Enterprising Insights: Episode 9 – NRF Wrap-up and Insights

Disclaimer: The Enterprising Insights webcast is for information and entertainment purposes only. Over the course of this webcast, we may talk about companies that are publicly traded and we may even reference that fact and their equity share price, but please do not take anything that we say as a recommendation about what you should do with your investment dollars. We are not investment advisors and we do not ask that you treat us as such.

Transcript:

Keith Kirkpatrick: Hello everybody. I’m Keith Kirkpatrick, Research Director with The Futurum Group, and I’d like to welcome you to Enterprising Insights. It’s our weekly podcast that explores the latest developments in the enterprise software market and the technologies that underpin these platforms and applications and tools. This week, I’d like to take a few minutes to focus on the key trends within the retail market and how they impact the enterprise applications that are being used by retailers. The impetus for this topic is of course that I was just at the National Retail Federation’s Big Show 2024. This is the large trade show that takes place every year at the Jacob K. Javits Center in New York.

Once I go through this recap, then of course I will close the show as always with my rant or rave segment, where I pick one item in the enterprise software market and I either champion it or criticize it. So, let’s just jump right into it, talk about the National Retail Federation’s Big Show and some of the underlying trends within the market. Now, I’m not going to rehash all the developments on the show. You could go online and take a look at some of the very good recaps that are out there in terms of all of the exhibitors who were there, all of the different keynotes that were taking place. I believe Magic Johnson did one, but I wanted to focus in on a couple of key themes that really were brought to the forefront at this year’s show.

Of course, the big one, of course, is artificial intelligence. Now, we’ve moved beyond just the gee whizz notion of artificial intelligence in the retail environment. And now what we’re starting to see is how AI is being used to really improve, not just in-store experiences, but the overall experience of employees, the overall impact on operations, and then of course, yes, for those in-store experiences and of course really linking all of that with all of the activity that occurs in the digital realm as well.

And why are we doing this or why are retailers doing this? Well, obviously there has been a massive emphasis being put on increased personalization. Really when we’re talking about personalization, it’s not just that these retailers really want to get to know everyone better, because they have this deep desire to care about each individual customer. Of course they do. They want to have them come back, but really what they want to do is make sure they understand those customers, so that when they either enter the physical store or if they go online, that they are being served up the types of experiences and products and services that will most appeal to them, not just in general, but of course based on those particular situations that they might be coming to their store for.

So, for example, if you think of how retailing used to be, there was no internet back in the day, of course. You would go to a store and a lot of times you were greeted by a salesperson, would come up to you and say, “Hi, how are you doing? Welcome to,” whatever the store might be, and then ask you, “How can I help you?” And a lot of times the conversation would go something like, “Well, I have a…” Whatever particular situation coming up. “I have a big ski trip coming up,” or, “I’m going camping,” or, “I have to go to this formal event and I need some more formal clothes to go to this.” And you would start a dialogue trying to understand not just what is the item you were looking for, but what the situation was. And this is starting to happen in the retailer environment, because retailers understand that it’s sort of like just saying, “I’d like to see this particular item,” doesn’t really get at what the underlying needs might be for that customer.

So, what are we starting to see? We’re starting to see, again, digital assistance starting to ask some of these same questions and asking them, or letting customers come to them online and say, “Hey, I have a trip coming up and I’m looking for these types of things.” With that information, there can be a lot of additional personalization provided. We can talk about things like add-on purchases. So if you’re coming in looking for a suit jacket, well, you probably also need a neck tie along with it. Or if you’re looking for camping equipment and you’re looking to buy a tent, you probably need some other things as well. Now that’s pretty basic in terms of an example, but the idea is that you’re trying to frame the interaction around how can that store meet your needs based on the situation rather than just looking at a specific item.

The other thing that’s of course going on is that when you actually have a customer come to an online store, you’re getting served up many different experiences. You’re getting other types of products served to you, you’re getting perhaps guides, helping you out, learning how to use their product better. We’re starting to see that migrate to the physical space as well. And the reason for that’s pretty simple; with the advent of same day shipping, overnight shipping, digital fulfillment, there have been fewer and fewer reasons to get people to actually get out of their house, get in their car, hop on the subway and head to retail stores.

So stores are really needing to up their game in terms of the actual in-store experiences. And as a result of that, they’re using or they’re trying to understand what it is that will actually bring people there to those stores. And a lot of that really revolves around these enhanced store experiences. So that can be everything from being able to try things out in a very seamless way, or to have information pop up automatically when you’re looking at an item, to provide more information. All of those types of things are being worked on by your retailers. And the thing that links all of this together, of course, is data.

And when we talk about data, it could be everything from past history, or past behavioral data from customers. And that comes from either previous in-store visits or data that’s captured when they use items or when they use things like in-store applications on their mobile devices. And of course, any activity that may have occurred online at that store’s particular website. And the idea is that by taking all this data and then being able to link it to other types of operational data, so things like stock information, am I able to… When I do actually go down to that store, I want to make sure that whatever item I’m looking at is actually in stock and it’s available now. Also looking at information like advertising and promotional information, making sure that they’re getting promos that are directly relevant, again, to that customer’s individual situation, past histories, all of that kind of stuff.

