In this episode, Madhav Sadhu, Vice President of Marketing Technologies and Data Engineering at Tailored Brands, talks about how he uses data to respond to clothing trends, Covid’s impact on the retail industry, Web3.0, and so much more.
In this episode, Madhav Sadhu, Vice President of Marketing Technologies and Data Engineering at Tailored Brands, talks about how he uses data to respond to clothing trends, Covid’s impact on the retail industry, Web3.0, and so much more.
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Steve Hamm: [00:00:00] Ma. It's, it's great to have you on the podcast today.
Madhav Sadhu: Thanks for having me.
Steve Hamm: Okay. Okay, great. Well, our podcast listeners are, are well aware of, of Tailored Brands two, two of their main brands, the Men's Warehouse and Joseph Fe Bank. But it would be great if you could give us the bigger picture about the company's businesses, its business model, and the competitive landscape.
Madhav Sadhu: Thank you. Uh, Men's Warehouse is a men's specialty clothing retailer. We specialize in men's clothing, such as. Wear pants, shirts, whatnot. And we also have a pretty big rental business If you ever want to shop for a prom or for your wedding, and if you happen to have a taxi to be rent out for yourself or your for your kid, or for your friend, or for your party, typically people look at Men's Warehouse.
So we are very well [00:01:00] known for our rental business, along with the retail business, which, which I just briefly talked.
Steve Hamm: Yeah. And it's, Is it the two retailers or are there additional brands?
Madhav Sadhu: We have two more brands. Um, we have mos, which
is
also called Less, uh, msp. It is based out of Canada. Uh, they, the business model is similar to Men's Warehouse and Joseph Bank, and we have another brand called K G FA Fashion Superstore. This, this is a brand based sort of, This brand specializes not only for men's fashion, but also for women's and kids fashion items as well.
Steve Hamm: Yeah. All right. So what are the major trends in retailing and fashion industries that your company faces, and how are you dealing with them?
Madhav Sadhu: So major trend that we are facing is, uh, people moving towards business casuals, and we started adapting to this merchandising, uh, trend five years back. [00:02:00] And that has been, Helped us to put back, uh, in, in the, in being the number one men specialty clothing. So we are pretty good. Our merchandising, uh, team is pretty good in understanding the trends that are happening in the industry and adapting, uh, very quickly to those trends and coming back on our feet.
Steve Hamm: Yeah. Yeah, so, So this, that trend. Toward business casuals. It's been a long time coming, but, uh, but your company stuck with, stuck with a more formal wear for a long time, but I guess there was a tipping point, it sounds like, that really sent, sent you this signal that we're gonna, we're gonna also add these other products.
Do I understand that correctly?
Madhav Sadhu: Absolutely. But, but once again, this was like five years back. That was the major friendship that happened within the industry, right? And we, we were prepared for that. We have data that we are collecting and we were preparing for it. So, um, we, we quickly adapted to that. The other trend that, that we are seeing in the fashion retailing industry [00:03:00] nowadays is people tend to like to get personalization, personalized recommendations, whether it is, uh, in store experience or e-com or, or email, right?
Uh, if we had shopped with us, uh, you would've, you, you would've known our brand very well. We, we are, we are top class when it comes to in store customer. However, when it, uh, when it, when we go to e-com or email, um, we, we, we are working on improving those channels to have the same personalized experience that you used to have.
Steve Hamm: Yeah. Yeah. And, uh, I wanna tell you a good story. I think you'll enjoy this. I have a personal fondness for Men's Warehouse, and that's because back in 1989, I worked for the San Jose Mercury News just down the, down the street for Men's Warehouse headquarters. And, uh, we had earthquake there and the Mercury News did a bunch of coverage.
We got the puli to prize. And I [00:04:00] bought my sports jacket for the prize ceremony at, uh, Men's Warehouse. It was a very nice sports jacket. So I just want to, I just want to, uh, give kudos to Men's Warehouse for a little piece of my history.
Madhav Sadhu: Okay. Thank you. Thank you so much, Steve. And we hear that all the time. We hear that from our US all the time.
Steve Hamm: Yeah. That's great. Now, let's talk about you for a minute. What's your role in the company and what's your agenda?
Madhav Sadhu: I play two different roles in the company. One is the head of data engineering. In this particular role, my main agenda is to democratize the data, get the data as quickly as we can from the source system, and keep it in the hands of analyst and business users so that we can make informations quickly.
And be ready, uh, with our next, it could be the marketing, um, marketing promotion, or it could be the new merchandising trend. So, um, my, my role primarily is to make sure the data is available in the right hands at the right time. My [00:05:00] second role is I also had the marketing technologies. And as part of this particular role, um, I'm responsible to make sure that we are having.
