Stitch Fix recently filed for its initial public offering, built on the back of its monthly subscription business. Stitch Fix is an e-commerce company headed by founder and CEO Katrina Lake and funded by top tier firms including Benchmark Capital, Lightspeed Venture Partners and Baseline Ventures. The company has 2.2 million “active customers” and just under $1B in annual revenue.
In this 3-min read, we're taking a look at Stitch Fix from the perspective of its growth levers, including:
- The role of data science and personalization in user onboarding and customer retention
- How their monetization and business model aligns with their core market dynamics, their product characteristics, and the channels they use to grow
- The user psychology behind their subscription box upsells
Key Growth Lessons
1. Personalization is the foundation of onboarding, retention, and monetization.
Far from taking a “frictionless” approach to user onboarding and online shopping, Stitch Fix instead presents new users with a lengthy survey designed to increase investment, trust, and identity with the product.
The more personalized the product experience, the more likely a user is to stay subscribed, and to convert upwards to purchases of individual pieces.
2. The Stitch Fix subscription model relies on personalization, but also user psychology and “reverse friction,” in order to maximize monetization on subscription users.
The company's subscription service functions as independently profitable leadgen for its higher margin e-commerce business. Once users have onboarded to the subscription service (high friction to onboard, low friction to retain), it's easier to keep (buy) monthly items than to send them back — reversing the typical direction of purchase friction in ecommerce.
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"We're in the business of personalization"
Subscription e-commerce is a crowded space, with multiple companies competing in the fashion and clothing vertical alone. But, to a customer, what differentiates a subscription clothing box like Stitch Fix (or its dozen competitors), from Amazon Fashion, Rent the Runway, or Nordstrom?
For Stitch Fix, the answer is personalization. The company recently revealed that it brought in $730M in revenue in 2016 and $977M in 2017, some of that from the $20 subscription "styling fee" and some of that from retail revenue it makes on items that customers keep.
Personalization requires data on both the customer and inventory ends of the spectrum, but while most retailers boast huge volumes of data on inventory -- items' fabrication, country of origin, color, etc -- that data doesn't end up driving customers' purchase decisions.
Instead, those decisions ultimately hinge upon qualitative and quantitative data points specific to an individual customer -- information that's typically hard for fashion retailers to get.
At Stitch Fix, the data science team is 80 people led by Netflix's former VP of data science and engineering. It makes sense, then, that data-driven personalization plays a role in three key areas of growth for their business: onboarding, retention, and monetization.
To get started with Stitch Fix, users complete a 10 to 15 minute survey that kicks off with personal questions about height, weight, and clothing size, and then moves into more subjective areas like personal style and other preferences.
The survey is a good example of friction in an onboarding flow that actually increases investment, trust, and identity with the product:
- Investment -- users have to spend non-negligible time completing the survey.
- Trust -- users trust in a better outcome because they've given detailed information.
- Identity -- users feel increased affinity with the product because it's now their Stitch Fix, and reflects their identity.
The more personalized and accurate a shipment is, the more reason users have to stay subscribed.
While it's unlikely that users would stay subscribed for the styling alone -- those efforts have to result in good matches in order to be useful -- data-driven personalization can help human stylists make better recommendations that users will be more likely to keep.
In Stitch Fix's case, retention is tied closely to monetization.
Stitch Fix monetizes through a blend of a $20 flat rate monthly "styling fee," plus any revenue it makes from the clothing that subscribers decide to keep.
The more personalized and accurate those selections, the more likely a subscriber is to keep at least one item. In that case, instead of $20 in monthly subscription revenue, the company makes $50 and up in retail revenue, minus a deduction of the styling fee that gets credited toward the purchase.
Stitch Fix's lowest price bracket for women's clothing starts at $50 but runs all the way up to $200+, and the company holds its own inventory in 5 distribution warehouses across the United States.
With average retail markups on women's clothing range from 100% to as high as 350% for premium denim, it's in the company's best interest to run a strong retail business and sell lots of clothes. Thus, monetization, subscriber retention, and acquisition are closely aligned.
Image courtesy of Brian Balfour.
At $997M in annual revenue ($730M for 2016), Stitch Fix monetizes well, and it's not just because of the markups on clothing. For comparables, FabFitFun brought in $40M in revenue in 2016, and Rent the Runway increased its revenue to $100M after introducing subscription tiers a year ago.
Better matches, and “reverse friction,” encourage conversions
Why does Stitch Fix monetize so well and move so much product? A lot of it is due to their comprehensive data science effort that combines qualitative, user-submitted information, with quantitative data on inventory and the warehouses that store and sort it.
The qualitative data collection effort starts with the onboarding survey, but also gets refreshed every month as users review the shipments they receive. In a best-case scenario, a customer's Stitch Fix subscription improves over time, which serves retention and much as it drives monetization.
There's also a user psychology component to Stitch Fix's monetization model. Because Stitch Fix customers must return what they don't want (the default is to be charged for the rest), users must either confront the immediate "pain" of boxing up and shipping off unwanted items that are already in their homes, or simply keep the items and defer that "pain" to the credit card statement they receive at the end of their billing cycle some weeks away.
With the average return rate for fashion e-commerce ranging from 25% to 50%, that's still a great business for Stitch Fix, which sends 5 items in that $50 to $200+ range. If a customer keeps just 1 or 2 items per month, it adds up to a significant monthly recurring ARPU that also means the user found value in the service and will be less likely to churn in subsequent months.
For more on Stitch Fix's data efforts, we highly encourage you to check out their microsite showcasing the role of data science at the company. It's a lot of fun and covers a surprising level of detail.
In a time when many other e-commerce companies (whether subscription or flash-sale) are focused around "cheapest" and/or "fastest" to compete with traditional retailers, Stitch Fix is selling full-priced clothes plus affordable, at-scale personalization based on data that's both direct and voluntary -- a value proposition that could help it to gain ground on Amazon, traditional retailers, and the apparel market as a whole.
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