take a lot of pride in. Having a product that, you know, you can have that eureka moment. You know, you go to Shop Talk, you're having this amazing conversation, it creates this creative kind of ping. You can open up your laptop, sign in, and within literally seconds start exploring the answer to that question, understanding why it might be or what it might mean for your business.

[Chris]

Ethan, I love and appreciate that explanation because I've never heard you take that approach to it. And it's, it's very insightful. We love the data that you collect because that single lens gives us a lot of content to work from. And recently we had you on our Retailers to Watch segment back in January. We're three months in and shop talks next week. Ethan, I gotta know, who do you want to hear from at Shop Talk? Who are you excited about?

[Sne Parmar]

So there's a couple. Like, actually what was great about this is it made me really peruse the agenda and there are some things I'm really excited about and so I'm taking a few as touchstones for the more interesting idea that they're discussing. So really excited to hear Wayfair, I think the future. They're in this really interesting position to truly break down what the future of Omni or harmonized retail is because of this, hey, we were digital and now we have physical. What's that balance? I think a lot of conversations going on now about like, digitally natives and what their footprint should look like, what they should be doing in both channels and using those to their full effect. Super excited about that. There's a Soul Cycle section around. Around brand narrative and especially brand narrative within locations. And I'm really excited about that because I think, like, physical spaces for storytelling is super interesting. Something that I think a lot of people are starting to think about more as we talk about the widening of the store and what its purpose is. So how do I create these kind of lasting impressions and interactions? And I think that's. That's really exciting. Fab Fabletics is having this conversation about, like, staying ahead of the customer. Super. I think one of the biggest things we've been talking about in the last few months has been how rapidly the customer is changing and how different they look now than they did maybe five to 10 years ago. And so this kind of listening to how retailers are trying to grapple with that problem. And then last bit is like, there's that whole lane of experience and storytelling. And I think that combo to me is like, that's candy. I mean, I could do that all day. So those are like. Those are like, thematically with a few direct examples, the ones I'm really excited for.

[Ed]

Wow. And I didn't have Soul Cycle on my Shop Talk bingo card. That's a. That's a good drop from Ethan. Of course, that Wayfair. Because you're moderating that discussion.

[Chris]

I know.

[Ed]

But yes, I definitely had that one.

[Chris]

Yes.

[Sne Parmar]

But.

[Ed]

But Soul Cycle, that's. That's interesting. I have to check that out, see if I can make it. All right, Ethan, so. So one question we want to ask you is. I mean, you guys. You guys, like you said, you're pretty ubiquitous at this point. A lot of people in retail know you. A lot of people in retail use you. What are you like when people stop by your booth? What are you focused on in really making sure that they, you know, walk away with or understand?

[Sne Parmar]

I mean, it.

[Ann]

It's the.

[Sne Parmar]

My favorite thing about Shop Talk is that it's a stop by in this cool conversation. Like, it does feel like more so than almost any other event we attend.

[Ed]

Yeah.

[Sne Parmar]

People are. Are like discussing ideas there. Like all. Whether it's the Sessions, whether it's the person you're sitting next to, waiting online, walking through like the exhibition hall, taking the one on ones, you're having these really interesting conversations. And so for some folks it's like, hey, look, what are you seeing about how the consumer is changing? What does that mean? There's this conversation about, you know, convenience versus experience that we're like having a lot now with retailers and we're excited to continue having. And face to face is so exciting. I think we're also excited some of like, obviously, especially when it's customers or prospects, a lot of the conversation is around like, ooh, so when is sales forecasting coming and when is the new markets feature coming out and what might that look like? What problems could I solve? So there's this, I think the cool thing about, you know, like sounds like so cliche at this stage, but bear with me, like the pandemic taught us how fun it is to be with people in person. And I think like at Placer, like because we're a data platform and it's like you just dive in and look, going through those Eureka moments together with kind of your customers and your prospects and your colleagues and your partners. It's pretty awesome because you just get to go on this fun collaborative journey together.

[Ed]

Yeah. Ethan, I'm curious too. Like, you know, not to get buzzworthy but buzz wordy. But I'm going to like, do you, Are you also hearing people like ask you about Gen AI too? Like how is the platform adapting and changing to incorporate that? That's something that Anna, I've never talked to you about. I'm curious.

[Sne Parmar]

Yeah, I mean I have a very strong opinion about AI and it's, first of all, it's already been happening for a long time. So every cybersecurity, every. Many of the cybersecurity solutions, many of the data solutions that you've been using for years have been powered by AI were one of those examples. And so the idea of like it's newness, it's kind of.

[Ed]

Yeah, it's a weird name.

[Sne Parmar]

Yeah, I mean like it's, it's been happening.

[Ed]

Right, so it's been there for a while too.

[Sne Parmar]

Yeah, exactly.

[Ann]

Right.

[Sne Parmar]

But I think the, the thing that really matters for me is, is like I want us to take a collective deep breath as like every industry but certainly retail. And I, I don't want to listen to another session about like how AI is changing retail because I think it, we have the, there's like a phrase that basically we're asking which is like, you know, how where our focus is is slightly tilted. AI is an amazing technology, but technology is a means to an end. The question needs to start with what are the problems we're facing? So we have a personalization problem. How can AI, Can AI play a role in fixing that? We have a problem in keeping our stores clean. Can AI play a role? Probably not. We have a problem in making our website more engaging. Can Genai play a role? Absolutely, yes. So I think it's. I would just love to see the conversation start with the problem and then ask, is AI part of that specific solution? As opposed to saying, ooh, AI. How can we jam that into every conversation? I think so many of the technological misses that we've had are because we overemphasize the technology. We under emphasize the problem we're trying to solve.