Pretty experience with our customers, whether it could be the personalized emails, it could be the personalized, uh, experience on the website, or it could be the email that we're sending out, or it could be the SMS channels and other channels that we're, that we're reaching our customers. My role is to make sure that we are selecting the right technologies, tools, and vendors to make this happen.
Steve Hamm: Okay. Very good. In your career, you've held technology jobs for IT consulting companies.
Then you came to the men's warehouse a decade ago. How have your experiences prepared you for the challenges and the opportunities that you face now?
Madhav Sadhu: Another excellent question is to you, uh, this, this actually, this helps me, um, go back to my memory, Lynn and, and, and think what I used to be as a consultant. Thanks. Thanks for that. Um, [00:06:00] so being a consultant, the primary advantage that you'll get is you get to see multiple domains, business domains. You get to see multiple technologies, deal with different people, deal with a different situation every day.
So that kind, that kind of prepare. To become a leader, uh, wherever you go and understand the problems that that particular client has and deliver those solutions that that will, uh, elevate those problems
Steve Hamm: Right,
Madhav Sadhu: coming from that mindset. When I initially joined Men's Warehouse, we quickly realized that the data is all over the place, and I.
Adopted some of the beautiful things that I learned as an IT consultant and implemented those practices, best practices and, and, uh, implemented the first interval data warehouse back in 12. And to give, to give an example on some of the practices I learned as a consultant, which really helped, helped us even today, is rather than utilizing IT tools [00:07:00] such as data stage or Informatica to move the data, we just adapted, uh, an ELT method.
Steve Hamm: Yeah. Okay.
Madhav Sadhu: People were not doing it back then, but I, I, I, I observed one of my, uh, client doing it as part of my consulting job, and I really like the way, and then I implemented it here. That really helped us in the last 10 years, uh, uh, to, to Democrat as quickly as, as much as we can, as well as move to Snowflake without much, um, without much time being spent on my.
Steve Hamm: Interesting. So you really modernized the data pipelines for the company.
Madhav Sadhu: Absolutely.
Steve Hamm: From all, all the different data types, bringing them in. And that's, and that's really cool how once you did that, you were really, ma it made you more ready for Snowflake. Very
Madhav Sadhu: correct, Correct. And, and that is from the technology side. If I may add,
Steve Hamm: Yes. Yeah.
Madhav Sadhu: the, the other thing that being in a prominent, the primary difference I observe, uh, between a. Consulting job as well as permanent employment [00:08:00] is in a consulting job. You don't get to get to know the entire broader spectrum of the business and as well as the depth of the
business.
Being in a permanent uh, company, you get an exposure to the Enter 360 degree view of the business as well as depth each and every portion of your business, which will help you to become a. Um, domain expert. Either it could be from your business domain or from technology, that that's what shapes you.
Steve Hamm: Yeah. You know, that's a very interesting point. You know, you, you've been at Men's Warehouse for a decade now. I run people into people in the industry who, you know, they've been a year and a half here, a year there, and a year and a half somewhere else, and I just don't know how they. . I mean, it just doesn't seem like they get the continuity, they get the, the, the breadth of context in their, wherever they're working.
So I just am amazed that people can do that. And I, and I really, I really, uh, respect the way you're doing it. Just getting in there, working different jobs, [00:09:00] developing your skills, getting more and more responsibilities. So that's, that's really good. Smart move. Um, now you mentioned Snowflake. We, we mentioned 'em a couple times.
When and why did Tailored Brands engage with Snowflake?
Madhav Sadhu: Yeah, we were using an TP platform, um, back in 20 20 16. We implemented that platform, um, in 2012 and it solve good for until 2017 or so, but at that point, we need to upgrade our MTP platform to the next version rather than upgrading to the to latest person. What we did is we just took a step back and.
What is our business? Uh, what, what is our business needs are in the next five years? Is the platform that I'm going to upgrade right now, is it going to take care of those business needs? Or I need something more flexible and scalable, Uh, which will, which is going to take care of my business needs for the next five years?
When we took a step back and looked into the market, [00:10:00] uh, we looked at Snowflake, and of course there are other, other platforms as well.
Steve Hamm: Sure. Sure.
Madhav Sadhu: But what caught our, our, um, attention with Snowflake was it's capability, it's scalability, um, it's re um, no database maintenance. There are so many things I can talk about it.
So all the problems that we had with our old MPP system has been solved with Snowflake. Uh, right at that moment. We know that this is going to be the. And we need to get onto this journey as quickly as we can so that we have concrete advantage on our on, on our, on other press.
