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A
I'm Mark Hardy with Walmart Data Ventures and you are listening to CPG Guys Podcast.
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Hello and welcome to the CPG Guys Podcast. Set at the intersection of commerce and tech, your hosts, Sree Rajagopalan and Peter V. S Bond explore how brands and retailers engage consumers in a digitally driven world. And now, here are the CPG Guys. Hello and welcome to the CPG Guys Podcast. I'm your indomitable co host pbsb and I'm joining you after a few days in Northwest Arkansas. More about that shortly. My co host, Papa Raj, patriarch of the Raj family media empire, is not with us today. But do see the digital show notes of this episode so you can follow us pop star daughters Ria and Lara on social media. They have got millions of followers. At this point, I am incredibly envious. If you haven't done so already, follow us on your favorite podcast listening platform and also leave us a rating on Apple or Spotify to help make our podcast more findable by your industry contemporaries. Now, as I mentioned earlier, I returned in the wee hours of this morning from the business trip to Northwest Arkansas. I had been invited by the terrific team at Walmart Data Ventures to attend the 2025 Inspire event. In its third year, Inspire brought together an invitation only group of now 1500 attendees representing over 300 companies across not just the US but three markets including Canada and Mexico, to hear about the rapid state of innovation around Scintilla and how it's helping subscribers to this service significantly outpace those companies not availing themselves of of this important commerce accelerator. So who better to join me for this episode to help recap and deconstruct all of the outstanding learning from the event than the head of Walmart Data Ventures himself. Please join me in welcoming back to the podcast for his second appearance only three away from the coveted five Timer jacket, the Senior Vice president and head of Walmart Data Ventures, my friend Mark Hardy. Mark, welcome.
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How are you?
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Really well. And Peter, thank you for having me.
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Listen, I am the one who has to thank you. You and your team were so kind to invite me down to Northwest Arkansas for this year's Inspire event. We're going to talk a little bit about that before we get started. I want to advise our audience to check the digital show notes of this episode. We're going to have links to Mark's LinkedIn page, the Walmart Data Ventures LinkedIn page and their homepage so that they can learn a little bit more as we go go on with our conversation. So what do you say Mark? Let's get inspired, shall we?
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Let's go.
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All right, so, Mark, as I mentioned earlier, I had the distinct pleasure and honor of joining you and your team for the 2025 Inspire event that was being produced by Walmart Data Ventures. Why don't we just start by letting you give our audience little context and remind them what is Walmart Data Ventures at its core and why is it? And the impression I got, it is really playing a very pivotal role in shaping the future of data and innovation at the world's most elite retailer.
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A
Yeah. So the remit for Walmart Data Ventures is to create value out of Walmart's data, and that has a pretty broad range. And, and an example may be working with data between Walmart, its suppliers and third parties for workflow efficiencies down to the store, retail to store operations level, all the way to another example, which is what you saw at Inspire, which is Scintilla, which is a insights ecosystem that allows collaboration between suppliers and our merchants as well to really put the customer at the center of decisions and help develop the right strategies, the right ideas that puts Walmart as the favorite place to shop in America.
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B
Thank you for that, Mark. That's very helpful. All right, so I'm just going to get right in and say there were so many things that I experienced during Inspire that I really want to. Want to get to now. There are a couple stats I want to share with our audience. First, this was your third year of running Inspire. You had 1500 attendees. They were representing over 300 companies, and you had expanded from the US into three markets, adding Canada and Mexico to your remit. Those are pretty big numbers. And you did that all in the course of adding Canada and Mexico and all of the enhancements you made. That's all a full year of innovation. That's a lot to tackle in one year, wouldn't you say?
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Yeah, I guess we don't let Moss grow under our feet here. We continue to move pretty quickly. Again, we continue to expand. This past year, we renewed 100% and grew by another 50% our client base. So we continue to grow. And again, our clients and our merchants are gaining value out of the system. And that's what really allows us to grow, allows us to think different, because we're constantly taking in feedback from our clients, from our merchants on what they need next to be able to make those decisions. And we actually, that value come right back to us to both.
