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Transcript
Our transcripts are generated by AI. Please excuse any typos and if you have any specific questions please email info@digitalshelfinstitute.org.
Peter Crosby (00:00):
Welcome to unpacking the Digital Shelf where we explore brand manufacturing in the digital age. Hey everyone. Peter Crosby here at the Digital Shelf Institute. The digital data ecosystem is constantly evolving as new data sets become available and brands work to connect the dots between each piece of that ecosystem. The important element for brands is learning how to navigate the complexity, have to break down silos in their organizations and turn insights into action at every step on the consumer journey. This is an audio rebroadcast of a webinar focused on just that, led by Lauren Livak Gilbert with guest experts, Tim Caggiano, head of e-commerce reporting and analytics at Nestle, Salim Bachatene, SVP, global Sales, e-commerce at Nielsen iq, and Michael Nunes, director of Product Strategy and Operations at PACView.
Lauren Livak Gilbert (01:02):
Welcome to the webinar. Thank you so much for being here. We have a great lineup of speakers today, and we are going to be talking about navigating the digital data ecosystem. We all know there is no shortage of data when it comes to e-commerce, but trying to figure out how all those data sets work together, finding the right insights and then bringing those back to the organization is definitely a complex model. But we have some experts on the webinar with us today to talk us through that. So first, for those of you who I do not know, it's very nice to meet you virtually. My name is Lauren Liebeck Gilbert. I lead the Digital Shelf Institute. Thank you for being a member. If you are a member, thank you for coming to our webinars and consuming our content. Really excited to be here, and I am going to have Tim introduce himself. Next.
Tim Caggiano (01:52):
Thanks Lauren. Tim Caggiano. I'm the head of e-commerce reporting and analytics for Nestle usa.
Salim Bachatene (02:00):
Perfect.
Lauren Livak Gilbert (02:01):
Thanks, Tim.
Salim Bachatene (02:02):
Yeah, Salim here. So I'm the SVP of Global Sales at NielsenIQ with I would say a strong background in the digital self. Thanks
Lauren Livak Gilbert (02:12):
Li. Hi Michael.
Michael Nunes (02:13):
Yeah, I'm Michael Nunes, I'm a director of product strategy and SI get the pleasure of building some of the cool tools at PAC View.
Lauren Livak Gilbert (02:20):
Fantastic. So we have a really well-rounded group today and a lot of exciting topics to get into. A few quick housekeeping items. If you have any questions, please feel free to put them in the q and a section of the Zoom. You can also, if you have any other questions or you need to get to me or you need a link for something, just throw it in the chat and I'll be able to moderate that. What we're going to talk about today, current state of data, why it's really challenging to navigate what you can do about it, and some really great examples and hopefully some takeaways that you can take back to your organization to help with your data ecosystem and your data strategy. So before we get started, we always like to do a poll to really understand from our audience where you are at. So you are going to see a poll pop up on your screen. Please come back to your screen and put in your vote. But the question is, do you feel that you have a connected end to end data strategy currently within your organization?
(03:26):
So I see the results coming in. I am going to give everyone a couple of more seconds to vote. If you just go back to your screen and add in your vote and I will close it in. 5, 4, 3, 2. Here we go. Alright, so 60% of people on the call say no, they do not have a connected end-to-end strategy. 13% said yes. That's really exciting. Please share your insights throughout the webinar. 28% said we are currently developing one. So I feel like everyone on the call, I feel like this checks out. This is what we see a lot. I see the nodding his head. So this is definitely familiar where you're talking to a lot of brands. I'm talking to a lot of brands who are really working through this and trying to figure out how to solve this problem. So without further ado, I will hand it over to Salim to kick us off.
Salim Bachatene (04:22):
Thank you so much, Lauren. I don't think we could have started better than this with the results of the poll. I think it's a good illustration what we already knew, which is this is the challenge and I'm very sure that amongst the people who said no, that the idea is kind of there is just didn't start because this is the topic we discuss with most of our manufacturer clients and I think it's a critical one. One, the first kind of idea I wanted to share is when we look at the numbers, I think there was an analysis we made that most manufacturers within e-comm would use at least six different sources of data to build their tech or capability stack. And I would say from experience there's a lot more than that. That's an average and we know that averages hide sometimes, some realities.
(05:16):
So it is a very complex topic and what we're going to try to do is to simplify, but I don't think there is a simple answer. I think there is is a growl that manufacturers are trying to establish. So if you follow me in this chart, so if we start by the left side, which is the first step of creating and centralizing the information, so that could be a very well like a PIM or a DAM or any kind of tech that would help do that. Then the second stop is mostly on measuring and from measurement perspective, there are different aspects of it. So of course it's the sales, the market share, the digital shelf, and so on and so forth. And I think it's important to see things in a sequential level as I'm going through it because I think looking at the end game is great, but there are so many things that can be done along the way.
(06:13):
And I think potentially a question that the people with us today could ask themselves is where am I within this kind of flywheel? So the third step is cross-referencing the data, and that would help the use case of visualization first. But then once you've kind of achieved the visualization stage, you can go to the next level, which is how can I recommend and prioritize actions? So you kind of get the idea behind this at the end. It's not just cross-referencing the data just for the sake of doing it. The ultimate goal is really what kind of action I can take and what kind of action that can come in a very timely manner so that I can impact the performance and so on and so forth. And the final step, which I think is kind of the end goal of everyone, is adding a layer of automation actions.
