It's time to close the in-store data gap


Art Peck, CEO of Gap, Inc., on a recent call with investors declared stores to be "the deepest form of customer engagement" and praised their value as "a source for an immense amount of customer data." And yet, retailers struggle to give in-store shoppers the personalized experiences they have come to expect online. By enriching their knowledge with in-store behavior sensing and advanced analytics, retailers can continually improve operational efficiency, deepen customer engagement, and boost their bottom line.


Al: Hello. Good afternoon and good morning everybody, depending on where you are in the world. And welcome to another RetailWire webinar. This one is entitled, "It's Time to Close the In-store Data Gap." And this is sponsored by Samsung SDS. My name is Al McClain. I'm one of the founders of RetailWire. If you don't know about us, we'll tell you a little bit in just a moment. But just for a second, if you see in the lower left-hand corner of your screen, there should be a chat button. And if you want to just click that chat button and that's how you're going to ask questions today. So, to familiarize yourself with that, maybe you just want to tell us where you are located in the world or maybe what company you're from. So, if you'll shoot those in there, we'll take a look. And we'll get better acquainted.

In terms of our background on RetailWire, we are the largest expert discussion site in the retailing industry, 90,000 sessions per month, 32,000 emails subscribers, and over 60,000 social media followers. But most importantly, we have a unique brain trust panel of industry experts with over a 150 panelists who weigh in on our three daily discussions. And you can weigh in, as well. Just go to retailwire.com. And in terms of our agenda for today, the first thing we're going to do is Joseph Landers, who is director of retail group at Samsung SDSA, is going to give us an interesting presentation entitled "It's Time to Close the In-store Data Gap." He's going to kind of tell us what's possible. And then, Julie Bernard from Verve, Meredith Darnall from Brookfield Properties, and Joseph and I will bat around some questions. We'll have some polls that we'll ask the audience. And we'll have a lot of fun. So, I see folks have joined us from Atlanta, Minnesota, New York, Dallas, State College of Pennsylvania, Toronto, San Francisco, Boston, and Chicago. So, hello again everybody.

And let me give you a little background on Joseph. He is the Director of Digital Transformation at Samsung SDS. He focuses on retail innovation using IoT, machine learning, and big data analytics. He has over 20 years of software and services experience, focused on providing the retail industry with highly interactive, personalized, and secure in-store experiences that help drive performance easily and efficiently connecting to the way modern customers shop and work today. So, Joseph, welcome. And I'll put you on your first slide.

Joseph: Thanks for the great introduction, Al. I appreciate it. We appreciate the partnership with your organization. It's been great. So, today we're covering, you know, really the fact that organizations in retail have really too much data. I know it says, “Close the retail data gap." But what we're going to cover are things that showcase where the data gaps are. There's new data based on capabilities with AI, IoT, big data analytics that offer real-time data as opposed to getting data from, you know, corporate. And having it push down on you and not being able to make adjustments in real time. So, let's dive in a little bit and take a look at the different types of data that retailers have access to today. And typically, all this is managed at a corporate level from headquarters all gathered into a large database or a large capability. They get ad data. They get credit card, point of sale. You're getting maybe even, you know, competitive data. You're getting social media data, website information, catalogs, and so forth. All that data gets collected and then built into a report where headquarters is basically saying, "Here's what you need to do differently in your store." It becomes a little disconnected because it's all aggregated into a giant pool.

So, what needs to happen, of course, is making that data actionable. While the actionable data is a little dated, you do get some increased customer transaction value from those traditional analyses that are provided. You're essentially getting some personalized, you know, advertising as well. You're collecting data before and after the sale and those analytics do assist. However, it's not real-time. It's after the fact. So, you know, it does help justify ROI and improve the branding and the brand purchase. But it might be missing just a handful of opportunities that traditional online web interactions might get...you might be getting as a consumer more real-time. So, you know, it really does need to improve, right? We need to improve our marketing effectiveness, whether that is in-store advertising that gets printed, or now usually traditional called DOOH or Digital Out-Of-Home Advertising on digital signage. That data can be put in the hands of the consumers, put on kiosks, you know, on screens, pushed towards mobile devices, or even, you know, in tablets in the hands of store employees to more accurately, you know, kind of predict what needs to change at the time when customers are actually shopping in the store real-time.

So, data needs to be collected. There's lots of ways to collect it. We covered a bunch of those before. Some newer ways of collecting data are sensor data. Those could be video cameras. They could be beacons. They can be, you know, in-store sensors, as well. That customer behavior is anonymized. So, it's all privacy information compliant, not targeting the individual who, you know, may not have opted into a program. That data is collected in a very, very crisp clear way, anonymized, and able to be aggregated almost in near-real-time. So, that targeted marketing information and analytics about what's going on in the store, at that very moment, actually is effective and can be used effectively by both the store and employees, or the digital systems, or integrated digital systems that are in the store like digital signage, which really relates back to increasing marketing effectiveness and allowing store management or even staff within the store to better manage their store operations.