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B
And you highlighted some numbers in your keynote around that. You said, you obviously said 100% renewal and you added a really important stat that was about the performance that Sentinel is delivering around those that are subscribers and, and those that are not subscribers. How are the subscribing companies outperforming those that haven't entered into the leveraging Scintilla for driving business decisions?
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Yeah, for the first time we're reporting on that difference. And what we have seen is that Scintilla subscribers are growing GMV 15% faster than non subscribers. And that really comes to the heart of this, which is an ecosystem that's driven to give you transparency and visibility. And we've democratized this data so it doesn't matter the size. As you saw in the room, we had everything from the largest CPGs in the world to some very small mom and pop shops who are innovating with the data. And that allows anybody and everybody to step up to the table and have the conversations with Walmart to bring their ideas forward.
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B
So last year at Inspire, you introduced the new branding of your tool Scintilla. And this year you announced the Scintilla Insights model. Now I was very intrigued by this Mark. This was really appealing to me. Can you talk about the four components of it? Kind of the attitudinal consumer insights, the behavioral component, how that can enable sales performance that lead to specifically desired business outcomes. What is that continuum and how do you see that? And Scintilla being at the center, the Insights model being at the center of that activation.
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Yeah. So at the end of the day, we're developing tools and bringing data to the forefront and putting it in the hands of all our stakeholders. That is exciting. However, there's a gap and that gap is around skills. Typically in companies including Walmart, we have subject matter experts sitting in different groups. And when you look at the ecosystem, we pull together what it allows. In each module is each one of those subject matter experts to access that data to do the roles the that they need to do. But what is really the value that's coming together is by being able to connect those dots and be able to see that broader picture. In order to do that, our clients have been asking for our help to upskill their users as well as internally at Walmart, being able to teach our users on how to use that data. So we developed a framework called SIM or Scintilla Insights model. And it's pretty simple. We start with a consumer mindset that then which is attitudes, perceptions, preferences. So what? How does a consumer or a customer think? What's on their mind? That mindset then shapes the behaviors. What are they Going to buy, where are they going to buy it, when are they going to buy something? That then leads to performance and performance is sales. So are we driving sales? Are we not driving sales? So using that model in each one of the business outcomes that we want to achieve, whether that is driving incrementality in advertising, whether it is changing or redefining a category or optimizing an aisle, whatever the outcome may be, using that same framework to think through what are the opportunities, what are the gaps is what we are now starting to release within Scintilla Learn, which is a library of learning certifications, learning modules and other videos that allows us to upskill our users. So it's not just about providing data and tools. It really is about helping people become more sophisticated at the analytics that that they need to perform as they put the customer at the center of all their decisions. Historically we would just take our supply chain data or our point of sale data, so sales and inventory and try to figure out what our forecast is, try to figure out what is the business problem that we're trying to solve and how do we best solve it. That didn't always start with a customer. Through Scintillo, with a ecosystem that we have built, we can actually see the journey of the customer from the home to the store, whether it's digital or physical. But we can also see that journey of the product right from source all the way to sort to which brings us to that point of conversion which is a shelf. If we can understand what motivates that customer to pick that product and put it into the basket and then walk out the door, we now can be better prepared at serving that customer. At the end of the day, it takes us from being reactive to being proactive about making sure we have the right product in the right place at the right time. And at the end of the day, it all goes back to how this world has evolved. So Walmart was great at bringing convenience to customers when we launched the Super Centers because it was a one stop shop. But at the end of the day, you had to plan a trip to that store. And if you think about our lives today as consumers, remember, right, we're very busy. We need to make sure that we as Walmart fit into the life of the consumer and the customer. It's not about trying to make the customer always fit in, fit us in, right. We have to flip that game and that's why we have that digital first strategy which doesn't matter whether it's the physical store or online or our app. It's about letting a consumer shop the way they want and us making sure that they have a great experience. We delight them on their experience so that we fit into their lives.