[Chris]

Well, Ethan, if we think about some of those questions, I'm curious what some of the bigger ones are that the retailers that are coming to you are asking, like, whether, whether that's AI related or not. Like, what are some of the problems that you're hearing from retailers that they're trying to solve that are being prioritized right now over maybe some of those others?

[Sne Parmar]

I think when retailers are, again, this is the joy of face to face. When people are being really honest. They're, they're talking about the fact that they're struggling to have a really good finger on the pulse of how the customer is changing. They know their customer is different, they know their customer is shifting. They don't really know what's happening. And they are trying to get ahead of that, which is awesome. I think there's certain spaces where, you know, take this, take retail media, which is, I know, I know we all have talked about ad nauseam, but like, retail media has this, like, is at this kind of like Frostian road diverged in the wood, and it needs to decide if it's going to fix its problem or it's going to continue being like, all, all smoke and very little fire.

[Ed]

Also not on my bingo card, Robert Frost references, not on my bingo card.

[Sne Parmar]

But I think it's like, I think people are grappling with that a lot of like, hey, what's the real problem? Is it actually promised or is it kind of just another one of the, Is it going to go on like the heap of technologies that never lived up to the hype? I think a lot of the, the role of the physical space is dominating conversations like, how do we, how do we grapple with the fact that our store is now also a fulfillment center. It's. Should we be leaning more into Bopus? Did Bopus really work? Did it fade back? Like all of these, we're grappling with kind of what is in actionable, real insight and what is buzz and myth. And I think there's the cool thing about, about data is it. It tends to be less concerned with the hype cycle. And so it gives not the only perspective, not a360, but a perspective that at the very least is objective. And it's. So I think we're. The interesting thing is every retailer, every retailer, so many retailers are asking very different questions of like give you one example that I loved. We had one ask us how different does the audience look between two locations? And they had this hypothesis of like, we think it's fundamental. This is our guess of who it is. And they were kind of using the data to check that guess based on their merchant, what products were moving and how that was impacting merchandising strategy. So we love that because that's already like a layer or two beneath kind of the surface. And that's where things get really exciting.

[Purva Gupta]

Yeah.

[Ed]

And data helps you cut through the hype for sure. All right, so let's close it up. We've been asking everybody this. I know how big of a fan you are of Vegas, but what is your favorite thing about Shop Talk?

[Sne Parmar]

So my favorite thing about Vegas is the flight home. But my favorite thing about shop.

[Chris]

Ethan. I love the honesty.

[Alex Hazy]

Yeah.

[Sne Parmar]

I take me any place where the big attraction is a, is a facsimile of something that exists somewhere else in the world is the original.

[Ed]

Being on a plane for 14 hours, that's your favorite thing?

[Chris]

Yeah.

[Sne Parmar]

To see the. A fake fountain that actually exists in Rome. Right, Sorry. This is going to become therapy. Not a conversation. I like. My favorite part of Shop Talk without question is I think uniquely that event creates an on point conversation about things that people are actually discussing. And so the sessions feel more like real, like it's less polished. It's actually asking things about what were the real problems. And it's not just kind of a billboard. We're an amazing retailer and we are so innovative. It's, it's, it's going those levels deeper, which I love. And I think that filters out into the entire setting of the conference. So the conversations you have in the exhibit hall, the conversations you're having, whether you're getting it, you know, having a drink at the end of the day or you're waiting for lunch, or getting a coffee, it tends to go deeper, faster. And so I love that, that one on one interaction, the number of kind of like eye opening conversations I've had within the Shop Talk walls certainly surpasses most of the other experiences I have. And so that's always my favorite part is just to be able to really kind of leave the noise aside and actually have direct conversations about the issues we're all interested in.

[Chris]

That's amazing. Great answer, Ethan. Great, great comeback from a very downer approach to flying home from the conference with giving us all the real purpose of why you make that trip in the first place.

[Sne Parmar]

I feel like my new goal is to Get Shop Talk 20, 20, 2026 might be too early, but Shop Talk 2027, I heard a rumor it's going to be in Miami and then we see if we can spread that out and like force that hand. Apologies in advance, Hype group, the Zeitgeist.

[Ed]

Quote unquote, moving towards Miami.

[Sne Parmar]

Beaches, hot weather.

[Chris]

I'm 100% in favor of that move. Well, Ethan, let's talk about where people can see you quickly. If they are out in Vegas, they're at Shop Talk this year. What's the best way for them to connect with you to find out more about the data that you and the team at Placer are able to give them?

[Sne Parmar]

So one, we are at booth 866. Come, come hang out with us, come see us, come have a conversation. We're doing a session at 10:15 on Tuesday. Come, come check that out where we talk about tech trends. So come, come join us there and just stop by, say hello, ask me if I want to grab a coffee because I'm probably going to be exhausted. And I'll say yes, let's do that.