So, just as a visual example, we know that this is an electronic store. It really applies in all sorts of retail. It could be automobiles. It could be digital consumer electronics. It could be clothing, apparel, cosmetics, large shopping malls, mixed use developments, even, you know, giant auditoriums, stadiums, arenas, and so forth, or concert venues. Those video cameras, for example, can collect data. They don't record data. They just basically anonymize the data and store the metadata and you're able to take action on it real-time. And a great example of that real-time analytics that can be impacted or changed is the usage of digital signage.

A great example might be on a hot day, advertise the cold drinks. On a cold day, advertise the hot drinks. If you've got more men in the store and based on your demographic information, certain items are more appealing to those men. If you've got that digital content already created, you can trigger a new digital ad on a digital signage screen. And that screen would not have to be pre-programmed and run on a loop. It would automatically change based on the demographic that's in the store or even change if it's a rainy day and you've got a certain demographic in the store. Let's advertise the kids' raincoats on that particular day, if it's raining or run a special on it from that standpoint.

So, what are the expected results of these types of capabilities? I think we've hinted at a handful of these already. But my favorite is really improving your customer satisfaction. And that's because they're able to buy the things that they want to buy. They're able to relate to the advertising that's in the store. They're able to relate to the sales team that's in the store or the customer associates that are in the store to service that clientele that's there. But, increasing store traffic, as well, getting more people in the store helps. It feels better. It looks better. It's more relatable to your clientele that's actually in the store at that particular time. And also, it allows you to reduce your store operational cost because you can. Well, let's dive into these just a little bit. I'll get into three examples in the next three slides and give you some concrete examples of how these work.

All right. So, benefit number one you guys can read what's on the slide. But if you're a store manager or even an assistant manager, you'll be able to actually take a look at the monthly traffic counts, the traffic counts by weather, how it varies by day, by situation, time of day. And if you can imagine what that data would allow you to do, well, that really relates right back to staffing levels. Historically, certain days you're going to have records and logs of what you need for staff. But this is concrete data that you can share and utilize day by day, hour by hour, minute by minute. When it comes to merchandising a store, knowing which areas of your store are working doesn't really take a software solution or a technology solution to do it.

You can observe it yourself. But what this also provides is concrete data that you can relate to, in case you've got a store district manager or corporate headquarters saying, "Well, you know, it's not time for you to remodel this section or update this area of the store." You might be able to adjust to your individual markets needs or dynamics to address, you know, marketing requirements. So, if one area of the store is not doing well, others are doing well, you can dynamically change that and re-merchandize after hours or even, you know, during your store time or during a downtime when you have extra staff, when you didn't plan it.

You can also basically improve the areas of the store by changing the digital marketing and dynamically advertising based on the demographic, or the weather conditions, or other external capabilities that can be pulled in to the IoT analytics system. That all sounds like a bunch of technical stuff. But what it relates to is you, me, and all of our colleagues and co-workers and our customers are now seeing exactly what they need to see, things that relate to them and cause them to create that impulse to either buy or ask more questions or engage with your store or with your brand. It also gives you a much better feeling while you're in the store. And you feel like you're immersed into a digital experience, as well as a physical experience, all at the same time. And as you see in this particular picture, it's a retail environment that includes automobiles. It could be a department store, as well, with different sections or areas.

And then lastly, the third benefit I kind of related to just a little bit earlier. But off-peak hours can be identified, also basically well-documented. That way you have the ability to then, you know, and your staff accordingly. Instead of guessing how many people you need, you can literally do better planning associated with that based on historical data. The more you have this running, the longer you have it running, the better you're going to be. It can also help you do some weekend promotions or weekday promotions, based on the demographic that you have in the store, as well.

So, I think that really helps you plan and execute your staffing. There's a quite a few other benefits associated with, you know, the real-time analytics capabilities that we have from IoT sensors that can be placed in the store, not just digital signage, not just staffing, not just merchandising. But we wanted to highlight the top three for you in this presentation. And lastly, let's dive into a real world, you know, kind of example or scenario. The store manager, you know, would, you know, already know all the existing reports that they have from the existing headquarters or even their own individual store. But that's based on historic data. What they would really want to be able to do and if you move from the as-is state from historical data, and the way you run store operations today, being able to make those dynamic shifts in the advanced or to-be capability requires a few things.

