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How big data makes shopping online suck less

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Transcription details:
Date:
06-Nov-2013
Input sound file:
1008.MP3

Transcription results:
Session Name: How Data is Remaking E-Commerce
Chris Albrecht
Michelle Lam

[music]
Chris Albrecht
00:04
[chuckles] Suddenly I’m Chris Martin. Up next we have: How Data is Remaking E-Commerce. That’s going to be a talk by Michelle Lam. She’s the Co-Founder and CEO of True&Co. Please welcome Michelle out to the stage.

[applause]

[music]
Michelle Lam
00:23
Hello. Good morning. This is going to be a little different than the other talks we’ve had today. Can we go back a slide? Great. I’m the CEO and Co-Founder of True&Co. As you can see, we sell bras online. We’ve taken a fundamentally different approach to the bra business, to the lingerie business. We’ve taken a data-centric, as well as a design-centric approach to the entire experience. For those of you in the room who don’t wear bras, you may actually think that this is what bra shopping is like. This is the fantasy that Victoria’s Secret has put forth. They’re about 40% of a 14 billion dollar market. They’ve told us that it’s like shopping for glamorous evening wear. You look like this woman. You look like a supermodel. You’ve got breasts that look like that and the entire experience in the store is full of glamour. When in reality, this is what bra shopping is really like. This is Linda, the bra lady. She’s fitting a woman in a fitting room. It’s incredibly intrusive, to the point where bras are no longer actually an enjoyable shopping experience. They’re actually a chore – an errand – that women force themselves to do once every several years. This is what New York Times quoted me as saying, “Bra is the worst shopping experience on Earth.” It’s a random experience, an inconsistent experience, often the bras don’t fit, it’s trial and error, it’s frustrating, and not only that, the products are ugly.
Michelle Lam
01:59
Here’s what we did. We combined design and data for a better customer experience. If any of you have been to the True&Co. website, the first thing you do, you take a two minute online fit quiz. Our algorithm collects a bunch of data from you. Then what we do is we create a personal shop of styles and sizes just for you. Then we take that customer experience offline and we send you a home try-on box. You pay for what you keep, it’s a $45 refundable deposit. All throughout this entire process we are collecting data that helps benefit the customer, helps us serve her better, but at the same time, helps us innovate in terms of product design, not only online but in terms of the actual bras themselves.
Michelle Lam
02:46
First thing I want to talk about – and Kevin mentioned this in his Instagram talk – talk about things that benefit the customer and a way to collect data that is incredibly friendly. When you compare the in store bra shopping experience, you have an experience that’s very intrusive, very uncomfortable and we’ve replaced it with an online quiz where the language is like a Cosmo quiz that you would take – if any of you guys remember that magazine in high school. The tone is very friendly. We have a ton of illustrations so that women don’t feel like they’re being compared to a Victoria’s Secret model. At the same time, we are asking incredibly personal questions. We’re asking what is the shape of your breast? We’re asking whether your breasts sit shallow or full in your cup. There’s a number of different pieces of data that we’re collecting from these customers, and we are actually classifying them into one of 6,000 different body types without them even realizing it. It doesn’t stop there. What we do is our algorithm actually takes the inputs from the quiz and we combine it with all the inventory meta-data that we’ve collected about the products in our shop. We collect over 30 different pieces of meta-data about each single bra, and we classify them into 6,000 different body types, and create a personal shop with the styles and sizes that are just for you. Even men can sympathize this, when you go into a shop you often see small, medium, large or 24, 26 waist band size. In our particular case, we will never show you anything that we think is not a potential match for you. This is all part of giving back to the customer. As they’re in their personal shop, we actually keep asking them questions. Very personal questions. What is your birthday? Do you have a significant other? What is their name? We are tracking all sorts of explicit preferences they’re expressing to us, as well as the different things that they’re clicking on the website and putting into their home try-on box.
Michelle Lam
04:47
An intimate shopping experience. We think it’s one of the most intimate shopping experiences on the web today. Then we make the experience even better. The purpose of the home try-on box for us is to measure our success. Can we actually fit women with just a quiz, no fitting rooms, no measuring tape, no photos. Actually to date, we’ve successfully fit 8 in 10 women just through the quiz alone. For harder to fit cases, we actually use a video fit consultation, – which is something new that we’re trying out – as well as fit consultations over the phone. Every time you shop, women are providing us. They provided us with nearly half a million data points on the bras they like and the bras they don’t. We’re not just asking them, “Why did you return this item?” We’re actually asking them, “Was the band too tight? Was the band too loose? Was the cup too small? Did you not like the color?” Women are also writing us free text novels about their bras and we’re collecting all this data. Every time they visit their shop, their fit feedback is being reflected in the shop for a whole new selection of bras. New arrivals, bras in different sizes that they may like the color of but didn’t fit them the first time. We’re creating an ongoing dialogue with the customer, while collecting a whole amount of data without any friction on their part.
Michelle Lam
06:10
