Making Data Simple: Data in the Retail Industry - Part One
The retail industry has experienced massive disruption over the past several years. Buyer behavior has radically changed with the continued expansion of online shopping. Now, data, machine learning and AI are set to change the industry yet again. Listen to the first in a two-part episode with Patrick Pitre, Analytics Client Architect IBM Cloud, and Renee Livsey, Director, Technical Sales, IBM Cloud, discussing emerging technology trends in the industry and how retail may be ahead in the data game.
01.20 Learn more about IBM Informix
01.30 Learn more about how IBM and Home Depot have incorporated Informix softwares
01.35 Learn more about how companies have been using Informix
01.45 Learn more about Federal Express
02.00 Learn more about Delta Airlines
02.30 Learm more about IBM Watson
03.30 Amazon and WholeFoods
03.50 Stitch Fix
05.50 Learn more about the Creepy Factor
16.00 Learn more about IBM Machine Learning Initiatives
Ready to dig deeper? Check out our previous podcast episodes of Making Data Simple.
Al Martin: Hi folks, welcome back to the Making Data Simple series podcast, this is your host Al Martin. Today I want to talk about data in the retail industry. We did a look at aviation, I think, some time back. So, this is kind of a carry forward. We're going to switch it to retail.
Today I have two guests, Renee Livsey, who is the director of distribution markets for IBM Global Markets and Cloud. And we've got Patrick Pitre, who's the Analytics Client Architect for U.S. Distribution Markets. These are the experts, so I'm going to be able to ask a ton of questions. Welcome guys.
So, look, let's start out with a few introductions. You guys obviously know a lot about retail. Please give a little bit of your history and how you got this knowledge. And, if you wouldn't mind, Renee, I'll start with you.
Renee Livsey: Okay. I came to IBM from the Informix acquisition. Prior to working — in between actually working with Informix I left and went to work for Home Depot for a couple years. I helped roll out their first 200 stores. So I worked in the stores as part of the corporation. I actually had to go in and work in a store once a week -- once a year for a week, which was very illuminating to see how they were going to use your software, how you could help them.
And then I also did about a six-month stint at Walmart. While I was with Informix, one of my two big customers, when I was part of our advanced technology group, was Federal Express. So, I have a lot of experience in the distribution market, which is travel and transportation, retail and consumer product goods.
Also in my time at IBM I've done a lot of work with Home Depot, with Coca Cola, Federal Express, we have a Delta Airlines, Travel Fort — we have a lot of those customers that are around my area when I was in a regional type job. I moved into the distribution market in 2016 as the business unit exec. I’m now the director of the IBM Cloud Unit, which is our cross-brand software, our Watson and cloud platform analytics.
Al Martin: Wow, all right. We have a lot of experience in that statement. So hey, Patrick, can you beat that?
Patrick Pitre: I'm going to give it a try. I've been with IBM for about four years. Been with the distribution market since 2016 when we made the switch. Prior to that I covered a couple of different retailers here in the local area. But, prior to coming to IBM, I was a service delivery manager and an architect at Kohl's.
So, I was living the life of a retailer, implementing and managing data and analytics environments for about four years before coming to IBM.
Al Martin: So, here's where you got Renee. So I know directors, because I'm also an executive. So Renee lives in la la land, and you do the real work. Is that what you just said?
Renee Livsey: Exactly.
Patrick Pitre: You said it Al.
Renee Livsey: I claim it, I claim it.
Al Martin: Fair enough, fair enough. So here's the first question I have for you guys. Very simply, is brick and mortar dying? Is it dead?
Renee Livsey: Well, our customers are really struggling, and I'll let Patrick comment. You know, the Amazon — Amazon is affecting all of our customers, not even just in retail. You know, we've seen them recently talk about they're even going to go into their own shipping, they want to do drones. Recently they purchased Whole Foods, which affected all our grocers.
So, the Amazon phenomenon is real. And people have different strategies to that. And I think you're seeing stores closing. You know, recently Sam's Club is closing, some of the Walmart's are closing. You're seeing Macy's close stores. A lot of the brick and mortar stores are closing because a lot of people want to have everything delivered to their home.
You have a lot of the companies, like Stitch Fix, which I use to deliver clothes to my home in a box, so I can try them on what I like, I send back. It's not stuff that I would usually pick out, but they seem to use our analytics and figure out what I do and don’t like based on what I keep. And so it's really convenient.