[Chris]

Just bring you coffee, bring you coffee and move to the front of Ethan's line because he always has a line.

[Sne Parmar]

Someone brings me coffee though, they'll be my best friend forever. Is that an exciting thing?

[Chris]

That's exciting and noted as well.

[Ed]

All right, well, thank you, Ethan. Thanks, guys.

[Sne Parmar]

It's always a pleasure.

[Chris]

Joining us next is Treasure Data's Chief Marketing Officer, Mark Tack. Mark, welcome to the show.

[Mark Tack]

Let's start with a little bit of.

[Chris]

Background on what Treasured Data does and your role at the company. What do you oversee?

[Alex Hazy]

Absolutely. So Treasured Data is an intelligent data platform. So a lot of people would know of Treasure Data as a CDP customer data platform. Treasury Data is one of the pioneers of the CDP industry. A lot of people don't know this, but Treasured Data was originally founded as a big data platform. So before Snowflake and Databricks and all these companies even existed, Treasured Data was managing massive data as a big data platform well before kind of the current wave of data warehouses came along. And then after about four or five years, Treasury Data said we should get, get on the CDP bandwagon. But that foundational big data platform is one of our secret sauce elements. And we really think that the whole market has evolved and has really expanded beyond just managing customer data. But was a big year for the industry and it was a big year for Treasure Data. However, AI came along and intelligence came along and in a matter of a couple quarters things changed really quickly. And so all of the foundational capabilities, the work we do with our customers to manage customer data, none of that has changed. The next big wave is around intelligence and we can certainly unpack that. But to us, intelligence is more than just gen AI. It's gen AI plus your customer data plus machine learning, plus personalization, plus decisioning, all to deliver incredible experiences that help businesses grow and achieve incredible profitability.

[Ed]

So basically what, what I take away from you is like you got to the whole enchiladas at play here and that, and that's the value of the, of the cdp, so to speak. And I got to think too, Mark, like the cdp. I'm sorry, the, the, the move towards AI has got to be good for you guys in general in terms of like CDP and growth for the industry, is that right?

[Alex Hazy]

Yeah, because the AI models out there, like open AI and all these others are great for public data. But what about your customer data? Right? What if you want to leverage Genai to run your business based on your data and Treasure Data manages all that first party data for the world's largest companies. So we really see ourselves now as the foundation for AI and a lot of our largest customers are working with us in that manner. Like Anheuser Busch is a customer. There's a case study on our website where Anheuser Busch abi talks about 90 million customer records in their treasury data CDP, 2000 data sources unified in their CDP and they're using it globally across 42 countries. So that case study is on our website. So you know, that's a pretty good illustration of scale. Yeah. So yeah, the AI movement has been huge for the business and I think most leaders now are recognizing the importance of having customer data that's feeding into AI so you can drive more relevance and more impact for your business versus just using generic open public inputs and Learning into the models.

[Ed]

Everyone always says you have to have a great cdp. So, you know, why is that such an imperative? And what is it about Treasure Data that sets you apart in that arena?

[Alex Hazy]

Particularly, you know, there's three key elements that we see as foundational for the intelligent data platform to really be meaningful for the business. One is you have to have the right data. And what we see in our customer base is it has to be real time and batch data. So there's a lot of customer data platforms that do one or the other, but there's very few that do both. And in a retail scenario where you're trying to align offline sales with online sales, and hey, this customer just bought jeans yesterday, but they're on our website today looking for a shirt, you need to have batch and real time data together to drive experiences that really move the needle. And that's something Treasure Data does really, really well. I mean, we talked about AI, like, intelligent data platform means that you have the AI agent framework, you have the gen AI, you have the machine learning, you have the predictability. And Treasure Data is really out in front of that doing some really cool things with some of these retailers. And then the last piece that I'll say around, how do you define an intelligent data platform? It's really the decisioning layer, and that decisioning layer is core to intelligence. In Gartner's Magic Quadrant Critical Capabilities Report last year, Gartner named treasure data number one in personalization and decisioning compared to all 17 vendors. So, you know, that just says that you're really going beyond data management and you're really driving intelligence. So those three things, I think when you think about like, hey, this term intelligent data platform, what is this? Is this just a fancy way of talking about a cdp? We actually think it's not. We actually think that the CDP sits on top of the intelligence data platform. So yes, Treasury Data is still a leading cdp, but we also see this new frontier, which is something bigger.

[Chris]

Where are retailers and brands when they come to you and they're saying, I'm having some problems? What are those things that you would call out for the audience?

[Alex Hazy]

Just think about it as the bookend problems. There's something at the very beginning and kind of near the end of a CDP implementation where a lot of retailers can get tripped up. So at the very beginning, before you implement the cdp, it's about getting really dialed in with your use cases in your business strategy. A lot of companies fast track that some don't do it. And they say, hey, we bought a cdp. We're going to pay our si a lot of money to go implement a cdp. We're going to work with a CDP vendor to get all our data engineered and, and plumbed in the right way. And then they got this beautiful Ferrari, they got this amazing cdp and then like, well, what are we going to do with it? Where are we going to drive? And unfortunately we see a lot of Ferraris that just get stuck in the, in the garage. Kind of like Ferris Bueller's Day off. You don't want that to happen, right? You want to have a very clear path of what you're going to do with the cdp, how you're going to drive value and what those use cases are going to be. It sounds silly and it sounds like something you would assume everybody does. Some don't do it and some, some pay the price. That, so that would be one. And that's like, that's booking. Like that's at the very beginning and then at the end it's all about change management. Right?