And even fulfillment information. So if you say, “I am going on a camping trip and I’m leaving on Friday,” and today is Tuesday, you want to make sure that you’re only serving up the equipment, or the products that are actually going to be available to that customer within the timeframe that they need it. That is real personalization that actually provides a benefit to the customer, because it is relevant, it’s timely, and it is information that really will help them move through that whole purchase process much more smoothly and with as little friction as possible.

And we’re seeing that large application vendors are really starting to focus on all of these elements. Companies like SAP, Google, Microsoft IBM, Salesforce, all of these companies at the show were talking and highlighting their various platforms and applications that are directly relevant to retailers in terms of helping them provide all of this additional functionality. It all comes back to making sure that they’re able to pull data from wherever it lies within the organization and make it available to whoever needs it. And that could be customers who might be online, or customers who might be in the store and increasingly making it available to store associates.

So if they’re interacting with a customer, they can have that information available to them as they’re interacting with the customer instead of having to go back and look something up, or call a supervisor, or anything like that. So we’re starting to see a lot of this information being automatically fed directly to store associates when they’re logging into internally, using a handheld device. And all of this, again, is just designed to make this purchase and shopping process as efficient and as friction-free as possible. Because ultimately when you think about what customers are doing, if they actually are leaving their homes, they want that experience to be as seamless as possible, as friction free as possible, so it almost mirrors the experience that they have when they’re online.

Now, another trend that we’re starting to see really take off, and it’s been in the works for a while, is this shift to mobile purchasing and payment. I think there was a study that came out recently saying that in the most recent holiday shopping, a majority of people actually wound up making purchases on their mobile device as opposed to on desktop. That’s pretty important, because it really portends a shift in the way that organizations, that retailers are presenting their products and service, because it’s a different type of user experience compared with looking at something on a big desktop monitor or something like that. This is where you’re going to want to make sure you have more in context information available to that user in a very seamless way, in a way where it’s easy for people to quickly get that information when they’re out and about.

I think the other thing that dovetails with that is that this shift to supporting different types of payments, we think of the younger generation, they never carry cash. They’re using all sorts of other payment methods, whether we’re talking about Venmo, PayPal, Google Pay, Apple Pay, WeChat pay, all of those types of applications. And the idea is making that as seamless as possible, making it super simple to do, because ultimately nobody is going to want to take multiple steps to complete a purchase anymore, because there’s too much friction involved, it takes too much time. And quite honestly, just like we used to see on the web years ago where you had a SNAFU with entering your credit card numbers, things like that, if there’s too much friction, people will abandon the purchase online and then will do so as well in store. Because if let’s say their Apple Pay doesn’t work, they don’t have anything else with them, they don’t have another card, they don’t have cash on them, and if you screw up that process, you’ll lose the sale.

Now, another thing that we’re seeing quite a bit of a focus on, of course, is the desire to improve AI chatbots. And these can be used either as a link directly to consumers who might be either on a mobile app or might be on the web. And the goal here is obviously to make sure that they are able to get the information they need either before they go to the store, while they’re in the store, if they’re shopping online or if after they’ve made a purchase, they’re able to get the service they need. Obviously, generative AI is playing a big role here. It really is, because they’re trying to make it as easy as possible for people to interact with these chatbots in a natural way. And the idea is that you should not have to go through and ever deal with a typical web interface of clicking boxes, choosing dropdowns or radio boxes to get the information you need. It should be as simple as a human to human interaction.

So we’re seeing a lot of investment there. The idea here is that consumers want to be able to handle a greater number of tasks simply by talking with, or chatting, or typing in and dealing with a bot, because in a lot of cases, it’s quicker, it’s just much more friction free, particularly for low level tasks like checking to see if a product is in stock, or checking to see when something might be delivered or it might be available in store. And I think there’s a lot of value there, obviously, for retailers as well to make them as user-friendly as possible, because the more that consumers wind up using them, it’s more data that gets fed back into their system to really understand; what is it that’s making a shopper make a purchase decision? What are the points that they’re having questions about?

And by capturing all that information, they will get those answers and over time they’ll be able to better refine their product mix. They’ll be better able to adjust things like; what is the expected shipping time for certain items? All of that kind of information really will come from capturing more data accurately and timely, and chatbots are a great way to do that. Now, one of the other things that is going on, of course, is that generative is being used to help out in-store store associates in dealing with customers by making it easy for them to quickly access, pull up or even directly serve to them information either about products, services, or even customers as they come into the store. This is critical, because again, as I’ve mentioned in the past, if you are a consumer and you go into a store and you are not treated as an individual, you’ll find somewhere else, because quite honestly, just going up there shows that you have a vested interest in purchasing something anymore.

Few people just go to stores just to browse around and not have any idea with what they’re looking for. Generally it doesn’t happen as much. You might have something where people may still showroom, they might find something on the internet and go to the store to check to see if they can get a better price, but ultimately they’re motivated buyers. And once you have them in the physical location, it’s really important to make sure they are treated as individuals, because honestly, retailers will have the data and they’ll be able to provide that.