It requires some technology and some capabilities. So, people counters, crowd analysis, facial analytics, these types of analytics tools allow you to then do dynamic digital signage, put more information in the hands of the staff that's in the store at the time that they're in the store. And then, even take some of that, you know, off their hands and put it into a completely automated and integrated solution. So, it gives you some integrated management capability, as well. It really integrates perfectly with the store operations. It's not onerous. It's super simple and can even work in offline mode so that, you know, you don't even have to think about it. And you can just run your store the right way and let people interact as they're self-shopping. So, with that I think, we're going to introduce some of the other panelists, Al, Meredith and Julie. And I'll let you do that.

Al: Okay, Joseph. Thank you very much. Yes, in terms of our panel, you can see who they are right here. I just want to remind the audience, if you have a question for Joseph on his presentation or on our panel discussion, use the chat function. And Joseph, a couple questions, so far have come in. The first one is asking about what the cause of the lack of sharing of actionable information at the store level is. Is it, you know, organizational culture, or is it having the right tools, or money, or lack thereof, or something else? Can you shed a little light on that?

Joseph: Yeah. I think it's a handful of things. It's going to vary by company to company. The technology and the capabilities wasn't there at a price point, I think you know, over the last four or five years, yeah, it's been around, but typically being used in flagship stores maybe experience centers just because, you know, the scale and capabilities weren't, you know, at such a point where it could be deployed at a store level. So, I think that answers it, but I think you're the person who answered the question or asked the question on the chat window, they're absolutely right. Those are reasons, as well. But I think the technology has advanced so much at a better price point. Manufacturing volumes have gone up. And it's reduced some of the costs in order to make this cost-effective more quickly. And I think adoption of, you know, digital science when a screen used to cost, you know, $15,000 five years ago for a large format display now, you know, is extremely cost-effective. These other technologies added along with it now make it very dynamic and, you know, competes with, you know, even print advertising in terms of cost level or even much more effective.

Al: Okay. And then one other question, can this data be used for out-of-stock analysis?

Joseph: Can the data be used for out-of-stock analysis? Candidly, there are some other tools that we're working on now. It's more of a little bit of a future. Out-of-stock analysis really would relate to your store inventory system. Although merchandising on the store floor, there are some really cool capabilities that we probably have under development that would allow you to say, "Okay, this display used to have merchandise on it. Now, it's in a different state and doesn't have merchandise on it." That level of capability may or may not really mean that you're out-of-stock though. It may just be able to alert you to, you know, check this section of the store, re-merchandise it, and refold the clothes, or restock the cosmetics, or you know, hopefully, you know, replace the car that just got stolen.

Al: Okay. And a couple more that have come in. So, question is, how did the sensors perform crowd analysis, other than getting just a headcount, gender, and possibly age? What other crowd characteristics are gathered?

Joseph: So, if I heard you correctly, a headcount gender, age. We also do get a, you know... Obviously, we call that demographic. So, I would call that demographic and behavior. Those are the two categories that I think got summarized. So, yes those are in there. We also provide a capability known as sentiment analysis. So, this is particularly effective out in the marketplace when you're creating ads at a corporate level. They get stored in the digital signage database in the in the cloud, and then push down to your digital signage. Essentially, while an ad is playing, we could measure whether it's effective or not. So, dwell time, whether they're happy, sad, surprised, neutral, these types of sentiments are, you know, very effective at determining was that ad actually effective and is it engaging for the audience that's viewing it. That type of data is really important when you're working with your agency at the headquarters level. So, you can help provide quantifiable data about how that advertising is to be created and changed for future ad campaigns or dynamically updated for the next day or the next week. And so, that can be dynamically pushed back down through the systems. So, I believe I've answered that question. I think it helps a lot.

Al: Okay. And then we've got one more. And then we'll move to the panel discussion. The last one is, how can a brand that lives within the retailer benefit from this information?

Joseph: Okay. So, I believe the question is how can a brand benefit that lives within a retail or benefit from it?

Al: Yeah.

Joseph: So, that could be a department store, it could be a large, mixed-use development, or even like a Brookfield property. You know, kudos to Meredith being on the call. I'll just throw this out there. You might have a Chanel or somebody else within a particular department store or stores within stores. And I think this is a concept that this works very, very well in. You can provide technology that allows that the store within a store or a brand within a store really gather more information about who is interacting with that brand? What demographics are there?

It gets back to gender, behavior, demographic information, sentiment analysis. And that can all be translated into real actionable data that can change the way the consumers are interacting with it, when maybe a store associate isn't available. And that data gets lost or is never captured. So, brands love it. We've seen those types of capabilities in pop-up scenarios, as pop-up stores. You can put a pop-up store anywhere within a large property or even a store within a store. And brands are seeing a lot more exposure. They're getting aftermarket sales. They're increasing revenue. And they get a lot of brand impressions from it.