[Sne Parmar]

Okay, great.

[Alex Hazy]

We've got this Ferrari, it's ready to rock and roll. Now who in the business is actually going to use this thing, right? How are we going to change human beings behavior? How are we going to drive adoption? Right? You typically have a, like a Martech unit or IT or someone in the marketing team that's, that's super, you know, kind of technology and data focused. Those are typically the people that drive these initiatives, but they're really doing it for marketing and for the business to use it, right? So the team that's hired to kind of evaluate a cdp, build it, implement it, they always typically do a great job and then they get really frustrated when they have a hard time driving adoption. Right? How do we get the marketing team to actually embrace this? How do we get the sales team to use it? How do we get supply chain to use it? We have some customers that are trying to get HR to actually lean in on their customer data and really with AI. So for us we have, yeah, why not? We have a chat GPT, like chat layer that sits across the whole cdp. So in theory anybody can, can access and use the CDP now right? From the CEO down to an intern. Anybody who can use chat GPT can now use the cdp. So the whole like excuse of it's too hard. I'm not a data scientist, I'm not an engineer, I don't know how to use this. Those excuses are gone.

[Ed]

I love that bookend analogy, Mark. That's a really great way to think about it, it's great just for business in general, but particularly for a CDP implementation, it's a really good way to think about it. You got to get it right going in and you got to get it right coming out. That those are probably the two most important parts. All right, well, let's get you out of here on this. We've been asking everybody, what is your favorite thing personally about Shop Talk?

[Alex Hazy]

It's in retail. I feel like the more things change, the more they stay the same. The key themes that we had in a retail advisory board like 15 years ago, those are the same things. But what changes, of course, is the how and the why and the how do we measure it? Right. So we're trying to solve these, these kind of age old, I don't want to say problems, they're opportunities, but we're doing it in a fundamentally different way. And I think that that's really exciting because, because it's more of a how do we move from good to great? It's, it's not a starting from ground zero. It's. We know what we need to do in retail, but we have, we have new tools and new methods that are going to allow us to approach it in a completely different way. And as someone who, you know, does creativity for, for a living, I think that this whole retail landscape is just, it's like one big piece of art. It's like, let's rip it down, let's rethink it, let's start and let's just, let's just repaint this thing with new tools, with AI, with intelligent data platforms. And I think that's what we're going to see at Shop Talk.

[Ed]

Yeah, that's great. That's great.

[Ann]

Yeah.

[Ed]

It reminds me, Anne, of the conversation we had with the investor recently where she's like, we asked her about how is the store of the future going to unfold. She said, well, basically you got to drive more sales or cut costs. That's what the store, the future's got to look like. Right. That, that's all we're talking about here. Fundamentally. I love how they put it in black and white terms. And Mark, you got me thinking of that too. So that's great.

[Alex Hazy]

No doubt.

[Chris]

Awesome. Well, Mark, where can people find you if they want to meet with Treasure Data? They want to stop by the booth. What are the best places for them to do that? Next week at Shop Talk.

[Alex Hazy]

So our booth number, it's a long one. It's like a credit card number here.

[Chris]

There must be a Lot of pens and paper ready.

[Alex Hazy]

There must be a lot of, a lot of poos talk, right? It's 1412 A again. Our number is 1412 A and we also have 22 one on one hosted meetings that have been scheduled. And if you're on our schedule, great, I'll be there. Look forward to meeting folks. If you don't have a one on one meeting with us and you'd like to meet, obviously we would love to make that happen. And then we have a cocktail reception we're doing on Wednesday night at the Skyfall rooftop lounge from.

[Chris]

That's a classy spot, Mark.

[Alex Hazy]

That's a classy, you know, that's what we like to do. I like to, I like to be up in the sky here.

[Ed]

Get the ticket for that folks.

[Purva Gupta]

Wow.

[Alex Hazy]

Reach out on LinkedIn. It's the more the merrier. My marketing team may, may not be happy at me for saying that, but. But I think it's the more the merrier. So stop by, we would love to see everyone and can't wait to meet up in Vegas.

[Chris]

Excellent. Thanks so much.

[Ed]

Awesome. Thanks, Mark.

[Ethan Chernovsky]

Thank you.

[Alex Hazy]

We'll see you.

[Chris]

Joining us now is Miracle's GM and CRO, Alex Hazy. Alex, welcome.

[James Toyakov]

Great to be here. Thanks for having me.

[Chris]

Well, Alex, let's start out by just giving our audience a little bit of background on you and Miracle, if you don't mind.

[James Toyakov]

I have a prior history with a whole bunch of different software companies that have been focused in retail and the CPG space. So been enjoying my stay with Miracle. Learned a lot and the company's been going through a lot of changes as of late.

[Chris]

And tell us a little bit about what Miracle does for those who might be meeting you for the first time.

[James Toyakov]

So Miracle has historically been focused in what's called marketplace segment, which essentially is any e commerce retailer that it wants to allow third party sellers to sell on their site to complement what they're currently selling. We essentially have software that enables that. So everyone's familiar with Amazon. That is purely a marketplace. This is for other retailers to be able to apply a similar business model.