So, Patrick, I'd love to get your feedback on that.
Patrick Pitre: Yeah, so I think that the comment that brick and mortar is dying is not that there's no longer going to be a physical footprint of a store. But brick and mortar experience where your shopping journey starts and ends in a physical location is definitely dying. And I would argue probably close to being dead. What I find interesting in the market is, you know, Amazon started its life as an endless aisle online retailer, and now they're moving into brick and mortar.
Because I think what you're — what they're finding and what we see in the industry, especially when you look at the changing demographics of who's shopping, is that people want the flexibility and freedom to both buy online and ship to their home. But also to touch and feel certain products, and get that physical experience with the products that you can only find in a brick and mortar store.
Al Martin: You know, you mentioned the Whole Foods piece. And to give Amazon some credit — I may get the figures wrong here, so I apologize to our audience if I don't. But, the day they bought Whole Foods, I want to say the market — the grocery market — lost like 12 billion in value. It was in 24 hours. That shows you where the investors are thinking when something like that changes. So, I mean, that's a good example.
But, having said that, I mean, I would think a lot of the brick and mortar stores — the one advantage they have is they're in various locations throughout the world. Meaning they could use those as distribution centers just the same, could they not?
Patrick Pitre: Yeah, absolutely. And I think what you're seeing a lot of the big box retailers is that they're starting to go more buy online, pick up in store, ship from store and those types of initiatives where they do leverage their retail footprint as part of their overall supply chain.
Al Martin: Let's talk a little bit about you Patrick. You're an analytics client architect. You seemingly have a lot of information around the retail market. What do you do for your day job? I mean how do you get that knowledge? I mean what's the role, what's the outcome?
Patrick Pitre: Sure, so the simplest way to describe my role is that I help customers while their leverage their data better, through building and designing analytic solutions. So I view my role is kind of taking the three-pronged stool of technology, so technology, people and process, and being able to advise customers about the best way to go about all three of those to deliver better analytics for their business processes.
Al Martin: So, in driving better analytics, is it also driving new approaches to go to market?
Patrick Pitre: Absolutely, so one of the big things that data provides for customers is the ability to transform their business, and find new markets, and go to markets differently and finding new revenue opportunities. One of the big things that I think we'll see in the coming years with data is this concept of selling data or creating new business markets for the data that customers already own.
Not that somebody's going to take personal data specifically and sell that. But large demographic trends, and those types of things that are going to be leveraged between noncompetitive retailers. So, for example, Home Depot taking data that they know about their customer, and, you know, even through kitchen upgrades or building houses, and being able to leverage that with a retailer like Kohl's where they can sell them the drapes, and the other things that go along with building the house that's not competitive to Home Depot. I think people will start to see those two start to become more prominent.
Al Martin: You know, the thing is, it brings up an interesting question that I've asked like the last few podcasts. Because I think it's becoming more prevalent. And that is, where does the line of distinction in that privacy of data reside? Because the more I'm talking to folks in this podcast, the more we're talking about gathering as much data as you can.
Like, whether it's a retailer or whoever, because there's value in that data. Like you said, in this case let's say Home Depot, Lowe's, whoever it is, they collect that data and they can make decisions off it. If you could sell that data, which some companies make a living at as well. Like Nielson or otherwise, but, you know, you can change the game.
Where does the privacy and stuff go in? And how does that relate to retail? I don't know if you can answer that, but I'm just curious.
Patrick Pitre: Yeah, so there's kind of two things there, right? There's the, what we used to call in retail the "Creepy Uncle Factor." So, you want to be careful — it is a technical term. You have to be careful in the data that you're using and the way that you're using that data, because you don't want to injure your brand reputation by being too invasive.
There is that fine line to walk between being able to provide a customer an additional service, or your business an additional stream of revenue, but not be too invasive. That, to me, is really where is consent and opt in comes in. So, I think, retailers are going to have to get more hardcore about ensuring that what they are doing with that data is transparent and that their customers are opting in. Not only for the consumer's protection, but as well as the business themselves.
Al Martin: Well, some of them are actually buying that data, are they not? In other words, essentially, I see a lot of telecom companies or whoever would say, "Look, here's your bill for $100, but if you share your data, $50."
