Updated: Mar 9
Dominic Chew, founder of Hatch Idea Lab, joins The Future of Retail Asia Podcast and shares about using design innovation and thinking to bring back desirability into the physical marketplaces. With over 20 years of experience in branding and marketing in CFLD International, Frasers Property, and City Development Limited, he brings across the importance of the customer, and how malls should tailor to their preferences using strategies such as retargeting and preference management.
Episode 6: “Making Malls Desirable Again With Consumer Data” with Dominic Chew
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IMRAN: Welcome back to The Future of Retail Asia, I’m Imran.
JUN: And I’m Jun. We are happy to have Dominic Chew with us here today in the studio. Welcome Dom!
IMRAN: Welcome Dom!
DOM: Thank you, thank you.
IMRAN: Dominic Chew has had over 20 years of brand, strategy and design innovation experience. He has spent a decade in multinational brand agencies and another decade with property developers. His recent appointments include Chief Marketing Officer for CFLD International, SVP and Head of Marketing and Communications for Frasers Property, and VP for Brand and Strategic Marketing for City Developments Limited. He is currently embarking on a new approach to design innovation training and providing design innovation consultancy by founding and setting up Hatch Idea Lab, a boutique agency designed for impact creation.
JUN: Yes, definitely. I think design innovation is about solving complex problems. How do we apply this in the retail industry?
DOM: I am glad you asked about design innovation. In the framework for design innovation, there are three aspects: It's about building desirability, the second will be about feasibility of the product or the services that we have to offer, and the last would be business viability. I would like to talk a bit more about building desirability. Because it enables us to take information, and information Aimazing actually compiles. And the question is, what do we do with this information to actually build desirability. So even if we look at it from a segment perspective, I would like to challenge retailers today to relook at their definition, their segment, even their own customers. To maybe look at these sacred cows and ask ourselves, should some of these sacred cows be killed. For example, I get a lot of input that the luxury segment is very different, for example, from, let’s say, people who buy handphones, the mobile segment. Are we then saying that affluent people don’t use handphones? Does that mean that the iPhones that they use, the same model has a different function? No. It is the same person using the same product and the same feature, and thus, often, we tend to segment these kinds of customer base artificially. And then we are unable to execute something that is really viable from that. Because we have these preconceived ideas that the affluent will only eat at high end, but why can’t an affluent eat a at Ya Kun. Don’t you think that an affluent would want a traditional Singapore breakfast once in a while, besides international spreads. I guess design innovation actually goes back to the core, which is if we say that if we put the customer in the center, the question is with all the data that is coming to me, how do I build preference for the customer? I guess that is what the value add of design innovation would help retailers to develop these brands.
IMRAN: Very nice.
JUN: Interesting. Just now you mentioned that it is interesting that, seeing a mall as a brand, and we have a chat with you before. Like you always mentioned about making a brand desirable. With the popularity of e-commerce and us now living in the new norm, how can we make malls more desirable?
DOM: The first thing that I would look at is customer journeys. So if you are able to track, Aimazing is able to track customers from one point to another, to record purchases, the question is then what do we do with this information as a mall operator. In terms of design thinking, a lot of mall operators tend to do what other malls are doing. But in design innovation, using let’s say a simple tool of alternate worlds, besides thinking about what the retail industry will do, why don’t we think about, for example you mentioned e-commerce. What would Amazon do if Amazon staff were to run this mall? Chances are they would probably with your data, people who ate at this restaurant also considered eating at this restaurant. Then when you actually push information like that on to a customer’s journey. You would find that giving the insights, just using a simple tool called alternate worlds. You are able to actually put a different approach and here’s where the greatest challenge would be: To understand what is best case studies from another industry, and to look at it from an applicable possibility and feasibility of putting it into a mall. It makes a lot of sense, because it is not rocket science, the information is still the same. The question is what you do with that information.