[Chris]

Excellent.

[Ed]

So Alex, I want to start out by giving you a little bit of kudos because Miracle, you all have been in the news quite a lot recently like Best Buy and Janie and Jack come to mind from me. So many new companies appear to be looking to, particularly Miracle, the stand up marketplace platforms. Why is that? Why are we seeing so many companies dip their toe into these waters?

[James Toyakov]

Yeah, it's a great question. In fact, there's been. Not only has there been a lot of press, just wait until you what you hear over the next six to eight months because there's some going to be some really big announcements with some other significant retailers that have also decided to pursue this as part of their strategy. And essentially, I think there's been a big shift from general merchandisers, you know, retailers that we've been working with for a while, like a Sax, a Macy's. And we've seen two themes that have really started to unfold that have expanded the portfolio. One of them is around specialty retailers. So whether it's within consumer electronics. So Best Buy is a recent example of that. Health and beauty, the DIY ecosystem, footwear, those vertical oriented retailers have actually found that marketplace is very complementary to their strategy. So we're seeing a lot of expansion there. The second, and again there was an announcement around a retailer called Janie and Jack. They're kind of a mono brand. Right. They're known for their own brands, but they're effectively trying to expand their strategy to service all the needs of their consumer and they want to do it all in one place. And so they've seen great success right out of the gate.

[Ed]

And so Alex, but what is the. That makes sense. But what's the rationale for them doing it? Is it the expanded assortment? Is it, you know, something else? What is the rationale that they're relying on?

[James Toyakov]

Well, so there's a couple of different dimensions. One of them is that it's capturing the audience, capturing the consumer, you know, part of the overall value proposition, but a part of it is also just expanding the volume or assortment of products, which then more consumers drives more traffic. Obviously there's a revenue and a growth story associated with that just on conversion of that commerce. The second part of the equation though is around retail media. So what's interesting, and again this is quoted in a recent Best Buy article, is that the opportunity for retail media goes up dramatically when you have a marketplace. So the two are very complementary to one another. And we've even evolved our strategy from being hyper focused on marketplace. We did expand that into a dropship solution, but then even beyond that, a retail media platform so that we essentially can help the retailers capture that opportunity.

[Chris]

Yeah. And Alex, let's dive into that a little bit more. Like what does it look like to first put a marketplace in place and then how does kind of retail media become support of that? Or like how do retailers kind of get that funnel up and running?

[James Toyakov]

Yeah. So again, the whole notion of a Retail media strategy is taking advantage of the potential, the advertising potential. Right. And I always look at it through a couple. Well, I look at it through three different lenses. One of them is through the lens of the retailer. Right. They have this inventory on their sites, it's available and you know, there is an opportunity to monetize that. And again, we've read all the articles about Amazon and Walmart and others doing it quite effectively. It's essentially applying that same model. The second part of it is the consumer, right. So by running ads that are relevant to them and assuming that they're personalized, the consumer wins because they get exposed to products that they might not otherwise have known existed. And then the third is the brands themselves now have exposure and opportunity to invest in that advertising, therefore being able to expose products that they would like to for those consumers.

[Ann]

Yeah.

[Ed]

So essentially what you're saying, Alex, is that there's the expanded assortment opportunity, there's the traffic that you get to the website, and also the additional revenue that comes as a result of that. But then there's also the retail media play, which I think is important to put a pin in. Because one of the big unlocks for me when I was running E Commerce was just how much advertising can scale across your assortment because the assortment is so large, so you have more items with which to advertise and to drive traffic and revenue from. And so that's an important piece of, of this whole equation. So it makes sense that you guys are seeing the success that you have. And the other part too, Alex, that I want to touch on real quick is don't, don't you in, in and of itself, by being the platform, also make this whole concept easier than it was say 10 or 15 years ago. Isn't that partly why Best Buy is trying it again?

[James Toyakov]

That, that's absolutely right. And, and again, you know, part of the constituents of this marketplace model are those third party sellers or the brands that actually are through this model selling on that E commerce site of the retailer. And so what we've done is invested quite significantly not only in the ability for them to facilitate the process of onboarding products, the catalog, onboarding, all of the merchandising that is associated with that. But within the same platform, they can actually make the investments, the retail media investment, so in ads and they can run their own campaign. So instead of hopping from system to system to system, you actually in one place can not only deal with your, your assortment strategy, but in conjunction with that, be doing your retail media as.

[Chris]

Well, which I Imagine, Alex is also helping support, you know, what would be the work at a retailer of the equivalent of, I don't know, four or five teams, a retail media team, a marketplace team, a procurement team. Like, you're kind of taking that all into work. One department that can run a marketplace.

[James Toyakov]

That's exactly right, yes.

[Ed]

The other point that I never thought about, Alex, too, which you just made think about, is the digital landscape and the tools available to startup brands and startup entrepreneurs to take advantage of systems like this didn't exist 10 or 15 years ago either. You think of, like, you know, all the different systems that enable people to stand up websites and start selling product and everything that they can do. So that's a whole unique wrinkle to this that I never thought about. So that's great. All right, if you could leave our watchers or, or the Shop Talk attendees with one message while you're out there next week, what is it going to be?