Patrick Pitre: Right. I also think that the changing demographics is going to play a big part of that. So, I have four children and they range from 15 to six, and it's interesting to me that my kids have very little sense of privacy when it comes to online data. They don't see the potential damage for sharing their data online.
And even millennials today aren't as concerned around privacy as I would say that the older generations are because they've grown up in an online and always-on environment where they don't worry about what they put out there. And so I think that's going to allow retailers to do a lot more with data as those generations mature than they would currently.
Al Martin: I think, you know, look we've said — we've repeated this a little bit, but I think you've eloquently put it in terms of demographics. And I think demographics have a huge role to play here. I totally agree with you. We've talked about that in previous podcasts.
So, Renee, those successful retailers, what are they doing with data that others, maybe not-so-successful aren't doing? In other words, what are the successful retailers doing with data?
Renee Livsey: Well, I think they're really looking at the data and how they can use analytics. We have a number of companies really using planning analytics. They're looking at the financials for their data.
But, a lot of them are using more predicted analytics. How can they predict what a buyer may want? And maybe it's because of that linked experience that Patrick talked about earlier. If I get online and go check the weather, I can see the product. They actually market to me what I had already looked at, but hadn't bought.
And so I think that our customers are a lot smarter about trying to take that whole experience and market to us more individually than they have done, perhaps, in the past.
Al Martin: Fair enough. Anything you'd add there Patrick?
Patrick Pitre: Yeah, I would just add that personalization is certainly a big driver within the retail industry. It's getting to the point where it's even hyper-personalization. And, every customer that I've worked with in the past year has some sort of initiative to try to draw more insights from the consumer data and be able to track that journey across all of the channels that they touch their customer in.
The ones that are really succeeding are the ones that are able to draw that 300-degree view of a customer and leverage that within their analytics.
Al Martin: So, I want to talk about personalization here in just a moment. And, particularly as it relates to machine learning. But, the one question I have is a lot of times I talk about the maturity curve where clients are. I’m just kind of curious. The question that I'm going to ask you in just a moment, is where do you think retail is?
You know, when I look at the maturity curve, you know, imagine a curve, and it's a hockey stick where you go from left to right. Where you're in traditional operations, your ERP billing systems, then you go to data warehousing, and you're starting to think about data lakes and that kind of thing. And you go to think about ETL from your traditional systems to your data lakes. And then you start passing into self-service analytics where you're democratizing the access to said data. And everybody across the organization, you know, because you've created new personas, can access that data. And then you really get into new business models, where then you start using machine learning or really taking it to the nth degree where the applications that are being used are data based.
I feel there's like four quadrants, and I find that most the clients tend to be right in the middle. Where's the retail industry? Are they still trying to get out of the operations piece? That first pillar that I talked about? Or, do you think a lot of them are really really pushing personalization, so they're heading towards the end of the hockey stick to really get value. Where do you find customers in the industry right now?
Patrick Pitre: So, for me, it's the aggregation of the customers that I deal with I'd say they're right in the middle. I think, in general, there are departments within retailers that are more forward leading, and that's going to be your marketing and innovation areas — e-commerce, omni-channel, and those types of things — whereas your HR, IT and finance departments are still lagging and trying to get out of those operational analytics types of areas.
In general, I would say they're in the middle, but the one interesting thing that I would add is that a lot of retailers are trying to leap frog the maturity model, and get to that farther AI machine learning piece with implementing things like chat bots and more predictive and prescriptive algorithms in certain areas around retail to try and — not really try and drive the whole organization forward, but at least drive parts of the organization forward.
Al Martin: So, is that the number one game then? Personalization right now to improve customer service and to also essentially market through a personalized vehicle to whatever the customer's interests are? You think that's the game? Or, are there other areas that are equally important that data's playing a role?
Patrick Pitre: So, I would say that that's where the industry is focused. But, that's not the only place they should be focused. There are a number of companies out there that really capitalize on their competitive differentiators, and that's not necessarily personalization. There's a company within Wisconsin that their personal, or their competitive differentiation is really their customer service.
And they treat that — and they know that that's their competitive differentiation, so they're not looking at chat bots, they're not looking at putting machine learning in front of a customer calling in for support. They have people that will answer the phone, sometimes before even it rings.
