FASHION MADE: Evolution of Geo-Targeting with Craig Crawford

Hey, welcome to another episode of Fashion Made. Today I'm sitting down with our first repeat guest, the one and only Craig Crawford. Craig, hello.

Oh, hello. Thank you for having me back. I love doing this, super fun.

It's great, it's great. Today we've got a very different topic to last time. Talking about location-based retail marketing and I guess the power of data when it comes to all of this.

Yeah, yes.

There's a lot of talk about it, has been for a few years now. So I guess in 2018 and beyond, what does it really mean today?

Well, I think it's evolved. You know, there was a lot of excitement around beacon technology and NFC and what you could do. And I think a lot of brands were lured into, oh, send a promotion off, send a discount coupon off, or send an offer. Some brands were quite successful in helping consumers who were nearby understand they were there, or understand what their product offering was, whether it was, oh, we've got this happening or that happening. But I think in general, you have to sort of turn on these notifications. And there's so much noise already. And no one really wanted it to be spammed. And they didn't want these messages, these pop-ups to sort of come in. And sometimes the technology, 'cause it's new, gets things wrong. I mean, I remember when Regent Street did, in London, Regent Street in London did this Welcome to Regent Street campaign, which was all based on, proximity-based marketing. And I remember being in Madrid, and all of a sudden it popped up and said, "Welcome to Regent Street." And it was because the frequency was close. But not very well— I think the campaigns weren't very well executed. And I think people, brands, then felt, "Well, this really isn't so great." And the unlock didn't really happen in terms of having real dialogue. But it's evolved now, and we're in a place now where there is technology to understand where you are in the physical space. So for example, if you go into a shopping center, or lifestyle center, or village, you know, because let's face it, that's what retail has become, are experiences. If you go into one of these areas and go onto the Wi-Fi, and opt in, it's important to opt in, then that is an opportunity for the center to actually help you. So that can be everything from, you know, "Well, what are you here for today?" or navigating or best place to park. Not necessarily things that are on sale, you know, it could be a hot summer day and they're doing a pop-up shop for ice cream. So why not let people know and, you know, enjoy an ice cream cone, come on over and then the ability to monitor who's read that and who's acted on it and watch them in real time move around. So mobile tracking has really, really opened this level of engagement up to be something that's much more important and enriching. And then we have platforms now, one that comes to mind, out of a company in Austin, Texas, out of a company called Carnegie Technology, is a campaign management platform, that's what I call it, called Octopus. But that allows you to then create channels. And it allows you to have that channel, a brand to have that channel, or the shopping lifestyle center to have a channel, and to then talk to consumers. And then based on what they respond to, what they'd like to see more of, what they'd like to see less of, you can really start to tailor these campaigns in these channels. And if you think about the constant dialogue—

OK.

—both with digital video. It can be video. It can be messages. It can be stills. It can be product. It could be anything, anything you want, just like you communicate across different channels lots of different information about the brand. Sure. So it's evolved to be really rich now. And not intrusive.

So the technology's obviously got over those glitches, the Madrid, Regent Street glitch. Yeah, oh yeah. And it's obviously got a bit more detailed in what you can do with the campaigns, as you're saying. Yes. Once you've got that consumer buy-in, that opt-in, as you say, what's their reaction like in the process?

Well, you know, I think it's like anything. Consumers are surprised and delighted when it's meaningful. And when it's not creepy, right? So if you've opted in to receive information around a brand and/or a shopping center, and then you're told your dry cleaning's ready, or you're alerted that the movie that you've been wanting to see has still some seats available, and you can book your tickets right there and go straight in, and you've got 15, 20 minutes to do that, why wouldn't you?

So that's how detailed you can get. I mean, how would they know what movie you wanna see? Well, that's what's— Is that based on your search history and all this kind of stuff? Yeah. So yeah, so it's all data, I guess.

Well, it is, it is. And it's super cool because, and I've said, I've talked about this a lot before, and perhaps not with you, but when we know where you are in the physical space, and we do, because your mobile device tells us where you are, you're on the Wi-Fi. And when we know where you are in the digital space, And we do because you're on the Wi-Fi. Yeah. Right? So if you are standing in a department store in the electronics area looking at a big screen TV and you're online comparative price shopping or just trying to read more about that brand of television, then maybe it's not appropriate to send a message to the consumer doing that. Well, that's crossing over into creepy land.

That's creepy.

