SAN FRANCISCO---At Rent the Runway, behind the shimmery gowns and shiny baubles up for temporary grabs, is a flourishing treasure trove of data disrupting one of the last spots of the home due for digital shakeup.
There are a number of businesses, from the startup level to established fashion houses, brainstorming how to use modern (especially mobile) technologies to tap into new revenue streams. This runs the gamut from new consignment schemes from the likes of Poshmark and Tradesy to the production of high-end connected jewelry, such as one collaboration between Intel and Opening Ceremony.
But Rent the Runway, a self-described "fashion company with a technology soul," has the ambition (or perhaps the audacity) to completely revolutionize how the average person shops for clothes, according to the company's chief analytics officer Vijay Subramanian.
I sat down with Subramanian earlier this week to hear his insights about just how Rent the Runway plans to accomplish these plans -- many of which come back to one simple but big buzzword in tech these days: data.
Here are a few highlights from our discussion, edited and condensed for clarity.
ZDNet: What is your average day like at Rent the Runway?
Subramanian: Today, I do two main things. First, I run the core data function. The first step is tracking the data, munching it. Then there is all the analysis to get insights, doing all the ninja work to understand what is going on. We also build data science apps for the company. That team reports to me directly.
What's also interesting, being a technologist at heart, data product and engineering they build products together. We have about four to five of those teams right now. I oversee two of them as the matrix lead, even though they report up through engineering and product.
Product, fundamentally, is very data-driven. The two best examples are logistics systems, which actually allow us to rent clothing successfully. The site on the surface is all about consuming designer products. That's all true. But in order to make that experience successful, under the hood there is a data technology platform that enables consumers to want to rent, makes it easy to rent, and makes rental economics work.
That platform, one key part is logistics. If you're going to an event on Friday night, you wear the dress and put it back in the mail on Monday. For us, to take that inventory back and process it to turn around for the next Friday is a real task. Only then will rental economics work. We build from the ground up technology to take the bookings and allocate for reservations, triaging urgent orders, less urgent orders, etc.
ZDNet: You joined Rent the Runway from the data science team at Oracle Retail (via the 2005 acquisition of ProfitLogic). How have you applied those analytics products and methods to the online retail business?
Subramanian: Elements of it. My PhD was in Operations Research. It's all about the customer journey. There's a supply chain element to it, so the bookings and allocations systems are really built from the ground up. The problem set is still different.
The second example is pricing. We built pricing software for Oracle. Here, conceptually the data ideas are similar but a very different problem. We're trying to figure out the right rental process, and we're the first ones doing this. We're disrupting and creating a new path to price a rental. I know what it is at retail. I know what I paid at wholesale. But in order to make our economics work and acceptable to customers, we've been doing a lot of experiments to figure out the correct rental range for different events.
For example, if you were going to President Obama's Inauguration Ball in 2012 -- which many customers did as DC had a huge spike in sales -- people had more propensity to pay for a formal, marquee event compared to buying with a rental for $100 versus $1,000. If you're going out for a night with your friends, you probably don't want to pay a lot.
ZDNet: How does Rent the Runway plan to use big data and analytics to stay ahead of the competition in a market increasingly crowded by rental and other "sharing economy" online-based businesses?
Subramanian: Our biggest asset for retention is our community: real women wearing the dresses. That is the single distinguishing feature that keeps people motivated and want to rent.
eBay was all about trust. Look at Yelp or TripAdvisor, both of which are based on trust and community.
One of the biggest fears women have about renting is worrying if it will fit. We have customer reviews and photos. Reviewers are posting pictures, and we're getting all that data and building features that allow you to enter your attributes and find women who look like you, where did the gown land, etc. Women are very detailed about what worked, what didn't work, what was tight, what was loose. It's almost amazing how much data they're willing to share. They're willing to pay it forward.
My job is to take all that data, parse through it, and use it to recommend what to rent and surface data for someone browsing, to make them feel confident.
Supply-side, we've spent four years investing in logistics. We have an army of seamstresses, dry cleaners, and technology to distribute materials in the right way.
We started off with weekend events, going after the special occasion market, from proms to weddings to holiday parties. Our single largest event is New Year's Eve. We're starting to take that portion of your closet that makes no sense to own.
We're also making a foray into daywear, renting amazing costume jewelry and handbags. We launched a subscription program six months ago for daywear. It's still in beta while figuring out what customers want and expect around products and price points. We believe half of the closet is going to be in rotation in some form.
ZDNet: What are some of the key metrics that play into Rent the Runway for recommendations? What are some of the back-end systems used to power those features?
Subramanian: I think of metrics as supply-side and demand-side. Supply is all about inventory and logistics. Demand is about consumers and how they interact with the site.
On any given weekend, how many units of inventory are out with customers? It's no different from a hotel in how many rooms are booked on a given night. Inventory utilization is a key metric for us. The faster we can turn inventory through different rental cycles, the more money we make. Operationally, it's about the cost of fulfilling the order. Those are the big metrics on the back-end.
Demand-side is about customer acquisition and retention throughout the year. Those are top line metrics. If you drill down further, you think about conversion and how fast customers find a product. There's a whole funnel we think about, from browsing to cart to purchase.
We're laser-focused on customer acquisition at this point. When you're the first company to create this use case - a commercial way to consume designer inventory - our goal is to penetrate the market as much as possible. Not many people were doing it because it's very hard to build.
Our thesis is that we believe the closet needs to be disrupted. We've disrupted every part of our lifestyles, from TV to how we eat. The closet, untouched. Our closets look like how Grandma's looked 60 years ago. But there's a certain portion you just don't need to own. You can own your staples, like jeans or a little black dress. But anything you need to spice up your day or want to be trendy, you don't need to own.
Our thesis is that we want to capture that market. But you have to teach [customers] how to do it. You don't wake up thinking, "I'm going to rent a dress today."
Twenty years ago, people didn't think the way about renting movies like they do now. Eventually, people will have clothing subscriptions, and we want to be the number one player in the market.