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B
Thank you for that, Mark. It was interesting you just mentioned digital first when you were talking with David Jagina on stage, the EVP of E Commerce. He said it's not so much digital first as it is customer first. You are recognizing that digital plays a very important part in how your consumers and your guests conduct their lives. And so digital first is by definition therefore customer first. So I thought that was really impressive. So there's a lot to unpack here because there's also some parallels. You talked about the Walmart Sooner Supercenter being that one stop shop where you can get all your stuff done. One of the things I also heard you talk about on stage was you wanted to make Scintilla the single place where you could get everything you needed, everything in one stop. You didn't have to bop out of one application to go into another. We think about the legacy of all these different tools. Attitudinal tools, behavioral tools, POS tools, inventory tools. You've unified everything. How does that make it easier from your perspective for your subscribing suppliers to actually access the information and affect their ability to speed a decision into activation?
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As we think about our platform, right, and having one ecosystem where all those different data sets reside, we provide some ease of use because everything's in one location. But that still does not answer the question because it still is putting the cognitive load on the user. So what we continue to try to do is to use AI and other data science approach to take the data and start reporting out. What do you need to know about your business today? Therefore a user when they come in. So for example, in Shopper Behavior, one of our modules we have just launched, Performance center, when a user comes in, it already tells them what is their status of their business, what are some of the key highlights of their business. We will continue to launch applications like that that helps the user connect the dots across all these modules. Along with that, we're launching, beginning next year, Data Companion. We just talked about sim. You know, part of our challenge is upskilling our users. So at the beginning of next year we're going to be launching an AI driven companion that helps a user understand metrics. How, how to apply the metrics, how are the metrics calculated? Because now the breadth of the data that we're going through again as I mentioned earlier, may have been common for different subject matter experts. But when you're trying to manage an entire business and look at all this data in one place, you may not be familiar with that. So that is a digital companion that will leveraging AI that will help our users upskill themselves. We're also looking at launching in this coming quarter. Right now AI driven tools such as our research summaries, where we can take our survey data and it produces the insights automatically at the end, fully driven by AI that will help our users as well bring this data together and understand the so what from the insights they're seeing. So ultimately what we continue to do is to take the different modules that we have developed over the last few years and start bringing the data together and helping our users connect a dot. Leveraging AI at times, but also helping our users upskill themselves. Because it is a parallel journey of both us adding more data, more tools, leveraging AI but at the same time users are in there need to understand what they're seeing because at the end of the day it's up to the user to ultimately make a decision. So they need to be able to interpret what they're seeing the right way. And it's all about bringing speed to this process. So it's about bringing speed to take data to Insights and then speed to take Insights to activation. And I think one of the great examples of that second step is when we launched Insights Activation, which is an always on recommendation engine that's looking at shopper behaviors and how shoppers are changing what they are doing. And that is highlighted once you go into Insights activation. In recommendations by brand that allow a supplier to understand based on their marketing strategy, you have an opportunity for customer acquisition or customer retention because we're seeing customers leaving your brand. Or do you have an opportunity to build awareness around your brand and all that is recommended? A user can go in, look at the recommendations. It actually tells you how we got to that recommendation. And if a user wants to then activate it on the touch of a click, they can now send that to Walmart Connects Ad center where then it can get activated onto Walmart. So that's how we are sitting here looking at how do we accelerate that process of taking what used to be data, converting it to Insights and then accelerating that insights back into activation.