(07:03):
And we'll talk about this a lot in details today because this is what start to help people free up resources and start to really create those actions that take the impact. So the topic is very complex. I'm talking about it mostly from platforms data, but it's wider than that. It's organizational, it's ways of working. And we will elaborate on this a lot more, but if we move to the next slide, I just wanted to share a wider idea. So we're going to be talking about automation, which is something that a lot of manufacturers are acting on now, especially on the specific use case of retail media because it makes a lot of sense, but I think it can be just kind of wider than that. And then we start to talk about orchestration. So what we mean by orchestration is that it takes a lot more than just one action from one data set on one platform to the other, but a whole set, the whole tech stack.
(08:05):
And I think what we're trying to illustrate here is the importance of the data structure, cleanness and cross referenceability. So I think a lot of resources today are spent while trying to connect the dots in realizing that it's very complex to connect those dots for the simple reason is that some of the data is not referenced, is not coded, and so on and so forth. And that's probably where we try to add the most value is to play that central role around the good referencing the healthy kind of database because then the capabilities are endless in terms of connecting. So if you take an example of orchestration is really before taking the action. And the case here is retail media. It takes a whole team and I'm sure team will talk a lot about organizationally speaking, how that will impact, but making sure that supply chain is in the know.
(09:07):
When we're launching campaigns on retail media, it's not only about stock, which we know is very important, we're going to talk about it, but is supply chain aware? Are we replenished? Are we ready? Do we have the insights from past campaigns to see the impact of the campaign on impact, direct impact on stock levels and so on and so forth. So I just wanted to kind of broaden and open really the potential of what we can do by crossing and opening and connecting the dots in the ecosystem. But I don't want to undermine the fact that it's very complex. So I don't want anyone to feel like this is an easy task. Where do I get this? Where do I buy this? And that's where we are talking about this today. So maybe good time for me to hand over to Tim.
Lauren Livak Gilbert (09:58):
Perfect. And I'll just, if you want Tim to tee you up on this is when we were prepping, we talked a lot about why is this hard, why is it challenging to do this? And to Salim's point, it's not an easy task. So Tim, kick us off and let us know why it's hard and how you're fixing it.
Tim Caggiano (10:16):
Yeah, thanks Salim. Thanks Lauren. As we started to put this deck together, Lauren was asking for examples and the thing that came to mind that is constantly happening is APIs are constantly changing. We're constantly getting product enhancements and building those into our backlog of development for IT teams that are already stretched thin, it's easily at a short conservative estimate, 15 hours of work, but not only that, you have to prioritize the other work they have just to keep the lights on so to speak. So we started to outline the three key areas why this is challenging and some of the ways we've addressed it, but first and foremost it is setting leadership expectations and then the reality of it. So the first one that I thought of was explaining to leaders without a technical background. So someone who has maybe a marketing background setting their expectation realistically that hey, what you're asking us to do is possible. It will take a lot of legwork and realistically could take multiple sprints. These are details they don't necessarily need, but finding a way to phrase it in a way so they can understand when they have to report up, they know, hey, this will be delivered in two months, three months next quarter. That's a very clear way for you to break through the expectation versus reality challenge.
(11:43):
Not only that, but working down the food chain, setting those expectations with room for flexibility and protecting the people that are doing the work. So this could be your BI developers, this could be your data architects, but understanding when they give you a timeframe, is that realistic? Do we think they're building in a buffer? What other work do they have? What challenges from a technical standpoint do you see before you even ask them to partake in this enhancement? And that's really about protecting their time and making sure that they are doing the highest ROI work. So having honest conversations with the people that are actually doing the work and understanding where they foresee blockers enables you to then report up and set real estate expectations to your leadership. Third, and this is something I constantly struggle with and it's something that is an area of improvement constantly for me that I think about is giving the right level of detail, right?
(12:42):
You're talking to someone who's a chief digital officer, they just need to know when they can expect to see it. They don't need to know if it's an MVP, they don't need to know that the data has been in a rough state, so you've had to clean it up extensively. They need to know that what you're reporting and what you're providing them is accurate, meets their expectations and what the potential roadmap might look like. And then filtering that down, providing more detail as necessary. And last but not least is when blockers do come up and when challenges do come up with two data ecosystems or marrying data ecosystems or really just any kind of typical blocker that might come up in the development of something like a dashboard, explaining that by fixing a simple what seems as a simple problem, you might create more issues.
(13:32):
So making sure that you've built in that time to test it and not only test it but vet it with the business and make sure that there are no other gaps that are created by fixing the problems that are highlighted. Lauren and I talked through examples, but being a global company using EINs, G tens, differing levels of UPCs, it's a constant struggle of, hey, do we have leading zeros, trailing zeros? There really isn't a great way when these are inherently things that are constantly shifting. In an ideal world, we'd have a mapping table that did all of this, but unfortunately lacking a mapping table that is dynamically updated all of the time to account for all of this is just a challenge. So it's a matter of understanding where those gaps are, having it documented in a way that you can have on hand. So when you do have to speak to leadership, you can explain it in a simple way. That's the first challenge.