IMRAN: What I love is a few points you mentioned earlier, one is that brand desirability is not just about having a nice design, it is about actually understanding the customer and using that data to then be relevant. I think the thing about implementing these strategies is understanding what is the data that we collect, how do we clean it, how is it relevant, and how do we use it. In fact when we talk to people in the industry, it is not that they don’t want to do these things, what we also find is that there is a challenge in how do we collect it, how do we use it, and being in the industry for more than a decade. Could you share what do you think are the gaps in the kind of data we collect, or maybe the gaps in how it is used.
DOM: The one thing that I feel is a very practical gap, is this thing called departments in the retail mall. Which means, let’s say I was dealing with Aimazing, I would be in the IT department. But the customer service probably is under the MarComms and Customer Service department. But all of it has data on the customer. The frustration of a customer would be recorded on customer service, and needs to be combined with this customer’s journey. And when you understand the preference, in order to do for example if you want to do service recovery. It is not going to be, here’s a tarbucks voucher. You want to say, Mr So and So, we are so sorry, but we understand that you usually like at 10 o'clock. You like your latte skinny one sugar, and we have that prepared for you at Starbucks right now, and we are really sorry. If you just drop by and give your name, they have already prepared that for you. Now how would you feel? The issue right now is the compartmentalisation is that IT is one department itself, doing the excellent awesome stuff with Aimazing, but customer service, we are going to do our own thing. Service recovery has nothing to do with the data you have. I guess what I am trying to say is that malls can function and kill these things called departments. The mecca that I would have is that we have one single knowledge management system. Everything from the input of the customer journey, to service delivery, or failed service delivery, to even recovery, so on and so forth. Start to build this, not about loyalty management, but start to build a preference management, so that you can actually deliver desirability because you cannot deliver desirability when you don’t know the customer’s preference.
IMRAN: So unifying that data approach and then the approach of the actual humans in the team to deal with the customer right?
JUN: This aligns back to what you mentioned, the customer is the center of the shopping malls. You are a big supporter of marketing to personal customer preference. Just now you gave a lot of examples like starbucks vouchers, you need to know the customers. Do you have any examples of creating a great customer experience by understanding the customer’s preferences?
DOM: Sure, I would use me as an example, because I am a customer. It’s very challenging when malls tend to like this whole concept of being different. Every mall claims that they are different, but the challenge that they have is that retailers actually want the uniformity. Correct? If you went to an LV store, or if you went to a breadtalk store, don’t you want uniformity in terms of service delivery. So you can create your own identity. Yet, the malls who have all the similar brands, claim differentiation. So at the end of the day, how do you deliver that desirability and it really boils down to one thing, which is personalisation. The service delivery, the last mile, how you are serviced. For example, I am wearing CYC shirts and there used to be several CYC stores around. I love their tradition, I love their cutting, I love their Egyptian cotton. There is this one person called Ryce that has been designing my shirts for the past twenty years. And they have all been the same format, CYC could have done that, but I can tell you why I keep going back to Ryce. Because he is so much into his craft that he was saying, I think this kind of button, I saw something like that in Jalan Sultan, let me go and find the buttons in Jalan Sultan for you. Now that is going to be the difference, isn’t it. I will still buy from CYC, but CYC, through Ryce, knows my preference. If you look at this preference management, it is not something that is new. In fact, when I was a little kid, I was six years old and I had this realisation that at 6 years old, I saw preference management at work. And this was at the hawker center char kway teow store uncle, who knows when you walk in is, ai hiam mai hum. And your’s would be mai hiam, ka zuay hum. Just by looking at your face, without identifying you or your name. Just by looking at your face, the person knows and can customise your order to your preference. While these are early days of what I notice of preference management, the challenge is that that person, everything is in that person’s head, it is not transferable. So in today’s technology, given that Aimazing is able to track customer journeys, you may even have facial recognition or check in codes that you can track the whole entire customer’s journey. Why can’t the same technologies be pumped into, for example, service delivery of the front line staff. Where the front line folks are able then to address customers by name and deliver preference services. I think that is kind of the last mile, isn’t it, where departments don’t talk because they feel that functions are separated. But if you actually collate data altogether, and develop one insight because it is the same customer you are dealing with. The same customer that went through your AI data points and journey is the same customer is at your customer service right now. Correct? You can be two different departments, but it is the same customer. So if you say that the customer is at the center of it all, then shouldn’t data be one collection point to identify preferences.