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I was really blown away by the Insights Activation module. The fact that it proactively, it analyzes your business and it tells you what you need to do, but most importantly it shows the homework. How did the tool get to that conclusion? It's not just some black box. It actually shows you the methodology based upon what you're trying to achieve. It came to those recommendations that's so incredibly powerful because you know, the person who's using is going to have to articulate that to other, other stakeholders in the organization in order to move forward. So that's really good. I'm the one, the one thing I want to talk about is I want to double click down on the first module, the customer perception module, because that one really, really got my attention. And here's why you brought up a fellow from Data Quality Group to talk about how important data quality is in attitudinal research. So can you talk to us a little about what is the Spark community? How is it that at the center of customer perceptions and why? What has been the unlocking insight about what, what Spark and Customer Perception offers through Scintilla that's fundamentally different and frankly substantially better than any of the more familiar attitudinal research houses that you and I have been in this industry for quite a number of years that we've experienced. What is so game changing about this?
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Yeah. So from the beginning, what we understood is that we need to start with a customer's mindsets. As I mentioned before, if we understand mindsets, we then can help understand behaviors and help predict. Right. If we're ultimately moving to a model, we can be more predictive on what's going to happen. We need to be able to start with mindsets, which means survey research. Historically, survey research was used as project based. You engage in a project, you might get your results in 12 weeks and and then you have a static PowerPoint deck that hopefully answers your question. What we're trying to do is take that same methodology and put it into a more agile fashion where you're capturing the voice of the customer on a continuous basis so that when a supplier and a merchant are collaborating on ideas, we're starting with a customer. And that customer helps us understand how they're using a product, why they're using a product, why did they make a buy, when is that product important to them? How are they thinking about a product which is critical when we start thinking about innovation and renovation. It is critical when we start thinking about experience and ultimately if we can start bringing to this these innovations and renovations to market. Within Walmart, we're earning the delight of the customer, we're earning the trust of the customer, that we are America's favorite place to shop. So we are focused on how do we bring that type of methodology, capturing that voice of the customer in A very agile way into our insights process. In order to do that, building the tool was one step and we have it in a model where it's do it yourself, do it with me or do it for me. Because we have a research services team that can help our clients in that journey. But those are tools and those are services. We have to start with a customer. So we built Spark Community which is an imitation, only double opt in community of Walmart shoppers. When they come in, we actually know who they are so they're verified. And if you think about the different panels that exist out there, they're not always verified individuals. So when we look at it, we engage the third party company which you mentioned, which is the data quality co op and their CEO Bob Fossen led the presentation. We engaged them because we wanted to benchmark ourselves versus the industry and have a third party do it. And it was interesting when they came back. And a couple of findings that he shared was the Spark Community because the industry has spent a lot of its time trying to fix the problem around speeders, cheaters, bots that exist in survey data by triaging the problem after we've captured the response. So what we wanted to do at Data Ventures is let's go to the source of the problem which is let's start with the community itself. So that's why we did invitation only. We know they're verified people. That alone already starts bringing to the plate or the table better responses. We got rid of the bots, some of the professional survey takers. Then the second thing that we did is we limited the amount of time that you can engage or responded with. I mean how many of us would actually sit behind a computer and take a 50 minute survey? I don't have time for that. I don't think you have time for that. Right. So by being able to make it smaller engagements with a customer, we are now getting really high quality responses. And what they showed at the, at the, at Inspire was where we did five different product concept tests and we, Bob was able to show how the responses come back in terms of what would be the likelihood of buying any of those improbable product concepts. And there was a significant difference between if you had used any of the six providers, external providers that he had benchmarked against us versus the Spark community. Again, the way we look at this is we need quality data to begin with. If we understand that customer, then we can now look at understanding the behaviors even better. So it all goes back to the source is the way we Looked at it.