Lauren Livak Gilbert (14:29):
And when Tim and I were chatting about this, the thing that really came out that I think was really important is also talking to your leadership about what is the question that you're asking first. Instead of starting with the data and being like, okay, here's all the data we have, here's all the data sets. First start with what is the question that we're asking? And then having the teams really come together to understand what data sets you need to be able to answer that question. And to Tim's point, it can be really challenging for a leader to ladder up and down between the weeds and the strategic, but they need to have some context and understanding about what is happening and how long it takes. So that example that Tim started with where if an API changes, it could be equivalent to 15 hours of work, A simple sentence like that just to provide context is helpful so that you can say something like that and then they say, okay, what is the plan? How should we execute it? And then you work with your team to be able to do that. So just kind of backing into the problem saying what are we trying to solve? And then saying, okay, what's the plan and what is the context is a really helpful way for brands to gather all that data and provide the right story.
Tim Caggiano (15:42):
Thanks Lauren. Yeah, I think that ties directly into the second challenge is if you've ever been in a cross-functional meeting, everyone has a little bit of a different viewpoint and they will bring that viewpoint and their background to the meeting. So a simple problem at a high level, how do we increase our share on the digital shelf? You talk to someone on the e-commerce team and the digital shelf team at Nestle and they'll say, well look at our PDPs. Do we have the right number of bullets? Do we have enhanced content? If you talk to the marketing team, we'll go, well, do we need seasonal content? You talk to someone on the brand, they'll give you a different answer, and so on and so on. So when you're building large scale cross-functional projects that touch on multiple teams, being aware of not only the viewpoint the people in the room have, but also your own biases and viewpoints is super helpful.
(16:33):
For myself, I come from an analytics finance background, so I go to numbers right away. So for me, understanding what is the Lauren's point, the business question at hand, and returning to that and potentially use cases if you have them, is super helpful for grounding yourself and grounding the business problem, but then also understanding where do I default to and who could I potentially partner with who has a different viewpoint and can bring different perspective to this problem. And from there it becomes more tactical. So one of the things that Nestle that we constantly do, and this was new to me when I joined Nestle, was building RACs and understanding from a high level, who's responsible, who's accountable, and in general, it's just really who needs to be informed. A lot of times meetings will consist of mostly people that need to be informed and the responsibilities fall on one or two functions, but also building in those meetings, those cross-functional connections and having a point of contact that then if you need something from, for example, someone on the brand team, I know I can reach out to someone on the coffee meet team and I know who that person is, those are the kind of things that help break the silos that we tend to fall into, especially when you're talking about a big cross-functional project or a dashboard that might hit on a few different people or different functions or something that is meant to be built for ding levels.
(18:06):
It's very, very important to start with the use cases, get the context and the business question at hand, talk about ultimately for all of these functions, what's the raci? And then afterwards building those cross-functional connections and leveraging those down the road because this is not going to be the last time you're going to need someone from finance or someone from data science. And having a point of contact is a great shortcut rather than having to start from square one
Lauren Livak Gilbert (18:35):
And to pull in Salim’s opening as well. Also understanding who owns the data sets, where does that data live, which function does it live in? Who needs to be involved in all of those conversations? Mapping that out from the get go enables you to have a more productive conversation and a cross-functional conversation. And does it make sense to have a data council, have a cross-functional team where you're talking about data, you're talking about governance, you're having these broader conversation. So as a brand, if you don't have these cross-functional communications or governance conversations, try to build something like that out, that's a first step to be able to get that visibility to your data ecosystem across the organization.
Tim Caggiano (19:25):
I'd say the last area is really just when you're thinking about a global company like Nestle, it's very easy for functions to go off and get vendor specific data, and there's a marketing team that goes off and has their own budget. The digital shelf team has their own budget. Our e-comm strategy team has their own budget. There's limited visibility because of that into what we're bringing into our IT and into our data lake. So having ways to break down those silos, even if it's something like what we did at Nestle, which is we have an annual thing called day-to-day where we bring in our vendors and different teams will say, Hey, I think this might be applicable to some of the work that you're doing, or Remember that project you did a year ago where you asked me a question? And that gets back to second point of building those connections when it comes to having to create a day to day where everyone gets in a room and says, Hey, this is what we have at hand, I think maybe it could be an enhancement.
(20:22):
It starts to facilitate conversations around, okay, what's a single place where we have all of this data? Who owns it? To Salim's point, which is always an important question, is this a contract that we have just for the year so there's some time sensitivity to it and we've got to leverage it now? Or is this something where potentially could be used across teams so we could share the cost that gets into the procurement piece of it, but really it's about leveraging the relationships you make in those conversations that are cross-functional and then making sure that when it comes to the actual use of third party data and technology vendors that who owns it and you know where to go when you're trying to build an enhancement to your project.