What are we doing with all this data? As of October 22 – which was about 15 – 16 days ago – we launched data driven lingerie. What we did is we took the data points we’ve been collecting through our quiz, the personal shop, the home try-on process. For the first time ever for an apparel company, we fed those data points into a product design and manufacturing process. We’re not just talking about sales data, what sold well, what didn’t, we’re not talking about colors, what colors people said they liked, what they didn’t. We actually have a perfect loop of body type, implicit/explicit preferences, measured feedback on what worked for them and what didn’t. It’s a perfect circle. We’ve taken that data to figure out what are the sweet spots for each body type in terms of a bra architecture that would fit them. We have then actually fed those sweet spots that type of data into a mass production manufacturing process to design and architect bras that would deal with the issues for the women who have issues. But at the same time, for the woman who doesn’t have any issues, we’re just making beautiful product. This is something that we’ve worked very hard to do since the beginning of the company. Our entire data collection, personal shop, home try-on process has been architected from the get-go in order to get us the data that we need. One difficulty is if you are collecting data and you don’t know exactly what it’s for when you start, when you look at the data afterwards, it’s not going to knock you on the shoulder and say, Hey, this is the amazing inside and this is the bra I want you to design. You have to have a hypothesis and a judgment call in terms of what you’re looking for, ask the right questions to substantiate it, and that’s exactly what we’ve done through our website and through our customer experience.
Michelle Lam
08:05
What we like to say is 200,000 women designed these bras, or 200,000 women contributed to the making of this collection. We call this our body of work. We think it’s very important. We think there are implications in many other areas of product design, not just bras. I happened to choose bras because I think it was a fascinating problem. A bra has 20 different components in it. Bras are engineered, not manufactured. They’re actually engineered to defy gravity. Everything from the fabric to the littlest details and the usability of the bra itself, all of these are nuances in a design in a production process that we’ve tried to innovate on. These are the bras that we’re selling here. Made in China because, unfortunately, mass production of this type of bra is no longer available in the United States. That’s actually something else that we’re working on. We’re actually being able to look at very specific and nuanced data about each of these 6,000 different body types, focusing on the ones that we think are the big spikes in the data that we see. Then cooperating with our partners overseas to be able to do a bunch of fit testing, as well as a bunch of design innovation to press forward in this space.
Michelle Lam
09:29
Here again, data is helping us making smarter decisions. It also tells us what sizes we should produce. If you look at a 60 foot wall inside of a department store, they’re producing every size, every color even though the bra is not correct for that size. We actually know which sizes work for which body types, so we’re a lot smarter in terms of inventory and we save on waste as well. As I mentioned before, careful engineering. Every single component – each of those 20 different components of the bras – we look at the half a million data points that we have, we look at the fit expert data that we’ve collected, and we are able to make good decisions on that as well. Then finally, all of this is not possible if you don’t have the right world-class manufacturing partners to make it happen. Consistency of fit between physical products. We live in a virtual realm where we can deliver pretty much a consistent experience from a single point of distribution. Every single customer is going to see pretty much the same home page unless you decide to show them a different image, you do have central control over that. We have found that feeding all of those insights into a physical product development process where you literally have 100 women sitting in a room at sewing machines, translating your spec into the product that you eventually want to produce – this is very specific to the apparel industry – the variation between those individual workers can actually throw off your entire design piece. Being able to actually translate some of your data insights into action also requires great partnership with people in the know, and with people who are top tier and have the ability to deliver a consistent experience for you as a manufacturing partner. That’s all I have today. True&Co., we’ve come a long way. When we launched, we’d actually only been around for a little over a year. Already, the pain point that we’ve been able to solve for women has been significant. A lot of women have said it’s about time. This actually makes sense. You’ve handed back the power to me so that I understand for the first time ever what sort of bra works for me versus what doesn’t. Just the way I shop in every other apparel category, it’s no longer a mystery. We’ve been able to solve that for them and to give them the measure of intelligence that makes them enjoy their shopping experience. However, at the same time, it’s a win-win situation because we’re also able to collect all of these data points to continue pushing forward innovating – and what I said before, it’s one of the most intimate shopping experiences on the web today. That’s what we want to do, create a beautiful shopping experience. Then also at the same time, create beautiful products that truly solve her pain point literally as she’s walking around every day. Thank you very much.

[applause]

[music]
Chris Albrecht
12:24
That concludes the first half of the morning session here. You can go and have a break. Enjoy the sponsor area. Get to know the sponsors. Let them know you appreciate them help bringing on the show. Get to know each other. Maybe take some selfies, post them on Instagram I don’t know. Visit the GigaOM research booth, find out all the cool stuff they do over there. The general session will resume at 11:30. Thank you everybody.

[music]

One Response to “How big data makes shopping online suck less”

  1. Just a really good example of how to approach smart data capture and clever data analysis with the end goal in mind – improving the shopping experience. There seems to me to be still too many companies out there that take the reverse approach. They start with the data and see what can be unearthed from it. They should, like True & Co., start with the objective they want to achieve and understand specifically what data they need to achieve that objective.