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All right, I love the product concept test because the one that really caught my attention that Bob highlighted was scented motor oil. And he said, just intuitively, when he looked at the percentage of respondents from the other houses that had duplicative audiences, that had these participants that you said, the cheaters, the gamers, these are all people that their goal is to get rewards and be part of incentive programs. That's not how you built Spark. And so as a result of that, I believe he said that 26% of the respondents said they would be willing to buy a scented motor oil product. But then he said, but the problem is that we've actually got research from a motor oil manufacturer that tells us that only 20% of people in the country actually DIY their own oil change. So let's assume that of the 26%, all 20 of is accounted from the 26th. So what are the other 6% doing? Are they like, they go to, they go to the motor oil change place and they say, well, I just want the guys changing my oil to have a good experience, so I would like them to use scented Motorola. I mean, it just, it just, it didn't pass the smell test. And so, but Right, and, and that's.
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That'S where you showed the difference with the Spark community being realistic. 5%.
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Yeah, it was, it was like 5%. It was. So obviously. And the problem is that people who've been used to traditional attitudinal research houses are going to be fundamentally surprised when they see the difference in what the realistic expectations are for new product concepts and innovation just in that area alone. So you are radically transforming and actually building a better mousetrap than the industry has ever seen before. Yes, we are.
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A
And the underlying issue here is the cost of failure is high. So when you think about every time that a company goes through the process of innovation on a product or even renovation, they take it to market, put it on the shelf, and then it fails. There's a huge cost to that supplier, There's a huge cost to Walmart. So if what we can do is reduce the risk of failure by being more precise on what will actually succeed, everybody wins in the game, not just Walmart and the supplier, but ultimately the customer wins. Right. So that's why what we're doing is we're constantly looking at different methodologies, survey research, just one example. And then we are trying to take that methodology, put in a more agile way and build it into ways that probably hasn't been used before.
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B
Mark, during the morning session One of the panels you had involved four merchant leaders being interviewed by one of your colleagues. And what they talked about was how they are embracing the insights coming from Scintilla to drive better business outcomes. Can you talk to us about how you have aligned the merchants around the power of this tool and how it can deliver those kinds of outcomes?
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Yeah. So what the tool has done has allowed to have a single version of the truth between suppliers and merchants. So rather than spending their time understanding the differences in data sources, what they do is they spend their time focused on the discussion of how to drive the business forward. So whether it's innovation, renovation, rethinking, assortment, whatever it may be, price, they spend their time taking the insights to drive those decisions. That is one of the big advantages of having this ecosystem that allows the merchants and suppliers to collaborate.
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B
E. Your product manager, Linda Linolino, was last to speak in the morning and at the beginning of her presentation, as she spoke on the screen next to her, there was a scrolling through of all of the product innovations that you had brought to Scintilla. Not in the three years since this business, kind of just in the last year. I mean, it was, it was very fast paced and you talk to each of those components throughout the day. And then on top of that, you added two new markets with two entirely new data sets to this equation. I don't think she sleeps. So talk to me about what? The expectations you're setting by the pace of innovation in bringing your tool and making. Making what I now consider to be the preeminent customer insights tool in the industry. Coming from the retail perspective, Yes.
- [28:21]
A
I think what has been great is that from the day we founded Data Ventures, Walmart has allowed us to run like a startup. And that has never changed even to this date. So the entire team was built on speed and agility. So it's not just the product team you got to add in. Our tech team, our sales team, our account management team, and all the way down operations, everybody. We then replicated that model as we've gone to the different markets. But in that process, we are maniacally focused on taking feedback from our customers. Walmart, Walmart, Data Ventures customers, which is a supplier, the merchant and other stakeholders are on our platform and we capture that feedback through a lot of ways. We do a lot of user research. We constantly are looking at the tickets that are submitted. We are always involved, our account management team is always involved with our customers, listening to them. And I also include our account services team. They come to the table with what are Our customers saying they need to make a better decision. And so we are constantly updating our roadmap. We have a high level roadmap that says this is where we're going to go. But then we also are constantly reprioritizing as we are listening to our customers. What do we need next? At the end of the day, if we're not driving value, we cannot sit here and actually feel good about what we're delivering. So we're maniacally focused on how do we continue to drive value, how do we fit what our customers, merchants, suppliers and other stakeholders are asking for in order to help them make decisions. So that's why you saw that list. Just keep going, Just keep going. And you know, I take my hats off to the entire team because that's a ways of working for our team.