Lauren Livak Gilbert (21:11):
And I really love the example about procurement because I feel like sometimes procurement might not be involved in the conversation, but bring them in, see if someone else is using the platform across the globe, or you can have more of a holistic conversation. Any type of centralized or cross-functional team gives you that visibility across the board. So really great examples, Tim, and definitely something to think about. So Tim, what can people do about it? What are some great takeaways that have worked for you at Nestle?
Tim Caggiano (21:39):
Yeah, so since I've joined Nestle, there's been a few things we've implemented to make it easier from a measurement and reporting standpoint and just in general increasing what I say the collective intelligence around the digital shelf analytics space, right? First and foremost is making sure there's clear recurring trainings and opportunities for people to get trainings, especially if it's a new platform. We want to enable people to do the work themselves. Self-service is something you always hear about, but enabling someone to feel confident that, hey, if I need to find out what my share of search is, they can do it because people will otherwise default to what they know best. So if they have experience in impact view, they'll default to PAC view. If they know data impact more, they'll default to data impact. So especially as you're trying to get traction for maybe a newer piece of software or a newer dashboard if you're building it in-house about providing recurring trainings and making sure those are in different formats.
(22:42):
So we'll not only host trainings on a recurring basis, and we have a calendar a little bit later, but we also have recordings of those trainings. So if you happen to miss it, no big deal. On top of that, we put out the decks. So there's different opportunities for people to learn on their own. And that gets into the second point, which is learning outside of the classroom. We have instituted something I call office hours. So no different than when you're an undergrad. If you have a question and you're a little embarrassed to ask it, feel free to come in one-on-one, an open door kind of policy, half hour where you can ask questions. If you just want to know how I would handle a problem, it saves you a little bit of work because you're not getting constant emails about it. So there's again, that understanding of I know when I can go to Tim.
(23:30):
And then the second piece is maybe somebody else has a similar question or maybe there's been multiple questions around it. So that's an opportunity for us to do retraining or maybe address training in a different way. Last but not least is giving context to showcase the opportunity. I think one of the things here with Nestle is the complexity. Someone with a marketing background or someone who's in supply chain might not fully understand the opportunity the digital shelf provides. And that's where we have to start. At the start, I think it's very quick and easy to jump into the how and what we're doing and what we're building, because that's exciting to us. But I think for other teams, you need to start and say, Hey, this is where the dollars are. This is the opportunity of getting trained on this platform. This is why we think this is important for everyone to learn. And that's something that we've really excelled at here at Nestle.
Lauren Livak Gilbert (24:25):
And training and context is so important. And I love that you're sharing this example of your training calendar. So can you talk through what does this mean? When do you do it? What types of trainings do you run throughout the year?
Tim Caggiano (24:38):
Yeah, so this is just an example month. The way we try to think about it is from a divisional level, people learn best what they know and ask questions about what they know. So we wanted to break this into the divisions roughly speaking. So if there's someone from a brand who has a question around how am I doing it with Aqua on the digital shelf, they know, okay, I can come on the 14th and there'll be something geared towards mine towards my division. At the very least, I'll have a good baseline of understanding because I know my own products that also provides cross training opportunity. I mean, Nestle is a company where you're encouraged to move around. So if someone wants exposure to a division outside of their own, we've had people come to other trainings. So we do see that people in different job functions will hop to other trainings. And you'd be surprised sometimes when someone or some function or group you think is focused on something like out of stock, you'll get no questions on it, but they'll have a lot of questions on the pricing data or they'll have a lot of questions around share search. So it's just constantly changing and having a baseline, but making sure that people feel flexible and feel enabled to do what works for them.
Lauren Livak Gilbert (25:57):
And Tim, we actually got a great question that I think would be perfect timing to ask right now. And so it's about how would you get past a set it and forget it type of mindset, especially for the sales team when it comes to the digital shelf, it's difficult to convey that a gap on the digital shelf is just as important as a physical gap in store, and they should be just as concerned when a product components are missing online as they would be in store. So how do you get past that? Hey, you're trained once and you're an expert versus an ongoing kind of thing.
Tim Caggiano (26:28):
Yeah, that is something that is a challenge. And the way we've kind of addressed that is when those questions do come up, because they will assuredly come up from our sales team or from a brand team, making sure that that is not left as an email response that you're saying, Hey, give me 15 minutes, let's walk through this. And it's almost like a little bite-size training and not only teaches them how to do it on their own, hopefully in the future, but also enables 'em to be potentially almost like someone who can socialize it on your behalf for the team. In terms of the gap between physical and digital, yeah, that's a challenge that every person who works on digital shelf experiences, it's about understanding. And again, we'll get to this on the next slide, but the potential, so showing them the potential of the digital shelf, this is a slide that we use with those teams, and this is exactly the type of content that I would suggest you build and we show this to everyone before we even get into a training. So we used to hop right into trainings for our digital shelf reporting. We usually start here now, and these are big numbers and these are the big pieces to the story that everyone needs before you hop into what does that look like? How do you attack the digital shelf, how do you compete? Getting and setting the groundwork of the first page is really where you win makes it easier to then get everyone's attention as you dive into trainings.
Lauren Livak Gilbert (28:20):
Salim, did you want to add something?