Al: Okay. So, with that, we'll move to our panel discussion. And I want to introduce our two other panelists. So, Meredith Darnall, is SVP business intelligence and strategy for Brookfield Properties leading the intelligence and strategy team for the retail real estate company. She established their proactive insights department and spearheads efforts in applying emerging technologies and trends that drive success to the company's 163 regional shopping centers. She has over 20 years experience as a leading expert in retail, real estate, and business insights. Prior to joining Brookfield Properties Retail in 2006, she was the real estate research manager at Nordstrom where she managed store site location strategy for all of the Nordstrom and Nordstrom Rack locations.

So, welcome Meredith. And last but not least, Julie Bernard, chief marketing officer at Verve, where she leads their brand strategy, marketing, analytics, and creative services. Previously, she was SVP of omnichannel customer strategy, data science, loyalty, and marketing technology at Macy's, where she was recognized as a customer-centric leader implementing data-driven approaches for strategic growth, including award-winning personalized communications at scale, first-of-a-kind loyalty programs, and modern media attribution techniques. And prior to that, she held executive leadership positions at Saks Fifth Avenue and XRoads Solutions Group, a boutique retail consultancy. So, welcome Meredith and Julie.

Now, back to the audience. I'd like to ask you your first poll question. So, the poll question is how far behind major online retailers are physical store retailers in understanding the buying behavior of their customers? So, do you think they're way behind, somewhat behind, about even, or actually they might be ahead? So, how far behind do you think physical store retailers are relative to major online retailers in understanding the buying behavior of their customer? So, just click the button that represents what you think. And let's take a look at the results as they come in. So, it looks like about half of you think that they're somewhat behind. And the rest of you think they're either ahead or way behind. So, looks like the consensus is that they are somewhat behind. I'll just let this go for another few seconds here. And we'll wrap that up. And go to our first panel discussion. So, question number one for the panel. We'd like you to talk about the difficulty retailers currently have in attributing in-store purchases to marketing exposures. What form of in-store data would be most valuable in solving this problem? So, Meredith, if it's okay, I'm going to come to you first on this question.

Meredith: Sure. Thank you, Al. So, of course at Brookfield, we see that store visit as really the strongest marketing exposure that a brand can offer because it's a thoroughly immersive experience for the retailers. And what we often find is our retailers understand what's happening within their four walls. They have a little bit of realization on a day-to-day basis. But they're not seeing what's going on outside the four walls. So, they're blind to what the trip driver was that brought the consumer into the store. And then once the consumer leaves, what was that posted, that exposure, and how do they really start to think about the brand and really talk to that. So, having that attribution platform where a retailer can identify the customer at any meaningful brand touch point and link it is really important.

So, as we're having activations and we try to drive content in our common areas and partnership with our brand, being able to then understand who's interacting at that activation, deliver those insights back to the retailers, they can pull the customer back into the store, and really start to personalize that location for the customers, we think is really important. And I even like to see it kind of go one-step further. We can really start to invent little loyalty platform means for consumers. And this is something that I think we see online retailers, retailers driving very well where they do fun surveys with their customers and they're visiting, they're asking a lot of questions about their brand preferences, their lifestyles that they're interested in. And they're taking into account all information. How can we really enable the customer to come in the store and have that same experience using the in-store analytics and their mobile invites that kind of unlock a way to start a dialogue with that customer? So, then we can start to attribute what exposures and other brand touch points have led the consumer into the store.

Al: And Joseph? You want to go next?

Joseph: Yeah. I'm going to revert back to things that Meredith said. I mean, I think she's dead on. In our experience working with our customer, she's right on top of that. If I would also add to it though, I think that having a digital experience or a mixed experience within the retailer's environment matters. They're shopping on the web all the time right now. But they're also physically coming into a store. So, kind of linking those two together by adding a little bit more interactive digital technology, whether it be in the form of a kiosk, an interactive display, in-store advertising, or dynamic in-store advertising, or even cross promotions, those are leading to sales I think from an in-store, you know, marketing purpose.

Al: And Julie?

Julie: Sure. I'll build on what both Meredith and Joseph said because I do agree that the store visit is a key metric of brand health and the frequency of that visit and purchase visit, in particular, and definitely, thinking about the digital points to capture that understanding. But I think the critical piece from my perspective is to anchor identity and your identity graph to a mobile device. And surprisingly, many retailers don't realize how this can be accomplished because mobile device IDs can be matched to households in privacy-compliant, privacy-sensitive ways. And obviously, PII and CRM data sets are matched to household. So, today the mobile device ID becomes the way to actually measure the store visit. You can physically see presence of the device in a building. And media platforms are all connected to or powered by mobile devices. It is the central hub of a consumer's life. They're spending five and six hours a day on their smartphone.