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B
Yeah, I, my head was spinning when I saw that Mark. It was really impressive. So in the morning it was mostly Walmart people talking about where you're going and the results you're getting. The afternoon was a series of breakout sessions that you let your users, the users of your tool talk. And this was they actually self nominated themselves for what they wanted to showcase in different applications of that. So there were 28 modules. I had the pleasure of sitting in five of them. One of the things that was said in, in during, it was said in the video you showed during your keynote was you built Scintilla Insights model to be intentionally simple. And I couldn't think of a better illustration of that than the case study by Gelsert. Gelsert makes powdered soft drink product. And what they told us was it was so easy to get up and running, to get educated and to take advantage of the tool that from the minute they signed the contract until their first presentation in front of the merchant, which led to the introduction of an insights based introduction of new product innovation. It wasn't two quarters, it wasn't two months, it was two and a half weeks, Mark. Two and a half weeks. Talk to me about that concept of intentionally simple. And yet, you know, I look at it like that duck that's swimming on the water. It looks like it's gliding around effortlessly. Right. That's the simple component. But I know that there's a lot of paddling going on and you've put a lot of work into the model to make it ultimately intentionally simple for the user. Can you talk to us a little bit about that?
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Well, we continue to try to make it simple, but I will tell you that my hat's off is the jailsert. Because if you think we are the duck looking common surface paddling fast, they were also paddling fast as well to make that happen. There was a lot of effort doing there because I sat through that case study as well. At the end of the day we look at again I talk to speed to insights and then speed from insights to action. So we are constantly. And through what you just mentioned, when you saw what we did in this past year and you saw that list not stop, this is. We're constantly taking in feedback and that onboarding period, the attribution period, the training period, we have all understood the pains of each one of those and we are constantly focused not just on improving our tools but also improving our servicing level, improving our teaching, our education of the tools so that we can get our clients from investment to value the fastest we can. Right, and you talked about seeing through that one. We had over 30 business cases that were presented because that's all the agenda allowed us to do. We had over 70 submissions of companies wanting to present. And what's interesting here is when we started this we were told I don't think you'll ever get anybody to present. And you fast forward to today and we have over 70 submissions. They were all fantastic. And what that shows is we are constantly evolving so quickly that what you present today is helping us raise the bar. It's new ideas of how you've applied the data to solve a problem and other suppliers can learn from that. And that's what we have seen at Inspire is it's a great forum for you to come up with new ideas to solve your problems. It's a great forum for you to network with non competing companies to have discussions on how to use the tool to be able to collaborate better with Walmart. And that was the purpose of Inspire from the beginning.
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B
I couldn't agree more with you on that. It's very reminiscent of going to the Walmart Marketplace Seller Summit that creates a community of sellers that are trying to learn from each other. I think Inspire is very much about breaking down those walls and being less about I don't want to teach anybody else. It's more of kind of like a GitHub approach. You've created this tool and everybody contributes knowledge to it and everybody benefits. The rising tide lifts all ships and by interacting with people in your industry and being inspired and that's such a perfect name for the event, being inspired by how they're leveraging these insights to get better business outcomes is helping Walmart. It's Helping the supplier and ultimately the customer, the consumer is, is, is getting delighted, better. So I think you've really done a phenomenal job. I know we only have a little bit of time left, Mark, but I certainly want to look towards the future. You know, I know you're not resting on your laurels, your legs are not up on the ottoman, they're not kicked over and. And you're ready to watch. Ready watch the game. You went right back to work this morning. Talk to me about what's occupying space in your head about innovating even further for delivering a better tool to the subscribers of Scintilla Insights model.