But sending over a sales associate and saying, can I answer any questions for you? You seem to be interested in this television. So, you know, notifying someone within the brand to act upon someone who is likely to buy. Yes. And to give them the level of service. That's tremendously powerful. So it's not just chatting with people and, you know, navigating them around to different things. It's creating awareness, but it's also having the brand do new things. Yeah. In terms of customer service.

I mean, that's great because that's obviously bridging the physical and digital, which we've spoken about before, which is obviously a real key element to retail. Yes. Yes. There's also another side to it, which is back in the digital space, not physical, but having chatbots and things like this. Yeah. How are they sort of playing a role in this, this area?

Well, we've seen a tremendous improvement in chatbots. I can't say that every big brand has employed intelligent chatbots or chatbots that recognize sentiment, and when you're frustrated, move you to a person. Some still are using very— I can't believe I'm gonna say antiquated or outdated chatbot technology, which is funny because it's not very old, but But it's hard for a brand— if you think about being a department store and how many people come into that store, if even half of those people are on your Wi-Fi and are now engaged with your brand's channel, and as a department store you could feature multiple brands, whether those are men's, women's, home furnishings, whatever. Understanding your consumer's behavior in the digital space, and over time understanding where they are in the physical space, gives you some indication of what they are likely to be interested in. And therefore, trying to have people monitor that in real time and respond to that with campaigns is pretty hard. No one has that many people on staff. And certainly store operations aren't currently designed today to do that. So this is where— chatbots come into play because they can ask questions about what you're interested in. And then based on your answers, and of course they get better, then they can start to give you more information that's relevant to you. Yeah. And I think I'm quite impressed, to be honest with you, with the banking sector and chatbots. And I guess that makes sense because it's your money and they need to make sure they're doing it right. But I'm— I was recently looking for taxation documentation because my tax returns were due and I was really struggling to find where my tax documents were. Were they in statements? Were they in documents? Were they somewhere? And I'm online trying to do this and it's after hours. I can't really call anybody. There's this live chat and I thought, I mean, not live chat, it's chatbot, but you know how I am, I'm so-and-so, but it identified itself as your chatbot assistant. So I knew I wasn't talking to a person. And not only, you know, well, I'm looking for my tax documents immediately. Well, go here, go there, go there. Was that helpful? Yes or no? Now click this, now try this. 'Now, are you seeing the documents that you need, or are you getting a message?' And I thought, 'Wow, that's interesting. I'm getting a message.' 'Well, yes, I am getting that message.' 'Well, that's because we don't have any for you. You don't need any tax documents.' Okay. And I was like, 'Wow.' Yeah, anticipated what I was doing, got me there, and anticipated my question. So chatbots do that in real time. Yeah, good ones do. Good ones too. And so why, you know, why not? And it's so much harder for a brand to try to do that with people.

Is it a cost thing? Why they're not doing it? Is it as basic as that? I don't know.

That's a good question. I don't necessarily think it's cost. I just think it's just like those horrible, horrible call center screening, you know, press 1 for this, press 2 for that, press 6 for that. Now do this, now do that. And then half the time your details don't go through the call center. I think it's frustrating. They embrace— Infuriating. They spend— brands often will spend so much time trying to automate that, and then they've invested quite heavily. So I think it goes back to not understanding that just like anything digital, there are improvements. Yeah. And sometimes you need to pull things out that you've invested in and put something in better. Yeah. Rather than thinking, I've done it and I don't need to do it again.

Well, the great thing is, is that obviously they learn, you know, that's the point.

And that's the whole machine learning piece, isn't it? And that's the artificial intelligence. So over time it learns more and understands more. Yeah. I have a client and we're doing some very interesting work in this space. And by looking at dwell time on the Wi-Fi, we can create demographics very easily around, oh, this person was here specifically at that time. They were here for this. This person was here repeatedly at these times. Well, we know these things are going on. And therefore, wouldn't we want to target different information to each of them because they're here for very different reasons. Um, and therefore just simple things like that, and then being able to respond and then learning. And the more we learn about what they like, what they don't like, how they respond— if they say they don't want anything else from that type of offer, then you don't do it anymore. So that's the difference between the early days in location-based technology, where when you walk through that sort of frequency, you got a message. But you got a message that was everybody got. Now it's, I'm through, give me something that is relevant to me because you know who I am. And when I'm in this space engaging with you, let's keep the conversation going, not starting it all over again. Or, you know, ask a man if he's interested in dresses or high-heeled shoes, right? Yeah. Well, now he might be, and if he is, you've learned that, you know what department to steer him to. Absolutely. But the point is learning who that customer is and not doing something silly. You know, my— I had pets and my last pet died a year ago, my cat. And my vet— I had two vets— and one of my vets still sends me information about it's time for my pet to come. My pet's dead. Stop sending me information about caring and looking after my pet. I realize you were my secondary vet. My primary vet doesn't do that, but the secondary vet does. Get me off the list. I did notify you that the pet died. Like, it's not only, um, well, it's not traumatizing, but it's a bit like, oh God, you know, a bit morbid.