Steve Hamm: Was was the old system, was that on premises?
Madhav Sadhu: It was on
Steve Hamm: Okay, so this was, this was the big shift of, of applications and data to the cloud. I, I think it was the great migration.
Madhav Sadhu: in fact.
Steve Hamm: Yeah.
Madhav Sadhu: Yeah. In fact, Snowflake was the first cloud migration that we have done in our company, followed by, There are a lot of other things that we are doing now, but it was our first cloud migration.[00:11:00]
Steve Hamm: Yeah. No, I think that makes a lot of sense. Um, so on Snowflake, what are the most important applications you've developed on the data cloud and what kind of benefits have you gained from them?
Madhav Sadhu: We, we are using snowflake. drive a lot of analytics and help business make informations. Some of them, some of the examples are like inventory planning, sales forecasting, churn, analytics, customer segmentation, supply chain visibility, just to name a few. And we are also building a lot of analytical models by consuming the data from Snowflake and building these models in Python.
Um, some of the more examples are like pricing, um, AB testing, uh, uh, churn prediction, so forth and so on. So we started Snowflake to be primarily used for reporting analytics. Now we are at a stage where we are [00:12:00] started building models using the data that is available in snow.
Steve Hamm: Mm-hmm. . And you do use it in conjunction with Python. We you build the model. Do you build the models within Snowflake and Python? Or, or, or still out outside of Snowflake?
Madhav Sadhu: Uh, we, we, we use JTA notebooks and, uh, build, uh, build models. Um, you, we connect to the snowflake, get the data from there, and build the models there, and then deploy.
Steve Hamm: Oh, okay. I gotcha. Yeah. Um, so, you know, one of the, the keys to your company is, you talked before about personalization, so how are you using data to kind of be more engaged with your customers?
Madhav Sadhu: Yeah, so we are in the journey of building this customer. Three 16.
Steve Hamm: Mm-hmm.
Madhav Sadhu: this. We started this journey. This. As part of this, what we are doing is we are collecting the customer data from different channels. It could be a point of, say, it could be a [00:13:00] recom, it could be our contact center or social media, whatnot.
So we are building this single view of customer and trying to understand the customer trends, their needs, what is the most, what are, what are the issues they have with, with our brands and trying to address. By either reaching out to them and taking care of, uh, their concerns or by giving them a, a coupon marketing coupon, which they're most likely to buy, or giving them some loyalty benefits, which will help them to come back to us.
Steve Hamm: Yeah, I would think your brands both have a lot of loyalty. A lot of people who come back, I mean both the rental thing, but also just Men's Warehouse and Joseph Bank. Uh, because people buy important, you know, traditionally they're buying ver, These are very important purchases, you know, an ex a. Is a sometimes expensive purchase that, that you really want to make the right choice with and you want the right quality, all that kind of [00:14:00] stuff.
So, um, I mean, I mean, you and you mentioned the loyalty program. Is there anything specific you're doing with data around the loyalty program that's that's making it stronger?
Madhav Sadhu: Yes, we, we have done multiple AB testing saying if we, if it, if we change our loyalty model, let's say right now we give find points. For $50 if you change it to two 50 points for five or visit. So there's a lot of testing that has been done and wherever we found success, we started implementing them. But we are also looking at, um, implementing a new project platform where, uh, not only we can do project points, but we also want to ex enhance the customer Experie.
Uh, by giving them some services, which we are not able to offer today.
Steve Hamm: Now what's next in your use of data analytics? [00:15:00] What, what do you see out in the next six months or a year or so?
Madhav Sadhu: What I strongly believe is we are in a pretty good shape, shape right now where we can, uh, start taking this data analytics to the next level. We are focusing very heavily on building, uh, models. Some of the models that we are, we are planning to build on a customer lifetime value prop to buy churn production.
Targeting promotion based on customer behavior. Once again, we are going to use the C3 60 data to make the information which promotions works well with that, with that person as well as we also doing a lot of stuff on supply chain, understanding the, the I churn, understanding the forecasting of our orders as well as placement analysis.
So Sky is the limit that we're planning to do with data analytics, but we are also planning. Create the models and make them real time, uh, expose them as real time models to selling [00:16:00] channels. We are doing some proof of concepts, um, and that is another cool thing that we are planning to.
Steve Hamm: Yeah. Yeah. Now, beyond your company in particular, when you look ahead over the next year or so, what major trends do you see emerging in data management and analytics?