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A
Yeah, as we're looking forward, there's really two things. One of them you already mentioned, which is sim, our Sentella Insights model. How do we continue to upskill our users? Right. We have a lot more data that's going to be integrated into our ecosystem. So we need to continuously get our users up to speed. Use the Gel cert example, that's a fantastic one. How do you get up to speed quickly is if we can help upskill you. So that's one of them. I think the second area you'll see us focusing on is leveraging AI so AI can help us today, again, as I mentioned, we have five different modules. Those modules will still exist because you're always going to have subject matter experts or certain roles and responsibilities that you only need one of those modules and you need to dive deep in that data. So they will always exist. But how do we start bringing the data together in an integrated fashion to make sense of it, give you the so what out of the data. Right. And allow you to mine it pretty quickly. So you'll see us leveraging AI now going forward over this next year, bringing that data together, integrating it better to create a better user experience and ultimately bringing this, the data to insights and insights to action even faster. So those, as I look forward to next year, those are two of the areas that we will really focus on. As I mentioned before, we're constantly looking at how do we create more visibility. So that means new data sets, right? New insights that we can roll in that help us really understand that mindset to behavior, behavior to performance. Each one of those, each of the times that we can bring that data to, to bear it allows us to address another outcome, business outcome, that helps us move the business forward. So that's. Those are the areas that we're focused on as we're going forward. If I were to ask you one question, Peter, since you're the first person from outside to attend an inspire event. What was some of your biggest observations that you had?
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B
The community that was being created around leveraging the tool for better outcomes. That was just so clearly evident. Two, the power of the assets that you brought to bear in a single platform and how you have, in my opinion, leapfrogged what many considered to be the, you know, the first to market industry gold standard for leveraging insights. I think, I think Walmart Data Ventures and its Scintilla Insights model is now at the top of the equation. I think that's very important. But three, it's about building it not just as a tool. And here it is. Go use something and do something with it. You've gotten the merchant community and the supplier community rallied around embracing this as a single point of truth and the foundation for making better business decisions. Because if you don't have process without tools, you won't get any usage. So I think you've brought everything together and I am just so excited to learn. I can't wait for next year. I want to see and I cannot wait to see because I think you won't have 70. I think you'll have 170 next year nominating to be up there because they're all very excited and get inspired by each other and that contributes to incredible business outcomes. The one you said, about 15% of gross merchandise value improvement over those who are not subscribing. That isn't a call to action for people to start, to start getting into Scintilla. I don't know what is. That is such a great, great story, Mark, but for me, you've just built a very strong tool, a very strong process and a community of people who are, who are making this all happen. So kudos to Walmart Data Ventures and I look forward to you carrying this, carrying this on even even further next year. I know I'll be dazzled yet again. You're going to up the bar.
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A
Well, thank you for sharing your thoughts.
- [40:21]
B
Absolutely. And Mark, I want to thank you for taking time out of your day. I know you've got to run, but it was so great to have you back on the CPGuys podcast. You're always welcome and we look forward to everything coming out of and I'm really excited to see what comes next from the Scintilla Insights model. So thank you very much, Mark. You have a great day. What a terrific conversation. We hope you enjoyed it. I want to thank you, as always, for following us on social media. If you're not just following us on LinkedIn. We now have a TikTok account. We have YouTube, we have Instagram. All easily findable. Just enter the term CPG Guys and that's how you'll find us. But we've got lots of content there as well. We're so grateful to the now over 40,000 people on LinkedIn who follow us and choose to enjoy our content for both educational and entertainment purposes. Shereen and I love meeting with you at conferences. I think we've got one more this year before we before we hit to the holidays. And then of course CES sends us into conference craziness. So we'll look forward to catching up with you somewhere along the road if you do run into us in the wild. I was flying back last night. A couple people stopped me as they were getting on the plane and had a little chat. So please do take the time to say hello. We loved hearing from all of you. Thanks again and we look forward to speaking with you on the next episode of the CPG Guys podcast.
- [41:57]
C
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