And so I think it's important for retailers especially to really leverage what their competitive differentiation is, what their brand is, and drive that forward. It may be personalization and hyper-personalization to get your brand more of a household name. But it also might be being able to leverage supply chain better. Or being able to leverage, you know, your competitive differentiation, be it customer service, or, you know, a seamless omni-channel experience that I think retailers need to focus on.
Al Martin: Now, how do you answer the phone before it rings? Wouldn't you get a dial tone?
Patrick Pitre: It is one of those things where as soon as the line hits, they measure and have SOAs around picking up the phone within seconds response times as opposed to minutes.
Al Martin: The reason I asked this question a little bit is, like one of our producers, Fatima, everybody knows Fatima that's out there listening, Fatima Sirhindi. She always says, "Hey, look, we always trend on this podcast to head to machine learning." And she's probably right. Talking about personalization, then, you're probably going to say, "Well, we're using data for machine learning."
So, I think it's like the trend in the industry right now and everybody wants to talk about it. At least it's a hot topic. But I'm also trying to make sure we're being fair around other forms analytics, etc. To your point, Patrick, that a retailers are engaged in, not just the sexy machine learning that we tend to always head, whatever podcast we're talking about.
Renee, if you've got any other examples of where clients are using analytics or any kind of solutions that they're driving based off of data. I do want to talk about machine learning, but prior to machine learning I've got to believe there's a lot of case studies that are being done today that you're involved with.
Renee Livsey: Yeah, we're doing a lot around pricing optimization with a bunch of our customers where we're working with them, you know, and that's all based on their data. But, they're optimizing their price based on their competitors, based on, you know, what they currently have in stock, etc.
But one of the things I did want to share, one opportunity we have is each time — about this time we go to go and actually be personal shoppers for some of our customers. And we sign up for two or three of our customers and we have a whole type of thing that we go through. It's all anonymous. But, you know, you go in there.
But what that also gives us the ability, is to take that data later and really go in and see where they have opportunities they might not realize. Because, you know, for instance I could do it at Neiman Marcus and I could do it at Nordstrom's, and I may have very different experiences. That gives us the opportunity to share with them, you know, how was it more personal to me with Nordstrom's. Or, you know, I actually did a grocery store. I did Publix at one time. So you do the online experience, and you do the store experience. And that gives us the opportunity also to look at our customers and talk to them about analytics and action.
And you mentioned data first earlier Al, I think that's a place where we go in, you know, we can segue into machine learning. And I worked with Patrick on that for a customer where we had to look at the data science and machine learning as well.
But, I think, you know, everybody is in a different place. And, we're seeing in some places there is way over — they're in a very, very innovative in certain parts of the business. And, then, in many parts they're still lagging way behind. So, I don't believe that a lot of them really know how to unleash and harness, you know, harness all the data that they have at their feet.
Al Martin: So, extending that a bit further, I mean, you're going into all these retailing clients to help them with what we'll call maybe a data-first method in transforming their organization to better use data. Can you talk to some of the challenges you're facing? Some of the common challenges you're facing, and some of the solutions that you're presenting on a regular basis?
Renee Livsey: Patrick, do you want to take that since you have done about 10 of these?
Patrick Pitre: The biggest challenge that I see with customers when it comes to the data-first engagements is that they don't know the state of their data or the state of their environment when you first walk in. So, the data-first method really is about starting with their current technology, their current environment and then moving them forward on a road map, in a journey to get them to where they want to go.
And they struggle around, you know, where their data is today, how clean that data is. That, I think, is the biggest challenge. So, the solution, from our perspective, you know, we have a very comprehensive governance platform and information server that is a great tool for our customers to be able to leverage to understand their data, to be able to find data, govern it and leverage it in a much better fashion in their every day.
Al Martin: Are there any — this is my personal question — are there any brick and mortar stores integrating the online experience with the store experience? In other words, trying to take a dilemma and make it an opportunity, given they are brick and mortar? You know, even, you know, I think I walked into a store, I can't remember the store it was, but, it was kind of interesting. They had like different racks and you can actually — they had surveys and ratings right on the racks where you can see what people are rating as you were walking by it, versus having to get your phone out or anything. And you could, you know, have it help you make a decision as you were shopping in that particular store. Is there any unique or innovative solutions that you're seeing — that you're running into?