[James Toyakov]

From my perspective, it's. It's explore and learn and understand how retail media and marketplace can fit into your strategy. And I'm speaking obviously to retailers, but the reality of it is, and this is what we've experienced over the past 10 years or so, is there's been this progression of learning and understanding. And that's where, you know my comment about the specialty retailers now understanding where it fits, you know, if you went back six, eight years ago, it was just dismissed as well. We'll never do a marketplace or retail media. That's for the really big retailers. The reality is that's actually not true. And so my advice to people would be learn, explore, dig in and, and define what your strategy is, even if your strategy is to not execute or have a strategy, if you will. And I would also advise that there's a lot of companies out there, in particular the strategy consulting firms, that have done a lot of great work with these retailers and can help you really get grounded on a lot of the things that we've spoken about today.

[Chris]

All right, Alex, this has been amazing. We're going to close out with one question for you. What is your favorite thing about being at Shop Talk?

[James Toyakov]

It's not because it's in Las Vegas, I will tell you that. However, I would pick a different location, but I've always really enjoyed. There's a great energy there, the people that are there. There's obviously a ton to learn. And so if you're listening and participating in the event in its entirety, you actually get exposed and can pick up a lot of interesting tidbits along the way way. And then we also love, it's a great opportunity to reconnect with our customers and then, you know, prospects and people that, you know, we were in some capacity already engaged with. So I will leave you with. We do have a booth there and it's booth 1746. And we would certainly welcome having a conversation with anybody that's interested.

[Ed]

Awesome. I was just going to ask you that, Alex, but I'm curious because we've had a few people that we've interviewed say that they'd love it in a different location. I'm going to put you on the spot again. If you were to have Shop Talk in a different location, where would it be?

[James Toyakov]

Well, so I was talking to one of our partners recently and he was heading off to go skiing in St. Anton. So I think that would be a lovely place for Shop Talk.

[Chris]

Oh my gosh. I don't even know where that is. Yeah, is that in the Swiss Alps or something? Yes. Okay, sure. Yes, yes and yes.

[James Toyakov]

I'm reacting because that's what's in my mind right now.

[Ed]

I want to go see.

[James Toyakov]

Yeah.

[Ed]

A stone's throw from Miracles Paris headquarters. All right, well, Alex, thanks for joining us. That was really great. Great. Thanks for giving us the rundown on, on what marketplaces are and, and why so many retailers are finding them so interesting and, and diving into them quite frankly too. So we're excited to see you at Shop Talk next week and of course, travel safe and stay well until then. Man.

[James Toyakov]

Thank you. Appreciate it. Thank you for having me.

[Ed]

Joining us now is Signified's co founder and CEO Raj Ramanand. Raj, welcome to the show.

[Ethan Chernovsky]

Thank you for having me. Excited to be here.

[Ed]

Let's start off though, give our audience a little bit of a refresher on what Signified is and as well as your background too. We always like to get to know our guests a little bit when we can.

[Ethan Chernovsky]

You know, I've been in the payments, retail and risk space for about 25 odd years. I started my background on the retail side with FedEx Corporation on the logistics elements of it. Learned a little bit logistics and fraud over there, then moved to the Bay Area to run emerging markets risk at PayPal that time. Emerging markets back in the day was Latin America, Middle east and Africa. I don't know if it still stays that way. Learned a lot about payments and fraud at that point in time and then branched off to start signified back in 2011 with my co founder Mike Liberty, who actually ran digital goods risk at Paypal at that time, it was an interesting time. We learned a lot about the space through those different journeys obviously. But one of the interesting things that was happening at that time, this was back 2011, if you recall, mostly everybody at that time in retail were focused around reducing fraud. And you know, in, in, in, in the retail space online, when somebody buys something, the merchant always is liable for that. You know, most people, an interesting tidbit of information, but obviously what that meant was because retailers were liable for that fraud, they were putting in these protections in place that effectively blocked the, you know, the good and the bad. And while reducing that fraud, they ended up actually turning away billions, billions of dollars of good transactions and good people who were trying to buy. So this was, think anywhere from, you know, it could have been a 1% for some of the really large potential retailers and some of them declining 15, 20% of their top line traffic. And that was where the opportunity came for signified. We saw this massive opportunity in saying instead of focusing on using AI to just protect the bad and help retailers reduce their fraud, what if we could turn that around and use AI for good, which is to be able to approve more and more of these good users such that you could drive growth in the top line from 2% to 20% depending on how much you could approve. It was the genesis of that. And that obviously built on a lot of other things we've done after that, which is protecting the entire customer journey in each of these sort of risk elements, not just at the checkout layer.

[Ed]

I think two things from what you just said. One, I find the idea of, you know, finding the, the hidden dollars in, you know, really understanding fraud inherently interesting. But then two, 25 years in payments, that means you're a glutton for punishment I think as well. So, so what is it that you find? So what is, what is it that you find so exhilarating about the space?

[Ethan Chernovsky]

I'm curious, when you think about businesses in general, they're the amalgamation of a lot of decisions people make across many, many, many different facets of the business. You know, it could be I'm going to launch this promotion in retail today and that's going to drive this elements of my business. I'm going to launch this new product line, I'm going to launch a new geography that's going to come out. I'm going to make tweaks in cost reduction and how I'm going to monetize my existing customers better than just acquisition of new customers, customers, all of that business decisions that Happen in this, in any sort of retailer today ultimately boil down to how you operate the underlying aspects of the business, whether it's logistics, whether it's payments, or whether that's risk. Without the combination of this three, the logistics side of it, the payment side of it, and the risk side of it, all of these decisions can't be executed against.