Madhav Sadhu: I, I think Steve, I can, I can, um, confidently say that, uh, was still holding on to the on-premises data warehouses, I think they, they have enough confidence know where they will start moving to, uh, cloud if they have not yet. Right. So I, I see that majority of the companies, if they're not at, have not started the journey, they will be very quick in, in getting onto the wagon, um, in the next year.
So,
Steve Hamm: Yeah.
Madhav Sadhu: The other thing I see is, um, with, with this cloud warehouses being so popular, uh, with the scalability features, there's a lot of demand for real time capabilities. Gone are the days where [00:17:00] people will, will wait for one more, wait until the batch jobs are done, and then do analysis. There's a lot of need for real time capabilities.
That is something which is going to, uh, turn off very quickly in the next one year or
Steve Hamm: Okay. Gotcha, gotcha. The Covid crisis has been hard on formal clothing brands, brick and mortar retailers. It's been a part on a lot of people, a lot of businesses, but in particular, I think, formal clothing because of, you know, the work at home thing.
How has your company used data to help deal with these really incredible pressures?
Madhav Sadhu: Yeah. Yeah. So you are, you are taking us back to the memories which we don't wanna go back to,
Steve Hamm: Yeah, I
Madhav Sadhu: in 2020 beginning of pandemic, uh, just like any other retailer, just like any other, Uh, fashion company. We also had to go through, uh, very hard time.
Um, and the data played a major role in understanding our current financial, financial model, how, how quickly we can come back. So there's a lot of role that data played inbeing back in [00:18:00] business. Other, other thing that we, that where we used data heavily was, um, to start opening our stores as if you, if you recorrect your memory.
Not the entire country did not open on the day one. There were some pockets of countries which were getting opened. Right now we have stores all over the country, so we, we used data, uh, exposed by staffs team, which, which was provided by John Hopkins. And then we try to understand the areas where we can start opening the store.
So, Combine their past purchase history with the opening, um, regulation, regulation restrictions and the dates, and then started opening the stores within informs whether they're going to work or profitably or we are, uh, you know, there are a lot ofs that been done, uh, for store opening, uh, during this covid crisis.
Steve Hamm: Oh, that's interesting because I remember that very granular data available in star schema. So, you know, [00:19:00] different parts of the country had hot spots and you didn't wanna reopen a a, a store in one of those, but it 50 miles away might be, you know, ready to go. So this is the kind of thing that you analyzed.
Very interesting.
Madhav Sadhu: Absolutely. And the other other thing that we also did was, uh, that was, uh, it's part of Covid crisis One is the other one, supply chain problem. Right. We all know that in 2020 when we had a lot of supply problems, now we, we have used data exchange lead to, to understand the bottlenecks of supply chain and took some, uh, quick measures to make sure we don't have inventory problem at, at our.
We connected the data from different multiple data points. It could be from, uh, shipping companies, it could be from our vendors, it could be from our internal systems, it could be from a system called Project 44. Uh, we connected all this data dots and then realized how long it is going to take for our inventory to hit our stores from the vendors.[00:20:00]
And if needed, we flew the, flew that product in, or we, we, we found some other alternative method so that the product is available at our.
Steve Hamm: Yeah. Yeah. I'm gonna ask you to put on your visionary cap now, looking out five years or more, how do you see data analytics transforming business and even society?
Madhav Sadhu: Um, very good questions to you. I see there are two major things that are happening when it comes to technology, which, which are going to be groundbreaking in the next decade or so. One is Web 3.0. Web three oh is going to change the way. How business collects the data today about the customer rather than business owning the customer data and our customer owns their own data.
This is going to create interesting trends on how quickly businesses like us can up to getting the customer information and making some useful insights out that business. [00:21:00] He's also going to bring in EA driven services. It'll also make us do decentralized data architecture and edge computing. So it's very exciting that it's happening in this world.
Steve Hamm: you mentioned Web 3.0. You know, so many people are talking about Web 3.0, they're talking about the metaverse, you know, and we get bits and pieces of it, So could you define those two terms and also how do they overlap or what, what's the, how do you compare them?
Madhav Sadhu: Absolutely. Steve, let me, let me explain you a little bit about Web three, four first. We are in the generation of WebP Do Web has gone undergone three types of um, iterations. One is web one.org, where people like us don't have access to add anything to the website. We are just the consumers and the developers are the ones who build the website.
That trend was where until 2004. Then from 2004 onwards where two org came into [00:22:00] picture where the end users can't start. Communicating with their friends, families, whatnot, or create blocks, they can start communicating on web two. That's the era that we are in now. The future is Web 3.4. Web 3.4 incorporates concepts such as decentralization, blockchain technologies, token based economics, Metas and ft.