IMRAN: I think that is a very incredible insight actually. You have all these people in the malls. Everyone from your customer service to your retail assistants to even the security people, even the people who are dealing with the social media and the marketing and the tenant management. You would have such a huge wealth of information. And I think what you said is true, that actually there is a humongous knowledge base that just hasn’t been tapped yet. We haven’t figured out how to put this data together, how do we humanise this and how do we unify this, so that everyone can see that thing. I think one thing that I was quite interested or intrigued about is the individual customer experience, and we have talked about this before, about how do we do this at scale? Ideally, we actually have a thousand, or ten thousand customer experiences based on their preferences happening at the same time right in the mall. That is kind of our wishlist, from Aimazing side, we do see, or we envision that this could actually become the new Great Singapore Sale. Hey, could we delight customers at scale with technology, with data, and then could we have the new Black Friday, Cyber Monday, 10/10, 9/9 which was just yesterday, 11/11 events, live in the mall. We know that, hey these are the stuff you like, these are the transactions you have made, these are the brands you love. And we have all these curated and lined up for 11/11, you buy this today, have this extra voucher. Or if everyone in the mall purchases hit 10 million today, everyone in the mall gets a $10 voucher. What do you think about something like this, using data, using automation to then create completely new forms of brand and shopping events at malls.
DOM: I think the current global pandemic calls for it. The challenge for most mall operators today is that they function as a landlord. I have been with three landlords in the decade, I function that way as well. That I am the landlord, and they are the retailers. It is not that we are in the same shopping mall, delivering the same service together. So if you look at the whole idea of desirability, it is to understand not just the preferences, but the question is with the data that we have, how do we generate desirability for this person to come back. I can tell you that the current situation in malls today is very much adhering to Covid-19 rules.
DOM: So even if you are successful in drawing customers back. I can tell you that they don’t know how to repeat it. Because they don’t know what was successful and what was not. They are offering the same thing and it is still back to the same offerings. I will just give you a good example even during the Covid situation where we know that Covid is still rampant in Singapore. For example, if you had data on this customer that the person actually had a shopping list of groceries at a supermarket, and you know that this groceries would probably deplete in two or three weeks. Prompting the customer who may be in your loyalty base and ask, hey would you like to come back again if you wanted to repeat your order, why don’t we pack everything and you just pick it up. We will ensure that the fish is fresh, otherwise if you check and if it is not fresh enough, we will replace it for you on the spot. So desirability here is not just the high, tall order of personalisation of shirts, but it could also be necessities. I think it starts with that kind of desirability.
IMRAN: The mundane.
DOM: Exactly. You know that for example, the Milo that I buy is not going to be the one in the packet because of the terrible paper straws that fall apart. It is going to be cans, for example. And you know, you already have this data, the question is what are you and the tenant doing about it to attract people back again. Once you have this mundane, it goes on. If you knew that the person, for example, missed her pedicure, manicure, and the person actually works there. For example, if it is raining outside. Can’t the system just prompt the person that it is raining outside and Grab’s going to be difficult to pick up right now, it is going to be expensive, you are going to be caught in a jam. Why don’t you spend half an hour and finish off your pedicure, we will give you a 20% off if you come in now. This is what I mean by preferences, haircuts. I go there every three weeks, in the second week, wouldn’t a prompt be nice. I get this stickiness back to the mall, and not always is about the purpose of visits and high, tall orders. Sometimes it is to do the mundane stuff. If you can do ordinary things extraordinarily, that is where the beautiful part of building desirability kicks in.