Salim Bachatene (28:22):
Yeah, I think first of all, it is a great question and I think it's also an opportunity, so I'll take it from two angles. First one is I think omnichannel is actually an opportunity to kill these kind of questions because what's in story supposed to be? What's online? So if we take the largest omnichannel retailers deploying on a kind of pickup strategy, basically we're not anymore talking about online versus offline, we're talking about the same thing. So the product is not online. If a product is suffering from bad search performance or bad content that would influence online sales, but that could also very well be a reflection of the performance of offline. I think on all the analysis I've seen so far, we're talking in the next three to four years that 70 to 80% of the cells will be influenced by online. So it's not anymore that kind of channel that you take a look at, and it's a source of growth is great, this is proper, the shopper is proper omnichannel shopper.
(29:26):
And I think the four of us are omnichannel shoppers as I am in all the analysis we made at N iq, we have something like 80 to 90% depending on categories of the shoppers, omnichannel, IE, they use all of the different ways to purchase. And when we try to take a look at who is online only, it's less than 1%. So, which means that online becomes a way to win new shoppers, but also a way to lose shoppers if the execution is not right. And I think this is the kind of education that has to be made. Back to Tim's point, and I love this slide because it repositions the topic and how important it is not only for online, but for the overall business of the manufacturer.
Lauren Livak Gilbert (30:16):
I love that. And actually, so Bailey, hi Bailey, thanks for adding that comment in the chat. I actually want to read what she wrote because I think it's a fabulous mindset shift, excuse me, because a lot of what we're talking about with the set it and forget it and when working with different teams is that they've worked the same way for a really long time. Change is hard naturally for everyone, whether it's data or technology or understanding omnichannel to Salim's point, and Bailey put something in the chat that I think is really interesting, and she said, based on a lot of studies, people are impacted emotionally twice as much as when you take something away versus when you give them something new. Applying that mentality to business process change helps you understand that they're grieving their comfort zone even if it wasn't a good process.
(31:03):
So helping them with process change prior to implementing a new software or new strategy helps the emotional side of change so that they can be ready to learn new tools. And I love, love that comment because I think at the end of the day, we need to remember that everybody's human and that change is hard, and we have done in-store shopping for hundreds of years, and e-commerce is new. So really making sure you're building out this change management program, providing the context, giving people the opportunity to understand these things will just help you leaps and bounds when you're trying to implement things like this. So Tim, we were talking about context here, and I know you have one other slide that you share that's helpful for context,
Tim Caggiano (31:51):
And this is actually very helpful for that physical versus digital shelf space. So when we think about the physical shelf, it's only resetting once, twice a year. But for context, the digital shelf resets every 10 minutes for a single keyword for one person that's at one retailer, 19 million shelf resets every day. All of those colors you see are different products. So that is in itself, those images are usually showstoppers because someone with a physical shelf mindset, no, generally has no idea that the digital shelf is that dynamic. And it's very good at setting the context of why this is such a challenge and why it's not as simple as, well, why don't we throw paid media at it?
Lauren Livak Gilbert (32:47):
So Tim, one of the questions in the chat, and I think it's a really great point, is at Nestle, how do you define the digital shelf? Do you talk about it as content, availability, price, share of shelf? What is in the definition when you are talking about the digital shop?
Tim Caggiano (33:04):
Yeah, when we talk about digital, it depends again on who you ask. It's a little bit of everything. So it is not just your content, it is not just your availability, it's not your price is really all of it. So the content is what the digital shelf team focuses on. Availability is another component that our e-comm strategists focus on. The share shelf is something we look at weekly, all of us. So it's really all of those pieces at a high level, we track our share of the digital shelf, and then we look at things like content availability and prices as levers, right? Things that are in our control and are not in our control. We can control how our PDP looks. We can control if the retailer is representing our product in the right way. If you are on, and I'm just using this as an example, Kroger, and they're not showing the right images, is that a syndication issue on your end?
(34:01):
Then it's on you to fix that as soon as possible. But if it's something where Kroger is misrepresenting your product and this is not a slight against Kroger, I love Kroger, just using them as an example, then you need to go to your account team and say, Hey, here's the issue. What can we do to get this fixed asap? How can I accelerate the fix? Let's try and triangulate that. And is this something that's occurring across multiple products? So the digital shelf is at a high level, it's your share of the shelf, but underlying that, are the pieces like your content? Is it enhanced? Do you have videos? Do you have the right number of bullets? Are you doing the basics? Do you have ingredients? Do you have nutritional facts? Those are all baseline things. They all drive your organic share, but at the end of the day, it's also comprised of stuff like retail media, and that's a space that we have a separate team for. So I typically stay out of it, but I work closely with them to understand, alright, what are our strategies based on what the e-comm strategist has provided and are we executing on them and how does that contribute to our share of shelf?
Lauren Livak Gilbert (35:13):
Salim, go ahead.
Salim Bachatene (35:15):
Yeah, so I love the second part of the question, which is what is the most important? And I think the answer is it depends. It depends on the retailer and it depends on the actionability. And I think this is probably one of the most important use cases of the topic today, which is the ecosystem combining data for what purpose? The purpose is to define what brings most of the value. So combining digital shelf, all the metrics that were mentioned, content search availability with sales data, and creating basic modeling to understand what are the levers by retailer that will generate most of the outcome. And this is precisely what we are doing. So of course there are prerequisites in terms of data needs to be well coded, and Tim's point about UPC lend is very important, but the reality is that you will have two, three levers that will bring most of the value.