There are so many things that you can do with with Web three dot four. This is evolving at this moment. But this web three technology is made. Core concept is decentralization. And the decentralization not only talks about decentralizing the web, but it also talks about decentralizing the data. It talks about having the customer data being given to the customer rather than to be company,
Steve Hamm: Aha.
Madhav Sadhu: needs lot of ways [00:23:00] how, how, how businesses are.
Taking care of customer data, how they're interacting with the users is going to completely change. So, for example, Metaverse, if, since you also talked about Metaverse, let's talk about an example of Metaverse being a, being a fashion retailer. I can, I can think about wearing a, uh, going into metaverse and shopping for menswear prs, right?
It is, it's a virtual. And you have your own, you have your own a avatar. You go into the metas, you look at your author avatar, you pick, pick and choose whatever. Um, so you want, uh, and then buy from there and the items will be shipped to your store. The concept is going from B to C, where business to consumers, to business, to avatar B.
It's BTA scholar, b2. There's a lot of exciting things.
Steve Hamm: Yeah. Yeah. Now let me ask you this about, you know, when you have the, your avatar and the metaverse going to the men's warehouse or Joseph Fe bank store. [00:24:00] So this is a very specialized kind of a avatar because it actually has the measurements of you.
Madhav Sadhu: Correct
Steve Hamm: so that when, All right, so when you try something on your, your shape is actually, you know, it's, it's similar to your shape in, in reality.
And when the, the store gets the message about what you want, your order, they know exactly how to fit you.
Madhav Sadhu: exactly, exactly it. It is a concept, but this is going to become reality in the
Steve Hamm: Yeah. Well, you know, it's interesting. Sometimes I ask myself, Well, what do I really want to be in the metaverse? This is actually one of the applications that I say, Yeah, well that's, you can see that that would be really helpful and really easy and really convenient. So thank you so much for the, uh, the gift of an example of the metaverse that would be, that I could see, uh, could be really good.
Madhav Sadhu: Thank you. I'm.
Steve Hamm:We typically end the podcast on a lighter, more personal note. Now, I understand that your son is going to [00:25:00] the senior prom this year. Is this gonna bring a big change in clothing style for him?
Madhav Sadhu: ab Absolutely. Being a teenager, he wears hoodies, uh, he wears jeans, which has some holes in it. Uh, I, I will, I never get that concept. Or at first he just wears some, uh, shirts and, and goes out. Right? And this is very, I always want to see him nicely dress up. I get to see, see that whenever he performs orchestra.
But once again, orchestra has its own dressing code. And, uh, now going to prom, I, uh, being at being at Men's Warehouse, I go and help at the stores where I look at a kid who comes in just like my. Wearing a hoodie, wearing a shirt, and then they go, they go inside the dressing room, come back with a, with, with a nice tuxedo, with with, uh, you know, with shoes on.
He's a completely different kiddo together.
Steve Hamm: Yeah.
Madhav Sadhu: Whenever I see those kids and [00:26:00] I'm like, I wanna see my son one day like that. And I'm glad that that year is going to be this year because it's going to go to prom. And I get to see, get that experience
Steve Hamm: Okay. Yeah, that's gonna be a lot of fun for you, I'm sure. Yeah. Now you mentioned, you said sometimes you go to the stores just to kind of see, you know, you're the data guy in the background, but you actually do go into stores and kind of observe. Right.
Madhav Sadhu: We do, we do. So that is a culture that we have within our organization where all the leaders, whether it could be technology or business, we spend time with our, uh, with our stores or with our distribution centers so that we understand, uh, the business processes that are going in there, understand their pain points firsthand, and see what kind of solutions we can provide.
That is a, that is the best way how you can think about providing a solution for your business.
Steve Hamm: Yeah. That's very interesting. This has been a great conversation, uh, really enjoyed talking to you today, and I, I really like con I want to combine two things that you said. You talked about how essential [00:27:00] data is both in responding to Covid, but also in responding to this big change that's even beyond covid.
In attire, in business attire from more formal to more casual. So data's been absolutely essential in that. And, and, but at the same time, the executives of your co of your company go out into the stores and just use your eyeballs and, and see what you're seeing about the business process, about the customers and that kind of thing.
So I do actually think it's kind of refresh. To hear somebody talk about that combination of things, because sometimes it's like, Oh, it's all about data. Well, there are other things too. Right?
Madhav Sadhu: Absolutely Steve, and now you know why I'm in this computer for 10 years.
Steve Hamm: Yeah. Yeah. I can see why. Well, this has been a great conversation. Thank you so much.
Madhav Sadhu: Thank you Steve.