[Chris]

But I'm curious what you feel like the biggest issues plaguing the retailers and brands that you talk to now are what. What are they focused on?

[Ethan Chernovsky]

The biggest thing that's happening in the space right now for retail is tied to the concept of returns. Okay, deal with this in some shape or form today. You know, where we buy something and we return it. And for the most part, we're all good people. We're not trying to abuse the system. But returns is now a $890 billion problem globally. And if I'm a retailer where I sell something and then have to figure out how to adjust my books or forecast these returns, you literally are saying that everything I sell, there's an x percent of that. Depending on the business in say, fashion, it could be 30% of everything bought online is return. You, as the retailer, have to deal with all of that. It comes down to how do you monetize that consumer again when a return happens? And then the second problem that people are trying to deal with is how do I make sure that the customer experience is really good when they make that return, such that the loyalty or the lifetime value of that customer sort of is sticky enough? And there are lots of risk problems or fraud problems that sort of drive this whole thing. But those are the two real big issues we're seeing in retail around returns right now.

[Ed]

What do you predict are some of the big changes that we'll see retailers try to make to achieve more profitable growth?

[Ethan Chernovsky]

Let's take the two examples. I'll take the first one, which is all about when you buy a pair of shoes. Let's say you buy a pair of shoes and you it doesn't fit just for the sake. And you want to return that pair of shoes. When you return that pair of shoes Today, it takes seven to 20 days for most retailers to put the money back on your credit card right now. It's not that the payment rails don't exist to put that money back on your credit card. The payment rails exist. They could put it back tomorrow if they wanted to put it. But the reason they hold it is because they have to wait for you to send those pair of shoes back. They have to open the box. And they have to make sure that the shoes that you bought is the shoes that you return, you didn't return like a stone in there. And, and that process, to be able to do it takes it from the time you ship it. It needs to go to a warehouse, somebody needs to open it, they have to validate, put it back in a system, and then they put the money to come back on your card. But ultimately, what's happening is there's a. It's a trust issue, right? Like, do I believe that you're going to send me that pair of shoes back? But if I could tell you at the point of return that when you initiate that return, even before you ship it, that, hey, you will return that. And I put that money back on your car card instantly. What we found is that buyers tend to buy somewhere in the range of 20 to 30% of the time more again with that retailer at that point itself. So you effectively don't go back and reacquire the customer simply because they got that money back instantly. And that's a big deal, right, because reacquisition cost is pretty expensive. So what's happening in the market, you'll see is that more and more retailers are going to realize that this concept of instant refunds is going to become the norm for the future. And there are a few great retailers who do that. We work with them and we sort of. We can get into more of the details of how we do it. But. But ultimately, if you can give that money back instantly to the customer, then you effectively have that repurchase rate to be higher. So I think that's going to be one thing that people are going to do in the future, and it's going to be over the next 12 to 24 months, a high adoption of that. And so then the second one, which, you know, I talked about this $890 billion problem. Every retailer has returns. It's a natural part of the business. But there's more obvious issues in avoidable returns that can be avoided. Let me give you an example. You know, people do promotions all the time at retailers. These promotions are being done by the marketing teams, and they do things like, hey, if you buy $200 worth of product, we give you 25% off. These promotions from the marketing team are disconnected from the operations teams. But what happens is that I, as the consumer, just like, wow, I'm going to get a 25% off. I buy $200 worth of product. I keep the one thing I want from that 200, say I buy four things, I return three, but I get to keep my discount. So I could have avoided those returns. Right? The three things that you returned to me, you're a good buyer. You were just trying to avail the discount. But I could have avoided those three things because I knew you were trying to avail that discount, but you bought four because you got the discount. There's a disconnect between the top of the funnel, where marketing is running programs, and the operational elements of how people have to deal with the messiness of returns. And if you can connect these things together, you can avoid a lot of returns. And that 890 billion doesn't have to become about penalizing the customer, saying, I'm going to charge you seven bucks for every return. Then there are lots of good customers who are never going to return. And paying seven bucks versus finding ways to just avoid the return in the first place by doing the right things, connecting the top of the funnel, the front end with the back end.

[Ed]

So, Raj, I'm glad, I'm glad we had to do the second one because the first one I can conceptualize, get my head around in terms of, you know, how you can understand the consumer. That's, that's, you know, returning the product and whether or not you want to give them an instant refund, you know, by applying technology to help you, to help you understand that. The second one's a little bit more complicated to me as a former retail executive. So, like, how do you see, how do you see technology bringing that, bridging that gap between marketing and operations? In actuality, because it's a hard problem to solve.

[Ethan Chernovsky]

I, I wouldn't discount the fact, and it's a good question. I wouldn't discount the fact that this is a hard problem and that's why it's not being solved. Right. It's, it's thing. I think the way to think about the problem is more about a visibility problem before you can solve the problem.

[Ed]

Okay.