(36:20):
And knowing the lack of resources, that is a common topic when it comes to e-comm teams that gives a clear guidance of what can be actioned. And then the other topic is when we talk about the action, in my point of view, most of the actions when it comes to availability price are within other teams. So that's why I feel that e-comm is required to have a high level of collaboration and the data is the element that can foster that collaboration by saying, if we impact this, this is going to generate this kind of output from a performance perspective. And that's how the data can help initiate those conversations cross functionally.
Lauren Livak Gilbert (37:06):
Perfect. Thank you, Salim. Thank you, Tim. So I think we have one more slide to dig into here. Tim, we were talking about what's next with data. We have a lot of things we need to work on in terms of working cross-functionally, bringing it all together, but what are you thinking about next? What's on your horizon?
Tim Caggiano (37:23):
Yeah, this is a prescient question I saw on the Wall Street Journal yesterday that Puma is leveraging AI for content personalization. And as a byproduct of that, they're able to get insights from their consumers directly. They don't have to work with retailers to get those insights because they can personalize what their consumers might want to see leveraging. I think it was a chat GPT based model, but you'll have to check me on that. But really I wanted to get AI out of the way because kind of where everyone defaults to, but anyone who's been in the data science space will tell you this is nothing new. It's just that we now have the computing power to do it at scale. And with that, we can get much greater details about our consumer behavior. Previous to this came from hospitality. I know what someone spends at a hotel.
(38:17):
If I own the hotel, I know what you spend in food and Bev, I know what you spend on the room. I have a much greater level of detail about my consumer than we do in this space. So I think that's where we're going and we're starting to see it play out because of the ability to compute at a much greater level with ai. But I think the second piece is, and we're starting to see it is retailer specific, right? Walmart Connect, we have 84, 51 Kroger. This is a space that's just going to explode and grow. I think what will happen is we're going to reach a tipping point where you have to make a decision. Do we pay for all of these retailer specific data sources or do we just do one or two? I think that's ultimately where the space is going, and maybe it's something like a third party and you pay for a third party who aggregates all of this for you.
(39:15):
I think those are the big trends. The last one, connecting data on the PDP to those retailer insights, that's something we're already doing and we're constantly trying to do. The problem right now is that it's kind of back of the envelope, right? Marrying this Williams point, something from Walmart Connect or from Kroger. On the loyalty data side, it's difficult to say, Hey, when we flip from four bullets to five bullets, it drives X amount of incremental revenue for this product. And that's ultimately, as we again get better quality data, we'll be able to answer those questions with a certain level of certainty.
Lauren Livak Gilbert (39:56):
And I think, Tim, you called this out, you don't own retail media, but you work really closely with the retail media team. If you've ever heard me talk about this, I always like to say if you spend $1 on a retail media ad and it drives to an incomplete PDP, it's a wasted dollar. If you are not having conversations across the teams in your organization with retail media, e-commerce, digital shelf, none of those efforts are going to be successful. So just thinking about how can you build those cross-functional conversations, connect people together and make sure that you're pulling your data, your content, your strategy across the organization. So Michael, bring us home in terms of how all of these systems and data are working together.
Michael Nunes (40:40):
Yeah, totally. So I mean, look, data and digital shelf with all the cycles and all the different complexity, it's really like wrangling the bear. So once you've wrangled the bear, what's the advantage you get? And really the advantage you get is you earn the right to win in the space. And so how do you earn the right to win in the space? Like I said, three layered approach, and I'll talk a little bit more about the details of the next slide, but really it starts with understanding where you are relative to your competitors from a holistic perspective, and then going down to the next layer, which is where does specific products, where does specific regions, where does specific offices, how do you see where you compete? How are you doing compared to your competitors? And then how do you take advantage of areas where you're strong and how do you back off on areas where you're weak? How do you respond with action at scale and in a dynamic environment where you can do things proactively as opposed to reactively?
(41:39):
Next slide. So really I was mentioning earlier, there's two different ways you can think of this. One is winning opportunities. Where do I identify places where I have an opportunity to go generate more revenue, sell more product, really take advantage of things that I compete in a good way? And the other is defending what you have. And so there's three different places you can do that. One is inventory, price, promotion, and content. So examples of that are inventory. When a competitor is running out of stock, can you push your advantage where you have stock and then you can defend that too where you're running out of stock, stop promoting a product, don't waste money with price and promotion. How do you win with price and promotion? Where do you have a price advantage? Where can you compete with your co competitors in a good way?
(42:25):
And then also when your competitor to defend your territory, when a competitor has a promotion, how do you respond to that? Do you want to compete with them, run your own promotion? Do you want to give the territory content? We talked about sling, talked a little bit about content earlier, which is how do you compare to your competitors across content? Can you push an advantage where your content is superior and can you identify the areas where your content is not as strong as your competitors? So these are kind of some of the ways that you can activate your digital shelf and you can respond not only from a reactive perspective, but you can generate automation and intelligence to be proactive about these things. And just, this is kind of a plug, we've got our NIQ impact view are coming together to do a lot of these solutions together to take your data and then make it actionable.
