In retailing, as with most businesses, there are two ways to grow profitably. You can grow your customer base, or you can sell more product per customer at a premium. The best clothiers are able to do both. Count Stitch Fix (SFIX 3.93%) among that group, thanks to a heavy dollop of data science.
"Data science" for Stitch Fix really means "studying everything we know about how prospects and customers interact with our styles." Stitch Fix collects data to reduce the risk of returns, to improve its carrying inventory, to get more from each dollar invested in operations, and, ultimately, to delight customers so they'll keep coming back.
Here are four numbers that reveal how successful Stitch Fix has been so far, and what to look for next.
How Stitch Fix gets data from its Style Pass mobile game. Image source: Stitch Fix.
1. At least 2.25 million Style Shuffle users
Though it's not exactly "swipe right for yes," Stitch Fix's Style Shuffle mobile game is meant to act as a sort of "Tinder for fashion" by giving prospects and customers another way to tell the subscription box clothier what they like and what they don't. More than 75% of the company's 3 million-plus active clients use it, which amounts to at least 2.25 million Style Shuffle "players." Stitch Fix has collected over 1 billion additional data points as a result, feeding its data science machine and improving how the company serves customers.
2. Over 70% retention of Style Pass customers
Like its main rival, Amazon (AMZN 1.66%), Stitch Fix has a Prime-like service it calls Style Pass. Introduced a year ago, the $49 annual fee confers upon members unlimited styling -- nonmembers pay a $20 styling fee for every "fix" delivered, with that fee applied to the cost of items purchased. Through the third quarter of fiscal 2019, renewal rates for Style Pass exceeded 70% for both men's and women's lines.
The customer benefit here should be obvious. Pay once, get new items from Stitch Fix at least quarterly, and pay less per shipment if your "stylist" gets to know you well enough that you buy most or all of what's sent to you. (Customers who buy all items sent in a shipment get a 25% discount on their entire purchase.)
For Stitch Fix, a large base of Style Pass customers creates a predictable base upon which to grow the business. And it is growing, as the last two data points show.
3. Revenue per active client is up 7.7% in the latest quarter
Stitch Fix profits most when clients buy more per fix. They've done that for four quarters in a row now. In fiscal Q3, revenue per active client rose 7.7% annually to $467. In the quarterly letter from founder Katrina Lake, Chief Operating Officer Mike Smith, and Chief Financial Officer Paul Yee, the company attributed the gains to "continued strength and improving retention in our Women's category." Women's is Stitch Fix's signature category, so if more women are buying more, consistently, it bodes well for the long-term economics of the business.
4. At 44.7%, gross margin hits a four-year high
Nowhere is this growth trend more apparent than on the top line, where gross margin hit a four-year high of 44.7% over the trailing 12 months. Q3 provided a significant lift to that result, with 45.1% of revenue flowing through as gross profit, up 150 basis points from 43.6% in the third quarter of fiscal 2018. More efficient selling -- what Stitch Fix deemed "lower clearance activity" -- was largely responsible for the improvement. And why not? With more data about what clients want and then acting on that intel with a better mix, Stitch Fix was bound to improve its financial performance.
The Foolish bottom line
Call it data science at work. Stitch Fix now has over 100 data scientists on its payroll responsible for figuring out new ways to generate insights that lead to tighter relationships with clients who are willing to give feedback that results in progressively better targeting. (Roughly 85% of Stitch Fix shipments result in client feedback, the company says.)
And that's just the beginning. As long as Stitch Fix continues to be good at collecting and utilizing data for improving customer experiences, every apparel category and global territory is a potential new market worth serving.