IMRAN: I couldn’t agree more.
JUN: Very, very interesting. I really like the example of if I know this customer is going to my shopping mall to have a haircut. Normally people would have a haircut every month, and I know my customer’s journey after haircut, they would go to the department store. Why don’t I do marketing, vouchers everything together. After that I know that you are going to the department store and now outside it is heavy raining, why not I give you a massage voucher, 20% off. You can keep the customer staying inside the mall.
DOM: So desirability that we talked about. We talked about desirability on two levels. It is not just about the product that is desirable, but the timing. Is it desirable for you to be outside, heavy rain, caught in a jam, or is it more desirable for you in the mall, having a pedicure,manicure or enjoying a massage that you missed. Correct? A lot of people think that this preference or desirability has to do with a lot of tall order stuff, but sometimes it is as simple as remarketing, the difference here of making it desirable is the timing.
IMRAN: Or the situation or context.
DOM: Exactly, exactly.
JUN: Very interesting. Can’t agree more. If we only can go more in depth. Sadly, we don’t have more time. So then, what would be your advice for both tenants and landlords? If you have a mall manager in front of you, what would be your advice for them? And the opposite is like, if you have a retailer, what would be your advice for the retailer?
DOM: My advice to mall management today is to continue to build desirability. You collect a lot of data, from Aimazing, from customer service. You collect it from even traffic counters and so on and so forth. So the question is what are you doing with it? If you use design thinking, could you challenge yourself and let’s not just take frameworks that every loyalty management system pushes to you, let’s take frameworks from other industries, like the example I gave was Amazon about preference management. As well as recommendations. People like your persona that have bought this, also bought this as well. This will actually expand the amount of time the customer spends in the mall. And of course, with the increased time, we are looking at increased expenditure. So building desirability is important and I feel that when you build desirability, the rest of the camp itself, and just focus on that. When we say we focus on the customer, it has to benefit the customer. The customer has to feel the difference.
To retailers, my advice would be never sell something you wouldn’t buy yourself. It is about that passion of giving service and selling products that you yourself would buy and very often retailers and shop owners don’t actually buy from their own shops. Even the staff don’t buy from their own shops. They don’t provide service that they themselves would appreciate. I guess what I am looking at is also conviction. If you actually identify that these are the gaps, if I use design thinking, innovation framework, the question to ask is under what conditions would I actually want to buy from my own shop. What should I change to make sure that even my staff would find my own shop product and experiences appealing. And it starts from there. And if you are able to convince your own staff and shop owners to buy what they sell, then I think the rest will come and will follow suit.
IMRAN: So we have a last question, and the question is do you believe that retail will continue to be king and why?
DOM: Wow. I believe that there are two types of kingship. Let’s talk about kings. I believe as a king that kind of exists outside of the customer’s lives, they are the ones that go, boom, this is what I have, correct? Now you take it or you leave it. That is one type of king, that means they probably sell something that everybody else doesn't have. There is another type of king, and this king exists within the customer life. This king knows what is desirable, when it is desirable, and how it is desirable for the customer. Now in this instance, the customer is the one conferring kingship status to the retailer, to the mall, because why? Without my king, my desires, my needs, my wants will not be fulfilled. So the question then is, with the retail mix, with the experiences that you have. How do you build preference and create desirability so that you can be the king that is conferred by the customer, remember, you are not the self-declared king. And I think this would be the Mecca for a lot of the operators as well as retailers, that if you wanted to be king, you have to earn it. And it has to be conferred to you, by the market.
JUN: Sadly, that is all the time we have for today. Thank you Dom for coming down and sharing with us your insights. To our listeners, do reach out to us if you have any questions or comments, we would love to hear from you. You can find us on LinkedIn, Instagram, Facebook. Our podcast is on all major streaming platforms and YouTube too. Stay tuned for the next episode. See you!
IMRAN: See you!
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