And ultimately, when it comes down to it, if you as a consumer going into a store and you have an employee that does not provide that type of experience, you won’t go back. We’ve seen the implications there. I think there was some news this week, Macy’s just announced they were going to lay off something like 2300 or 20,350 employees. I think Wayfair announced they were laying off employees. And really, what does this say? It means that ultimately retailers need to do a better job in terms of really reaching out and making sure they understand their customers, understand their needs and make it easy to shop for and purchase products.

What I’d like to talk to you about next is something that we’re seeing in the market and that is Walmart. They’re going to be raising the pay of their managers, I believe with a new average salary, about 128,000 a year. That’s up from about 117,000. The interesting thing here is that these managers, in addition to getting a long overdue raise, a lot of their compensation is actually going to be based on their bonus. And this is really going to be all focused on store profit. So what does this mean for retailers, particularly Walmart? Store managers are going to have to figure out ways to really try to drive profitability within their stores.

How do you do that? Well, you really need to, again, lean back into this idea of personalization. Personalization will help make sure that once a buyer or a customer comes into the store, that they’re getting the right offer at the right time, with the right product or service. Walmart, biggest retailer in the world, they have tons of customer data. And that is, there’s a significant opportunity for store managers to leverage that, even before the customer walks in. There are tools that are being announced by some of those major vendors which are able to create more personalized advertising to these customers based on their past history.

And then being able to take that information and then roll it through the entire customer journey will really help to create more personalized offers that really try to motivate customers to take action based on that information. And this will, of course, if you tie a bonus to a store for profitability, it’s really going to be about making sure that you not only drive up the top line, but make sure that the stores operate the most efficient way possible. And this is also where things like AI being used as a tool to help your store employees to work more efficiently, to work more quickly, and ultimately to make sure that they’re trying to move the right products to those customers, that’s going to be a real key moving forward.

And then finally, in terms of looking at the retail market and how it really impacts the enterprise application market, we’re going to see some more consolidation in terms of platforms. This is a larger trend, but particularly now as, if you look at the retail market, there’s a lot going on in terms of customers still being somewhat wary about spending. Some may spend more, but ultimately the economy is still not 100% solidified. We have an election coming up. So, retailers are going to have to make sure that any investments they make are really, really focused on driving as much profit from each customer as possible. And again, that really comes down to understanding who those customers are, what their needs are, and then providing them with the most targeted and personalized products and services as possible, so they are ultimately being well-served and not moving to a competitor.

Now, I think as we look forward in the marketplace, we are going to see a greater number of tools being released over the next 6 to 12 months that are going to help retailers accomplish some of these goals. Ultimately, it’s all going to come down to making sure that retailers have a clear data strategy in mind, making sure that all of the information that they have within the organization is accessible to anyone who needs it. And that really means that everything from promotion data, to product data, to fulfillment data, all of that data is clean and available for all of the systems that need to utilize that information.

And that’s where the retailers need to make sure that the platforms they have can support that with the right integrations across a number of different applications. And of course making sure that once that information is made available, they have the right tools to really activate it and deploy the right programs to really connect with their customers. And I expect to see that happen over the next 6 to 12 months. Retailers have obviously understood that the future for them is really based upon creating better experiences, more data-driven experiences, and that is going to be something that carries through over the next several years as we move forward.

Great. So now I’d like to come to our rant and rave section, which is always a hit with our listeners here and today, surprise, surprise, I actually have a rave. Normally I’m ranting about something, but I will say that if there’s one thing that I was really pleased to see is that going through all of the different large vendors at the National Retail Federation Show, I saw a real focus on looking at AI being used as a tool across the entire organization. It was not just about looking at the shiny object of; let’s talk about generative AI, so we can create better chatbots. It was not just this singular focus on customer facing tools. It was really about looking at how generative AI and predictive AI could be used across the entire enterprise.

Because ultimately the goal here is to really reduce friction across the entire value chain, everything from looking at how products are delivered or made available to retailers, how marketing is carried out, how fulfillment is carried out. The goal here is really to reduce friction and make processes as smooth as possible. Because when that happens, you have happier customers, you have happier employees, which in turn makes them more motivated. And ultimately it creates a much, much more seamless experience for everyone involved. And that that really does… It really is reflected in the in-store and digital experience as a customer.

When you go through and you can see things are smooth, see that things are seamless and you don’t have to jump through multiple steps to accomplish specific tasks, it makes you that much more likely to continue to do business with that particular retailer. And I’m happy to say that it seems that that has really been this point of focus for all of the vendors there in terms of trying to provide those tools across the enterprise to really help out their retail customers. So unequivocally, that is a rave for the week.

Well, that’s all the time I have today, so I want to thank everyone for continuing to join me here on Enterprising Insights. I’ll be back again next week with another episode focused on the happenings with the new market. And so I’d like to say thank you very much again for tuning in and be sure to subscribe, rate and review the podcast on your preferred platform. Thanks and see you next time.