And digital out-of-home, connected TVs, natural interfaces, all the various in-home IoT devices, wearables, connected cars, all of these touch points and potential media platform environments are connected and powered by these mobile devices. So, if we start to re-frame identity management around mobile, then mobile becomes the way that you can not only observe the movement patterns in your physical location and understand dwell times, but now you can actually match it back to actual purchases. So, not only the store visit and whether or not it's an incremental visit to prior patterns of movement, but you then actually can really start to understand not only what people are doing in store, but observe where they go before and those types of movement patterns informing who they are to create more relevant experiences in the physical context. So, the screens, as Joseph was saying, the price has come way down that barrier is gone. But how can I make sure that the content that is being presented when there's presence of a device that can be triggered by that device, but on the digital screen? So, there's a lot of things that can be done to operationalize and execute through the mobile device ID management.

Al: Okay. Anybody have anything further on this one? All right. We will move on. So, poll question two. Which type of data-informed improvement is most important to customers? So, do you think it's most important for them that they get personalized recommendations, more effective merchandising sets, more efficient traffic flow, or better staffing? So, what do you think is most important? I assume by customers we're talking about retailers here. So, let's take a look at the results. And it looks like over half of you are saying personalized recommendations are most important. And then better staffing would be in second place. So, with that as a backdrop, we will move on to our next discussion question, which is what do you see as the worst blind spots in the data views retailer's need to create more personalized in-store experiences? Can you give an example of how a particular data set could translate to a great personalized interaction? So, Joseph, would you like to start this out?

Joseph: I'm going to punt to one of my wonderful colleagues first on this one. I'd love to get their perspective.

Al: Okay. Julie, would you like to...

Julie: Yeah and I'll build on something that Joseph said in his opening piece. One of the questions from our attendees here today on the webinar was about the operational hurdles. Everything that Joseph said was correct. Screen costs have come down, a lot of those types of barriers. Another one related to beacons, Joseph, mentioned it. But I'll add on to that. And a lot of times, a lot of these beacon implementations were negative because they were a separate activity in and of themselves. You could have union labor, off-hours. Lots of locations to have the beacons have to be maintained. You had low battery, you know, short battery life, things like that. The reality is now we've gotten smart.

And with, of course, the IoT of everything, a lot of partners for big retailers now are putting the beacons in their lighting. A company like ours, we have partnerships with some companies. Acuity Lighting is one of them. And when it comes back to this mobile identifier or the beacon signal is only as good as how it is ingested, understood, and then used for an insight. And so, we began beacons in the lighting as an example as a normal course of business. Now, you can change them out as you do that. But then the blind spot is that these retailers still can't see what's happening with consumers, with real people outside of their owned properties, outside of what consumers are doing on their sites and mobile web, and mobile app, and stores. Yet, we can understand people through the lens of their device, where they go in the real world to inform more relevant content and experiences to drive incremental visits to that location.

So, starting to think about some of the more sophisticated and advanced retailers that we work with, all the large household names that you would know in home improvement, and electronics, and in mass retail, with the beacon signal, by putting a software development kit in that brand's app, that SDK in the brand's app can detect that beacon signal. And when working with partners, that can also observe movement patterns in other locations. You can now know, say if you're a Target that someone went to a Petco before coming to your Target, or if you are, you know, Subway that somebody goes to McDonald's beforehand. And you can start to see a more robust view of who people are outside of your context so that you can create even more relevant experiences for them in creating more meaningful and memorable in-store experiences for them. So, I think that the blind spot is not being able to see what's happening to people outside of your own properties. And again, this mobile device, and with the beacon signal in particular, it gives a lot of illumination to who people are in a much more robust way.

Al: And Meredith? What's your guess?

Meredith: Yeah. I'm going to build a little off of what Julie's comment. And I think that even beyond that, it's important for the retailer to have an understanding of what the consumer is doing outside of their four walls. But even have a deeper understanding of when that consumer is motivated and primed to buy. And oftentimes, we hear from our retailers that we partner with in our centers that they're one, you know, that their biggest challenge if they don't know the consumer is in their store until the transaction is complete. So, once the purchase has been made, definitely verification that they know the consumer has even been there at all. Again, thinking about that mobile technology and knowing where the customer is through their device, if we can form that the retailers, that their consumer, was on property at the beginning of the visit.

So, maybe even that day when the shopper steps into the center, they haven't really considered going to one of the main retailers, who are pretty loyal to, but just didn't think of a need that day. If that retailer knows they're on site, they could send a push notification to the phone, welcoming that customer personally to the property, inviting them to have a cup of coffee on them, and come in and see some new and exciting product of brands they know this customer have infinity for. So, being able to use that technology to give that information to the retailer faster elevates the level of service they're able to provide. It really delights the consumer. It's sort of that unexpected, but personal reading and welcome into the transaction experience. It's also benefit to the retailer because if that individual sales associate isn't there, their information can still be shared. And they could still have a great experience that day as they're shopping.