[Ethan Chernovsky]

I think solving for the visibility is a pretty powerful thing in our industry right now. Most people who run returns teams, you go and talk to any retailer, you go into any one of them, they now have returns. VPs just kind of sit there and looking at how do you deal with returns, what do you do to manage costs. And most of them, if you really look at what's happening in the space, are really optimizing their logistics costs, right? They go in and negotiate their price with UPS and FedEx and that's really what they're doing. And they're doing other things. There's a lot more. But that's sort of where their prime focus is. I manage a big vendor and contracts and I'm going to negotiate prices down and I keep kind of getting my costs down. But ultimately what they're missing is their mission control. Like one place to look and understand what are all the reasons for my returns coming in? How do I look at the different types of the returns? What is causing these returns to come in? How do you connect the dots between. Between buyer habits and what's happening? How do you look at that consumer outside of my network and know are they typically doing a lot of these types of promotional abuse or loyalty abuse? Do they like to wardrobe? Do they like to bracket? You know, you can understand the holistic that consumer and if you can understand the different patterns happening and you say these are my top 10 reasons for how I can avoid the return from happening. Now you start putting solutions in place to be able to reduce it. But I think if I were to zoom out and answer your question, I think the VP of return that's optimizing logistics, contracts and doing other things doesn't have their mission control where they can understand how to avoid these returns. And there's lots of pockets for opportunity in this space.

[Chris]

So Raj, is that where you would say then that because of AI being a part of this experience to kind of gather all of those touch points and put that into one dashboard for the VP of returns or whatever executive might be in charge of kind of managing or overseeing this process? Is that where AI is really making this experience better for the consumers and better for the business? Bottom line?

[Ethan Chernovsky]

That's exactly right. One of the most powerful things that's happened in the space over the past 10 years is that the amount or the explosion of consumer data is pretty high. But also it's not just about the transactional elements of the data. It's everything pre transaction. How long does someone spend on your return policies before they buy your buy your product? Like if someone, we found if someone has spent a lot of time looking at your return policies before they buy something, they're most likely not going to return.

[Chris]

Interesting, right?

[Ethan Chernovsky]

Like they're most likely not going to return because they've really thought about what this is going to look like and done it right, there'll be cases people return. But. But how do you take that data that's happening pre transaction even before someone click checkout and use that in your intelligence to how you tailor the policies for your returns? Could be a very Interesting thing that happens. You then have the checkout data, which is everything about what someone's purchasing, and then you have all the post purchase data that's happening in the world today. How frequently does someone return? Why did they return something? What are the return reasons that come with it? Normalizing those return codes across all of retail is very hard to do. And tying all that together and so where AI plays a massive part is bringing all that together and building predictive elements to be able to say with certainty, I think this person is really good. You may think that they're a first time buyer for yourself. You may think that this person is looking abusive, but they're actually not. They're really good people. And if you follow that journey almost from the time someone lands on your website all the way down to when they return something and you've gone through the elements to connect that journey, you effectively now have a very predictive way of saying, this is how I should treat my customer, as opposed to this one size fits all of how you treat them. You use AI to be able to tailor that experience to, to the end customer.

[Ed]

The way you just described that was really great. I mean the way, I mean the way I'd summarize it is really like knowledge and data is power to understand, you know, how you want to approach your end consumer at the end of the day and what services and experiences you want to offer them. So. All right, well, with that said, Shop Talk, we're all getting geared up for it. What is your favorite thing about shop Talk, your favorite thing to do while you're out there?

[Ethan Chernovsky]

So the biggest thing I enjoy about Shop Talk, and I'm sure most of my peer group does as well, is that it brings together the most elite minds thinking about the future of retail in one place. I mean, I'm sure you feel the same way and the energy that comes from that and getting to meet those people and hear about what different businesses and what verticals in retail are doing about the future and being able to tie that together, I think is the most powerful part of that. And obviously just to be able to hang out with your peer group that, that you've known for a long time, I think you, you don't get those opportunities in big groups often. And so I, I typically like that as well.

[Ed]

Nice. So it's not the blackjack table, Raj. It's not the blackjack table, but he'll.

[Chris]

Admit on this session, not the drinks.

[Ethan Chernovsky]

Not the black, none of that. But my co founder would like the, the blackjack he was a professional blackjack player at some point in his life.

[Sne Parmar]

So he was.

[Ed]

Oh, my God. Professional blackjack player. Wow. I didn't know there was such a think. Oh, that's crazy.

[Alex Hazy]

Yeah.

[Chris]

Well, thank you so much, Raj, for taking the time with us today. Before we let you go, what's the best way for people to connect with you next week when they're out at Shop Talk?

[Ethan Chernovsky]

That's great. So we do have a. A strong presence there at Shop Talk from Signified. You can find us at booth 1906 on the floor.

[Chris]

Perfect. Sounds good. Thanks so much, Raj. We'll see you there.

[Ed]

Well, that wraps us up today, and we're thankful to all our guests and to those of you who are able to join us live today. And to those listening on their way to Shop Talk, we'll be heading out shortly ourselves. And you can catch our full live coverage of Shop Talk, brought to you by Meta and Avalara beginning Tuesday next week and available to you on LinkedIn, our YouTube channel, at YouTube.com omnitalkretail or wherever you get your podcast. So until next week, out at Shop Talk, as always, be careful out there.