Renee Livsey: At NRF we are able to see some of the customers, or, actually, the partners who are creating technology. And some of the customers as well. But, you know, there's a lot of technology out there that it will basically show you stuff based on what your eye focuses on.
So, if you're looking at a rack of shoes, and you really keep returning to this one pair, you know, it will give you more information on that. It will look at pricing. If you start to walk away, it may actually give you some discounts. It's pretty innovative stuff.
And that's one reason we like to go to National Retail Federation, is not — it's to really see what our customers are doing. But also what our partners are doing to assist our customers, and in ways we can integrate with them and help them utilize, you know, the existing data that we have. Go ahead Patrick.
Patrick Pitre: I was going to say, I worked with a customer that's a jewelry store. And one of the interesting ways that I think retailers are starting to integrate that online with retail experience is really in the back end. And so we worked with this jewelry store to take data from their online system, and the online journey, and push that to their in-store associates, as well as the reverse, right?
So, their competitive differentiation is that all of their associates in the store, their sales people, are USGS certified on gems. And, so what they've found is that a lot of the folks coming in to shop, the first couple of journeys into the store are educational. For someone like me in my 20s when I was shopping for an engagement ring.
And so they wanted to take that and push that into the online sector. So that, one, they sped up their speed to market, or that speed to sale. And, two, so that you weren't relying on a jewelry store, and the knowledge within that jewelry store — which was typically contained to a mall where traffic is dying — that you can push that education out to your customer, and in online fashion.
So, I think that what a lot of shoppers may not realize is that a lot of retailers are starting to do that more back-end integration, so that the online experience transfers to the associate in the store.
Al Martin: Are spending a lot of your time with visualization with reports to executives with a lot of retailers in terms of understanding their business via sales trends, sales reporting? Where does that play out?
Patrick Pitre: So, it's interesting, right? I'm not spending a lot of time in visualization. It's more around mobile deployment for analytics, because the executives want to be out in their stores. And, I think, they realize that they need to be out in their stores. It's no longer you can run a large retail chain from a corporate office.
So, the big conversations that I've been having around deployed analytics has been on the mobile space and being able to push analytics and applications to a mobile device that allow the executives to get what they need when they're in the field.
Al Martin: That strikes me as odd. I don't know, maybe it's just me. I would think that that would be a huge play from sales trends, production yields, whatever you want to call it, that you would use reporting and visualizing to help drive your business. Do you think that's just, personally, you're not spending a lot of time there? And there's other folks in the business that are?
Or, do you just think it's not — how are they solving that problem?
Patrick Pitre: So, I think the merchants are spending a whole lot more time on visualization, and understanding trends and those types of things, so that they can do better assortment planning. The executives within retail that I've been spending time with, it's much more around — they want to put the data in the hands of the folks that can make decisions when they need to make decisions.
The executives, it's more of a, "I need to know because I'm walking into a store, so I need to know how this store is doing, and so that I can either motivate or dig into what's happening at that store." It's less about taking an action from, "I'm going to change my sales plan" to, "I'm going to be able to effectively interact with that store better as an executive."
The merchants, on the other hand, are much more into the visualization, and being able to see trends, and sales plan and assortment plan for an organization in that space. I do see a lot more visualization at the merchant level.
Renee Livsey: And I think that might be a little bit more mature type — I mean we still definitely — I have a — you know, that's not really Patrick's wheelhouse, he talks to people about everything. But that may be a little bit more mature piece of the market. But we still do have a lot of customers who are looking at visualization, who are trying to figure out — and then we have, you know the integration of, maybe they're even using another product. Maybe they're using one of our partner products like Salesforce.
And then you look at, how do they enable Watson with that? And how can they utilize their existing data — their existing customer data — to put some of that in? And so we do see some — definitely still see some of that. But I think on — a lot of that piece of our market, they have already been using that business analytics. They've already been using the visualization.
And we're continuing to add to it. But for the most part that just seems to be a little bit more mature. And they're trying to get a little bit more innovative in different things they're doing with data.
Al Martin: Hey folks, we had a great podcast on data and retail with Renee Livsey and Partick Pitre, so, this is a two-part podcast. Tune in tomorrow and you will get part two of the podcast. Talk to you later!