Lauren Livak Gilbert (43:15):
Awesome. Thank you, Michael. So if you want to get in touch with everyone, we have a lot of great people on the chat today. Excuse me. On the webinar today, we pack you Data Impact Digital Trump Institute. If you're not a member, please become a member. Scan these QR codes. If you want to get in touch with anyone, I will keep this up here. We do have a few questions that I'd love to share with the group, so let me just pull those up and if anyone else has other questions, please throw them in the q and a module or in the chat so that we can get to them. Okay. So Tim, I think I'm going to throw this one to you and then everyone feel free to jump in as well. Is there a single share of shelf metric that you use at a high level from a KPI standpoint?
Tim Caggiano (44:00):
Yeah, no, because if you use one KPI, you become beholden to it. And we're aware that the digital shelf is far too complex for that, right? We can look at our ESHA and compare it to how we're doing overall, but that's just directional, right? There's too many things at play, and I think the physical shelf versus digital shelf slide that we shared earlier does a great job of making it clearly. There's just way too many levers. And even if you were to do something like a regression analysis to try and get at what's the most important, you're not going to find definitive answers. So we don't look at one, we look at 'em holistically and we think about what can we control and what can we not control? We can control, to Michael's point, if we're putting paid media towards a product that we know is going to be out of stock, or if we can see that, hey, our competitors products look like they're going out of stock, maybe we should be investing more in paid media.
(45:05):
And that gets into the second piece of this is making sure you find partners who can be that dynamic with you. Because if you are working with a partner who doesn't have that level of flexibility, it's very similar to what Lauren said. If you're directing a product towards a PDP, that's incomplete, that's effectively you're losing sales. So you have to make sure everywhere along the whole chain of your entire digital shelf is connected and in sync and able to be as dynamic because if you have, from an operations standpoint, you have a blocker somewhere or you have a throughput issue, you're really going to be falling behind competitors. The second question from Sarah, in relation to digital shelf, to what extent do you value or use competitor benchmarking data to understand best practices in the industry? Or do you even look out with your own categories?
(46:00):
We look at our competitors when we do track our competitors' shares. That's about the extent of it. We want to understand is the whole category declining in something like share of search or share of shelf, or is this something that's more localized to private label or a specific manufacturer specific brand? So we'll look at those lenses and that level of granularity, but beyond that, we're really not tracking competitor benchmarks from a best practice standpoint. Of course, we want to do what the retailer is identifying if they have as the best practice, but that's a constantly changing criteria set. So that is, do we put our teams time towards chasing that and potentially it's going to shift in three months, two months, or do we have them focusing on the things that really matter across retailers? And that's a constant point of conversation is what's the RO? I
Michael Nunes (46:59):
Want to chime in here too on the KPI as well, because what you're really after with KPIs is a story, and the more points that you have, the more KPIs or metrics you can put together, the stronger the story you can create and the better you can react to it. So things like buy box and share of assortment and all these things coming together to show you a holistic picture of what's happening tells you how to react to certain situations.
Lauren Livak Gilbert (47:25):
I love that. And we also, we got a really good question here, and I think maybe all three of you probably have an opinion on this, so feel free to jump in. Do you believe there's a need to customize KPIs for each digital shelf partner or a one size fits all approach? Tim, I see you smiling, so I might toss that to you first, and then we'd love to hear from Salim and Michael.
Tim Caggiano (47:48):
In an ideal world, yes, right. I think as you think about building out your capabilities, starting at the start, and if it is, hey, we don't even have KPI set, it really depends on where you are in your journey is how I would answer that. If it is the start of your journey doing a one size fits all approach, seeing if that one size works for all of your partners and then adjusting from there, no one is going to bat an eyelash. And leadership will not begrudge you for taking that approach as long as you have rationale to back it. Now, in an ideal world, knowing what your partner wants, yeah, absolutely customize as much as possible for those KPIs, but you have to, I think, constantly think about what additional value or what additional dollars can I get from customizing these KPIs for a few of my partners? But I'll defer to Salim and Michael on differing opinions.
Salim Bachatene (48:48):
So I think I agree with you, Tim, because, so on this the point that we need to start basic because there's no need to over complexify things, especially if it's the beginning. But I would say just to add, it depends on what the manufacturer is trying to achieve. So typically what I often see, and I think it's something that is not good, which is defining same rules or same objectives or same kind of scorecarding for every single market, every category. And I think before even starting to think about how to customize the kpi, because there is a lot of complexity behind calculation of KPIs, I think there is an in-between, which is how do I adjust my targets or what I want to achieve based on the maturity of that brand or the maturity of that market. So typically you have some markets globally where content is an easy task to have your content a hundred percent aligned with the trusted source.