It's a reminder of that.

And it's like, I don't need that. But also it's like, well, how— what kind of care did you give her? You know, you don't even know why she's dead or alive now. I mean, it does make you think that, even though it's just as simple as someone hasn't removed me from a mailing list. Exactly. And I'm supposed to go in and unsubscribe. Yeah. Why? I called you and told you the pet died. Yeah, you know that. Yeah, get me off those lists.

So they're not listening to you. That—

well, and that's it. And that's the— I think that's the key. And that is what brands are learning now. Yeah, that listening equals loyalty. Yeah, right. And listening is data. Yes, right. And using artificial intelligence and machine learning to better interact to— and, and to then be able to curate.

It must be hard though to truly listen to consumer in a data form because often it's sort of binary, you know, it's yes and no. So I guess that's where the machine learning, artificial, like real artificial intelligence comes in, where it can understand sort of open text and understand complex problems that aren't just, do you like shoes or red shoes or not? You know, a bit more complex than that. That's right. So how do these, um, tools do that? Are they able to really get quite detailed in how they listen to consumers? Yes, and it's a combination of things.

What happens in the store is, you know, gold dust. And we often do, or we have traditionally as brands and retailers, looked at what we bought, what we sold, what we marked down. We look at a spend analysis, and it's no longer relevant, quite frankly. And so now, well, if that sports bra was was picked up and tried on 18 times during the day, but there were no sales. Why? And was it the fit? Was the material too rough? And so these are things that then, you know, we can start asking those questions and we can start looking at why things aren't selling, but they're still being tried on. Or why people pick something up, look at it, and put it down. Yeah. Right? And there are a number of different stores that are doing that and put in-store technology. There's one in the United States, I believe it's called Fabletics.

I'm going to get it wrong. Fabletics. Yep. I've heard of Fabletics.

Yep. And they've, in partnership with Microsoft, they've done all this incredible in-store technology where they can really evaluate. And what's really cool is that anything you, even when you pick something up and take it to the fitting room, it automatically goes into your your wish list, your cart online. So they are merging all of that so that even if you don't buy it in store, you've still got a running list of what you tried on.

You don't have to scan it or something, or—

no, because they're just paying attention to what you are doing, and they understand you as a consumer. And now obviously people have to opt into this. Yes, yes, that's just— doesn't grab them and create a profile for you. You do that. But, but why wouldn't you? Because it just makes it easier. Yeah. Absolutely. It makes it much easier.

Well, I guess it's got to be a two-way street, hasn't it? Yes. Not just to sort of say, oh, you picked up these many things here, you should buy them. So I guess what can people offer their consumers in return for that opportunity to sell them things that they've picked up? I guess that's another side of it. Getting the opt-in is a hard thing. So what can people offer their consumers?

Well, I think if it makes your life easier, I know that sounds silly, But we're all time poor, right? We're so time poor. And actually, there's a statistic, I wish I knew it off the top of my head, but people will pay more, a large percentage of people will pay more for something if they perceive that it's saving time. [Speaker] Yes. [Speaker] The value of an hour, so to speak. So if you are able to make not just the shopping experience, but the retail experience, 'cause remember retail is everything, retail is, you know, Retail is fast-moving consumer goods, right? We all know now, you know, through voice activation, you can not only order something if you need it and have it delivered, but you can also just have your shopping list created. Well, you can also have that all done online and have it delivered, and then you don't have to go to the market, right?

Yeah, exactly.

So it— and that's saving time.

Yeah, you know, so that's the two-way street there, you know, saving time, and then, you know, locked into that, and it just helps me, you know, at the end of the day as a consumer. You still have that power whether to press the buy button or not.

That's right. And, and I think it's interesting how, you know, data is captured across channels. I don't know whether you've been looking at the recent— I don't know if you've been looking at the recent reviews on YouTube of Amazon Look. Amazon Echo Look. Echo Look. Is it Echo Look anyway?

No, I haven't seen it.

But that is— it's basically marketed as a camera that you can do selfies so that you can see how you look in the outfits for the day. And you can keep track of your wardrobe and you can, you know, understand what you wore where. And, you know—

Is it good? Have you tried it?