Al: And Joseph, you want to weigh in or...?

Joseph: Yeah, so, you know, punting initially to Meredith and Julie, but I want to build off of the blind spots that they outlined. There are obviously some other blind spots. And I think you're right using mobile basically relating back to the other experiences they've had on their shopping journey while they've been within the property, Meredith and Julie, all these make a difference. You know, seeing a way to particularly, you know, translate into a greater personalized interaction, it's really back to not just mobile, but also the digital experience that they started on the web, and pulling it back into the store and then even pulling external data sources, not just the mobile data sources, but it could be web data sources that weren't part of their shopping journey. It could be just weather, temperature, things that are going on in the in the community at that point in time. Those external data sources could make it much more personal to them, whether they're shopping with their kids or a family, whether the demographic at that point in time is different. All those can translate into getting a much more personalized interaction, not just with the store associate, but also with the digital side of what they're doing inside the physical property.

Al: Okay. So, we do have a number of audience questions coming in. So, I'm going to move on to our next poll question, our last one. Which retail segment would benefit the most from real-time in-store data? So, do you think its supermarkets, department stores, apparel stores, mass and discount stores or C-stores? So, which retail segment or what we used to call channel do you think would benefit the most from real-time in-store data? So, it looks like department stores, and then supermarkets, and then mass and discount stores get the most votes, but it's pretty spread out. The last panel discussion question is many look at department stores these days and say they are in need of a reinvention. Imagine you had access to a full array of real-time in-store data. How would you use it to re-imagine a department store?

Julie: Sure. Thank you. The inspiration I would take here in terms of re-imagining the department store would be from the direct brands that have taken so much market share in the tune of billions over the past three to five years in particular, but really for about a decade. And when I say the direct brands, I'm thinking about Casper, and Lisa, and Peloton, and brand lists, and Hubble Contacts, and so many very impressive brands that have emerged and have taken very meaningful, you know, market share from the traditional CPG retail environments. And I think one of the things that are important as we think about them is their definition of value where it's not just price. But the value equation is about convenience and simplicity and the ease of a truly frictionless consumer experience and environment.

And when we think about in-store, I think many retailers have moved into things that are a little bit more gimmicky, things like the introduction of robots that theoretically could do way-finding for you, but they, you know, bring you to a brick wall. And I think we have to be authentic and really still be thinking about how technology enables the meaningful experience that also has value where the value is about convenience. Yet, we also can take inspiration from the fact that these direct brands, these direct to consumer brands, are opening physical locations. You know, an example where they have openly admitted that they see now that they'll have 50% direct-to-consumer and 50% physical locations. And the traditional retailers have an advantage in this regard where they've always had associates who can deliver on these authentic one-to-one human connections.

So, when I think about the data opportunity here, I think it's time to, as I like to say, and I've been saying it for well over a decade now, liberate the data and democratize the insight. And don't just report on “the what” by putting more data into a tablet that an associate or somebody in the store has to interpret. So, what does it mean and now what do I do with it? Yet, leveraging, the sophistication of AI, various AI capabilities that are out there. Serve up the now what for the associate and empower your associate to deliver to really enable moments of discovery and inspiration, introducing consumers to things they didn't even know that they might want or need. So, that the traditional, physical, retail environment can be empowered and improved through enabling technologies and the insights to be derived from data, not just data for data's sake, but the real now what do I do with it to re-imagine what experience looks like to encourage and inspire consumers to come back to physical locations.

Al: And Meredith, how would you re-imagine the department store with all this new data?

Meredith: I think for the department stores today, they're just, that the broad department is really tough. They have these fixed spaces that are really built around product. And they don't have a lot of flexibility in terms of how they can really serve the changing customer demand. So, I'd like to see a space that is almost like we tear down the walls. And you create this totally flexible space where there's the fluidity in the product or the merchandise categories. And based on what you see in your data and who's coming through, and how that's translating into sales, you could start to really have nimble space and really go after and capture where real customer demand is. And if we can unlock where those interests are using our data, I think we going to start to also build experiences that are really meaningful less around product and more around themes because our consumers are telling us they want curation. They want to have a sense of community in their retail space.