(49:50):
And there are some markets, and I don't want to quote any market where it's extremely hard. So giving both markets the same objective to achieve is kind of unfair. So I think these kind of customizations would help create the right level of engagement. And then there are other types of customization or adaptation such as the way your data is categorized for digital self. So we put, and we insist a lot on this, so it's important that the digital self data is categorized in a way that is recognized in the business because the business is organized in a way as well. So I've seen so many meetings where the meeting is diverted for 20 minutes because we don't agree on what we call the subsegment or subcategory, and that's why we do it this way, which is matching the categories of the client so that we remove that nonsense 20 minutes debate during a meeting on what's in and out this segment so that we can focus on, okay, my sales are doing this, my outdoor stock is doing this, and how can we create the right thing?
(51:00):
And then it's also an evaluative word. Back to Tim's point, my strong recommendation is always to start with what can be actioned. There's no need to acquire data that will not be actioned. So it is always to start with what could be actioned. There's no need to try to solve bigger problems if they're not going to be actioned. And then once it's actioned, it creates that positive flywheel around, I acquired a bit of data, I took the actions, I had the support of my providers, I generated outcome. I can prove it to the leadership and I can seek for further investment to go to the next level. And I'm growing the maturity and the knowledge of my teams while I'm going through that journey.
Michael Nunes (51:49):
Couldn't agree more. I think we've beaten this quite to death, but just to drive it home. And things only mentioned, I think super important is following the guiding principles of what you're trying to achieve, let the implementations go where they may go, but follow those guiding principles because it's probably the common ground as you go across.
Lauren Livak Gilbert (52:06):
And then one question I wanted to bring up, and I'm curious, Tim, I'm not sure if this applies to you, if not, Salim, Michael would love your thoughts. Do you work at all with your other global teams outside of the US to understand how they're collecting data, what they're looking at, or any trends they might be seeing or how they might be approaching things? Or are you really more focused on just North America?
Tim Caggiano (52:31):
So less so global. I do have global counterparts, but I do work with the other opcos here in the us. So Purina, Nestle Coffee Partners, Nestle Health Sciences, we work with them a lot. We face similar challenges given the market. So we talk about what we're seeing at a retailer specific level. We'll have conversations about just best practices. So I have a monthly standup with my counterpart from Nestle Coffee Partners, and they'll bring their problems to me and then I'll bring my problems to them and we'll kind of work through, Hey, have you started building this out? Where are you in the process of training? What challenges have you seen with training globally? The interactions, there are more of an inform and we'll keep them, since we in general are one of the first countries and areas to usually get these capabilities, it's really more of an exercise in how are things going and where are we seeing challenges? Because depending on what country you're talking about in Europe, there's varying levels of sophistication when it comes to the digital shelf. So really it's at this point, mostly uk, us, Canada are my main points of contact. And then obviously Vive.
Salim Bachatene (53:48):
Yeah, so as my role is global, I kind of have the opportunity to talk to a lot of global leaders, and I think so why it's important to collaborate, it's because there's a lot to learn from it. So I've not seen one wave in the digital shelf. If we just take the example of retail media. So of course the wave potentially started or it got a lot bigger in the US than anywhere else, but we can see that it's happening in Europe as well. And when Omni or pickup started somewhere else in the planet and then during Covid, it started in the us. So I think there's a lot of learning to be ready. What are the trends, TikTok, as we're tracking TikTok, we realize for example, that countries like the uk, TikTok is becoming one of the top retailers for beauty. Is this going to happen in the us?
(54:45):
I think personally it is. So if I'm collaborating with my partners in other markets, I'm able to get ready, have a sense of what potentially could happen, what are the growing trends, and how can I get the business ready for these trends and take advantage of them Because some people see them as risks and new things to do, but the reality is that they are opportunities to be the first one to action. So I think the why is really important here. Collaboration is kind of critical. And of course all the things around best practices, ways of working, and since some of the retailers are now global, there's also ideas that can be shared on how to partner with retailers in the right way, using the right type of insights, bringing value to the table.
Tim Caggiano (55:33):
Just to follow up on that, I think that's one of the first questions was thinking about the e-commerce data ecosystem in Asia versus America and Europe. That's the kind of interactions that we're starting to explore is now that we're speaking the same language. And a lot of that comes from using the same data platform, or at least having a baseline of here are the tools we are leveraging, it can facilitate those conversations. So before when it was different ecosystems, different data points, now I can go run a SQL script and pull down keywords from all of Nestle's countries and see their share and how we're doing across all of our countries. That's powerful. And then we can say, all right, well, where are we seeing similarities? Where are we seeing differences? And then facilitates those conversations with individuals who might be working on the digital shelf there. It enables us to think about best practices, not only from a retailer specific perspective, but also country specific.
Lauren Livak Gilbert (56:38):
Fantastic. Well, thank you everyone for great questions. Thank you Salim, Tim, Michael, for all of your insights and for sharing that with the group. For those who ask the question, you will receive a recording of this in your inbox. Really appreciate all of your time today for listening to us and then Salim, Tim and Michael for sharing. Thank you all for being here. Really appreciate it. Have a great rest of the day everyone.
Peter Crosby (57:01):
Thanks to all our guests for sharing their wisdom. There will be even more wisdom live and in person at the Digital Shelf Summit in New Orleans in April. Go to digitalshelfsummit.com for all the details and to register. Thanks for being part of our community.