Well, I haven't tried it, no. But what I think is fascinating about it is, of course, This is data being captured, and how interesting to be able to sell back to a brand. Actually, more people are wearing red, or more people are wearing shorter skirts, or more people are wearing jean jackets, or, you know, whatever the case may be. Yeah, because just because she bought it doesn't mean she wears it. Yeah, right. So things hanging in the closet, never worn, with tags— well, if it was a sellout item because it had hanger appeal or some decent marketing around it, everybody thinks thought they were going to look great in it, and on second thought they didn't. Well, the— if the brand just bases their next season's manufacture on spend analysis, they would believe that that was a bestseller. Yeah. And sometimes it's not.

It wouldn't be right sometimes.

Here's the inventory problem, right? So, you know, it's interesting. It's interesting. Just monitor— not— well, monitoring and reacting to consumer behavior, but in real time. And so that's really what location-based is helping us do. But it can't do it by itself.

I was gonna say, yeah, what are the challenges with it? What are the inherent challenges with this now in 2018?

Well, I mean, part of it is getting the campaign right, getting the messaging right. The data scientists, what are you looking at? What metrics are you defining? What are you going to look at? And how do you keep evolving that strategy? Because like any technology, you have to nurture it and you have to pay attention to it and think differently about your business and continue to evolve your thinking. And that's tricky because we just like to think, well, we buy, we sell, we buy, we sell. Doesn't work that way anymore.

I know. And with all this data, I mean, it's— there's so many different sets of data that you could choose to pick up on. If you wanted to. I mean, the fact—

and retailers admittedly are overwhelmed by the data.

Yeah, exactly. So how do you choose which ones to focus on? I mean, is it business-specific?

Well, I do think it's, it's, it's a matter— and, and by the way, you know, this is where machine learning can help you as well, and the algorithms of artificial intelligence can help you. You know, step back, look at the patterns, understand what the, the, the behavior is. And really think about that. As opposed to, I've got this much inventory coming in, how do I move it? No, let your buy be influenced by this technology. Let your product development and product assortments be influenced by that. And why not try different products through these channels? Why not give people an opportunity for customization or personalization? I think people don't mind waiting And we're seeing fast turnaround times. I mean, you know, yeah, the Product Innovation Apparel Conference, we've got people that are out there now, you know, showing how they can take an order and have it delivered in just a couple of days. Yeah, it's not mass quantities, but the quality is there. Yeah, and those business models work.

So I guess, I mean, if the challenges are there, the solutions to them are to use more of the AI and the machine learning because it will actually help you solve those challenges.

Yes, and, and, and think differently about marketing, think differently about consumer engagement, listen to the customer and respond to what they, what they're looking for. And that's a different type of marketing, that's a different type of customer service, a different type of CRM, so to speak. So it's helping those departments internally evolve because the technology gives them greater and different insights.

I think this is something that we're seeing so much, is this cross-departmental collaboration that's required in modern business with technology. Yeah. You know, you're no longer just siloed doing— you're doing sales, you're doing marketing, we're doing product, you know, kind of all these guys got to work together. And yes, yes.

And it does mean changes for supply chain as well. Yeah, exactly. It all has knock-on effect. Yeah, absolutely. But these are all doable things. They're all And positive. Very positive. Very positive. They, they, they— it's a paradigm shift for our industry. It changes not only the business model, but it also changes inventory management. It changes warehousing. It changes— it can reduce, you know, carbon footprint of product if it's made locally. It can be much more sustainable in terms of, you know, environmentally friendly, not having waste. You know, if we really are listening to the consumer and making on demand what they want, And oh, by the way, full price. How interesting. There's a concept. More money as well. Selling things at full price. Yeah, exactly. Less stuff to move around and selling it at full price.

Yeah.

Well, I mean, I watch retailers struggle moving inventory around from store to store based on what the till had as sales last week. Like, why are people even moving products store to store? We've been past— we're well into, you know, endless aisle and omnichannel and fulfillment from everywhere. Yeah. So why on earth would you pick up an entire season of something and move it somewhere else because it's selling better in that area? No, you just have the tools to sell it directly. Yeah. Well, hey, I know, I know, it's funny, isn't it? I know, but all habits die hard. It's difficult to think It's difficult to think different. It's difficult to think.

It's difficult to think sometimes.

Let's face it, most people don't. Yes. So if we get past that, it's difficult to think. It's difficult to think differently. Yeah, absolutely. Yeah.

Well, Craig, thank you very much for coming and joining us again. It's just enlightening stuff. So yeah, thank you. Oh, thank you.

Great to be here. I look forward to coming back.