And if you could take that department store and you knew that you had a lot of younger professionals coming in, you could create a space for them that would be not just about apparel they could buy to wear to work and what styling means, but invite strategic partners like we work with to come in and help talk about networking and really facilitating how to start their career and give them this whole educational experience if you can tie back to, you know, meaningful sales and then build a meaningful relationship with that consumer. I also think it's possible for the retailers to really think about how they start to create some whimsy and gamification in that shopping experience too. So, understanding the data and knowing when that consumer walks into the store based on what they're seeing, you could do similar promotions to what Nike has done, which is to host scavenger hunts almost. Have a special hunt through the store that day for this preferred consumer. And let them unlock a special SKU sale that's meant exclusively only for them because they have come in and being able to have that really surprise, and delight, and recreate experience so that people want to come back and start to see what's next and what could possibly be new within this store model.

AL: And Joseph, last word on this. And then we'll move to the audience questions.

Joseph: Yeah, tailing off of what Julie said regarding the use of AI and advanced analytics capabilities, and then what Meredith was saying about how, you know, really the department stores are thinking about how to re-imagine the space that they have, that they've got just awesome amounts of space and the ability to, you know, be an anchor tenant in a huge mixed-use development, really, you can extend with sensors, with the advanced data collection capabilities, customer behavior analysis, which is PII compliant, really end up changing the way you dynamically merchandise the store. You can run easy and efficient, based on the customers we've been working, with store operations and A/B tests on how to re merchandise. And then run marketing campaigns, like Meredith was alluding to, that our dynamic, new, and creative, that are driving really interactions with the customer and the way that they want to shop, and the way they want to experience the space that was traditionally, you know, known as malls, but are now live-work-play environments.

And then kind of tying back to what Julie was also saying on her side with AI, the more data that's collected. And, of course, there's a ton of it that we referencing back to the very first slide that we were looking at. The more data that's collected to make it effective and make it dynamic, instead of relying on those really expensive store associates that are experienced, that cost a lot of money that are hard to find these days because unemployment rates are very low. You're going to have to use systems, and capabilities, and technologies to dynamically, you know, insert intelligence into analyzing the data and then driving dynamic real-time, you know, interaction using the technology that's available to us. And we can help make that a lot easier and we're seeing stores and I think some of the more advanced department stores are doing this much more effectively. They'll be able to essentially then make more money with the brands that they have or the stores within the stores. They can basically say, "Hey, you know, we can charge you more in this area because you're going to be able to get, you know, higher revenues, translate to more sales, and have a higher customer satisfaction at the end of the shopping experience."

Al: All right. So, with that, we're going to move on to...we've got a...we're pretty short on time. Sorry, whoever was jumping in. But I'm just going to move on to the panel discussion because we've got the audience questions. We've got a lot of questions. So, if I could just ask you if you want to answer the question, just jump right in. Say who you are. And we'll probably just take one or maximum two people per question because we've got a lot of questions. So, the first question is how does the brand get access to this data, if it lives with the retailer who typically doesn't share data very readily with brands? So, who wants to jump in on that?

Joseph: That's really up to the owner of the system. So, if that is, we'll, call it the mixed-use development, then the mixed-use development can monetize or share that data with their tenants as part of their lease agreement. I'll let, you know, Meredith talk about that, if she wants to jump in on it. But if it was at a department store level and they owned the systems, then the department store would then be able to share that with the brands that are within the department store.

Meredith: Thank you, Joseph. And yes, that is true. So, we are actually are seeing a level of collaboration that we haven't seen previously between ourselves, and our retail brands, and our tenants. I think we're also going to recognize we need one another to create that dynamic experience for the consumer. And so, sharing as much information as possible is very important. So, oftentimes if our retailers are coming to us asking for questions, what we're seeing through our technology enabled that they were able to collect through our properties, we're very open to sharing in that collaboration and building that partnership. It's only going to make a more meaningful experience for the consumer.

Al: Okay. And the next question is will GDPR or other heightened privacy issues change the info that you can access on consumers?

Julie: I can take that. It's Julie. As our company operated also in Europe and, you know, what I would have to say here on the GDPR piece is that we already have legislation that has been passed here in the United States in California that will go into effect on January 1st, 2020. That will be similar to, not exactly the same, but similar to the GDPR regulation that we saw in the EU. What we will see as a part of that is that lots of data that today are not regulated or legislated in terms of its use are actually going to be re-categorized as highly sensitive data. The important case when it comes to all of this are the core elements of being transparent and giving the consumer not only the transparency, but the control and the consent mechanisms, as well as then the accountability. So, I think what we'll see is more rigor around transparency, control, consent, and accountability.

Yet, through consent and through the really, you know, truly in plain English type of consent. So, people understand that you are in fact capturing data with the intent for the responsible and ethical use of it for their benefit. Then people do give you those approvals and it'll really just be that it's lightly regulated. There's a lot of federal privacy action. I sit on the board of the data board of the IAB and I'm a part of the policy team there. So, there will be a federal privacy-led action in the United States, so that we don't end up having 50 individual states with their own nuances. And that will probably happen next year after the elections. And I think it's a positive thing for both consumers and our industry. And like with anything, think back on the old Oxley days. We'll all do whatever we need to do to be compliant and to improve our people process and technologies along those necessary dimensions.

Al: All right. So, Julie, you're telling me there...

Joseph: I'll get it.

Al: I'm just going to ask, there are elections coming up, Julie? I hadn't heard. Go ahead Joseph.

Joseph: No, I'll just jump in and say, you know, to Julie's point, it's important to recognize that yes, legislation could change, will change. And from a system and a capability standpoint, any system you look at should be looked at from a standpoint of being able to be flexible, being able to take the data, use anonymized data, so, that it's maybe not personal, but personal enough. So, it's not necessarily one-to-one, and that type of capability can be still used on the back end. But legislation will obviously drive those types of things, which is I think a good thing for all of us. We all know we're sharing data all the time. We're signing all those rights away. And I think we're going to have an ability to control them more, which is all the more reason to have both a one-to-one personalized marketing capability with these technologies and systems, as well as an anonymized capability to help operate your business, as well as market directly to the consumer.

Al: Okay. So, we're just going to have time for a couple more because we want to end by the top of the hour. This next one's kind of long. So, listen everybody and give me a quick answer if you can. So, the question is how can retailers do an effective job of measuring the return on experience, ROX, when there is no direct correlation to return on investment ROI? Digital brand experiences are often pushed aside for investments in areas that drive direct sales. So, how do we do an effective job of measuring ROX?

Joseph: Systems are getting much better at capturing real-time data in terms of the experience. I'll point back to being able to measure essentially the effectiveness of an ad through how much was the dwell time? How long did someone engage with that particular ad? Not just how long they were engaged with it, but the level of interaction. So, their facial expression anonymized, of course, being able to gather were they neutral, surprised, engaged, those types of things. That can directly relate back to an ROI through analysis of the larger systems that says, "Hey, this person or these people in this demographic ended up buying 50 of this particular item: those demographics, looking at the point-of-sale data, looking at the credit card data. And then it can be translated to an analysis that says, "This age demographic or gender liked this ad, and they ended up buying this object from a general pool standpoint." So, I think you can maybe not get a direct ROI on the ROX. But you can make the right level of inference that is statistically correlated to the advertising campaign.

Julie: Yeah. This is Julie. I can add one sentence to it too. We see a lot of the brands and retailers that we work with where the CMO and the CFO are as closely connected as the traditional old age of the CIO and the CMO where they're looking at the recognition that is the cumulative impact of thousands of media and experiential touch points that ultimately influence and impact consumer behavior. And so, starting to move away from looking at things episodically, expecting that a single mobile exposure caused someone to buy a home, or a car, or even a, you know, a t-shirt or pair of jeans and recognizing and that it's a cumulative impact of lots of different touch points and exposure points. And so, they're looking at the longitudinal behavior analysis of consumer purchase behavior over time, usually in minimums of 6 and 12-month increments to see was there an incremental purchase visit over a window of time, so just measuring sales through that kind, that kind of...just the lens of real sales that go to the bank.

Meredith: And this is Meredith. Just to affirm what Julie said, our retailers, the most successful retailers that we've worked with are moving to measure that customer lifetime value. And so, as that begins to change and customer value becomes a real measure of success for our retailer, you'll see that they're going to start to look at every touch point that drives to that consumer and how that contributes to the incremental value. It will be a more long-term measure over time. But you should be able to see the added benefit of that experience exposure and how that impacts the customer’s relationship and engagement with the brand.

Al: Okay. So, we're not going to have time to get to all the questions. So, I want to give you the contact information for Joseph, Meredith, and Julie. You see it before you. Yes, you will be getting access to the slides and the recording. You will get an email when those are available. If we did not get to your question today, we'll try to get Samsung or one of, some of the other panelists to get back to you on that offline. So sorry we didn't get to you. And I do want to acknowledge Barry from Dublin, Ireland who wanted to let us know that he was listening in, even though it's late in the day there. And I'd like to thank Meredith, Julie, and, of course, Joseph for sponsoring this and given that great presentation. And if you wouldn't mind, please stick around for just a minute longer to take our brief post-webinar survey. In the meantime, we will see you on the next RetailWire webinar. Thank you everybody. So long.

John Bertoli
John Bertoli

John Bertoli currently serves as Head of Marketing & Partner Services at Samsung SDS America where he is responsible for brand awareness and driving demand through outbound campaigns and optimizing inbound marketing channels to generate meaningful opportunities for the various business units and solutions, namely retail technology, digital out of home (DOOH), HPC Managed Services, blockchain, and retail analytics software.