The music industry finally has some reason to celebrate, thanks to artificial intelligence.
The Recording Industry Association of America (RIAA) recently announced that music revenues in 2016 grew 11.4 percent to $7.7 billion — the highest year-over-year growth rate since 1998. Although the industry is only half the size it was in 1999, double-digit growth is encouraging after years of either declines or flat results. Why the growth? According to the RIAA, the answer is simple: streaming is taking hold. And streaming services — especially Spotify — are lapping the field with AI.
As the RIAA noted, the biggest contributor to growth was a doubling of revenues from paid streaming services such as Apple Music, Spotify, and Pandora. In fact, for the first time ever, streaming music platforms generated the majority of the U.S. music industry’s revenues.
Younger streaming platforms such as Tidal are still too new to contribute significantly to the $3.9 billion that streaming services generated in 2016. Rather, the established streaming leaders, especially Spotify, are hitting their strides by offering better products fueled by AI.
Pandora and the Power of Personalization
Streaming services such as Pandora and Spotify have always created customers by personalizing their vast inventories of music. If you stream music, you already know how well Pandora and Spotify create engagement by offering you customized listening choices based on your personal tastes. I still remember how exciting it was when I first started using Pandora years ago and created my own Pandora radio stations based on names of artists or songs that appealed to me. If I wanted to create a station based on my love of Massive Attack, I could do so. If I wanted to create a station of music inspired by the Cure song “All Cats Are Grey,” I could do so. And Pandora refined my stations even further when I gave a thumbs up or thumbs down to songs that Pandora suggested to me based on my listening tastes.
Amazon sure knows how to keep everyone off balance. While retailers are figuring out how to use automated chatbots to service customers, Amazon is pushing a new personal styling feature that relies on the human touch.
The Launch of Outfit Compare
Days ago, Amazon began to make available to Prime members a service called Outfit Compare. With Outfit Compare, Amazon Prime members receive advice from Amazon on their style choices. The service works like this:
Amazon Prime customers may post two photos of themselves wearing different outfits of interest to them.
An Amazon stylist then gives feedback on which outfit looks better on the customer. The stylist provides feedback based on factors ranging from what’s trending to what looks best on you. The stylist uses a style scale in voting for the preferred option, ranging from “Definitely Pick This One!” to “It was a close call.”
And according to Amazon, your stylist is a real person, not a bot. Amazon says that Outfit Compare “is powered by a team of fashion specialists” whose backgrounds include retail, editorial, and styling.
Throughout the past week, a number of journalists have reported on the launch and have tested it. So far the coverage of Outfit Compare includes a fair bit of incredulous head scratching, such as:
How Amazon corralled a team of fashionistas to help people in a stylistic funk is a weird question. It’s unclear whether there’s any sort of automation at play — because it’s hard to imagine a team of stylists eagerly waiting just to dress you. — Sam Blum, Thrillist.
It’s not immediately clear how this feature will boost Amazon’s bottom line in the near-term. — Sarah Perez, TechCrunch.
Amazon has added what might be the strangest feature for Prime members yet . . . Outfit Compare is a fun tool to mess around with, but it’s unclear what exactly Amazon gets out of it. — Chaim Gartenberg, The Verge.
Those comments remind me of the bemused reactions when Amazon rolled out the Dash button in 2015. The Dash button seemed so out of the blue that many thought its launch was an April Fool’s joke. But two years later, Amazon says the list of brands signing up for the Dash program include Campbell’s Soup, Cascade, Clif Bar, Mentos, and Quilted Northern, to name but a few. All told, more than 200 Dash buttons exist.
In other words, Amazon is not just messing around.
Amazon’s Fashion Aspirations
So then what does Amazon get out of rating customers’ style habits? I think Amazon is using Outfit Compare to figure out how to create a more effective balance between human judgment and personalization through technology. Why? To become a true fashion brand.
Amazon clearly wants to become a fashion brand. The company operates Amazon Fashion, which bills itself as “a one-stop destination for head-to-toe style.” Its moves to build up its fashion business also include, among other things, consulting with fashionistas such as Julie Gilhart (formerly the fashion director for Barneys New York) and hiring Caroline Palmer, formerly Vogue.com editor, as director of Editorial, Video, and Social Media for Amazon Fashion.
I suspect Amazon is watching Stitch Fix to learn about style curation. Stitch Fix is an online style recommendation service. The site uses artificial intelligence to analyze and recommend personal style options to its customers based on a variety of data, including information reported by customers. Personal stylists analyze the AI-based recommendations and then assemble a customized package of clothing, which is delivered to the customer. Customers can always return what they don’t want — in fact, returns help Stitch Fix’s AI engine get smarter.
When a client fills out a profile and is ready to be styled, we are able to see what the algorithm is suggesting based on the data collected from her profile — everything from sizing to location, geography, body type, fabric preferences, colors and pattern preferences. It helps to not have to worry about the broad strokes of what a client does not want. Then we can make creative decisions about what will fit her body and her lifestyle.
By contrast, without AI, a stylist might need weeks of working with a client to come up with the best recommendations.
So far, the combination of AI and human judgment has made Stitch Fix so successful that more than 80 percent of its clients come back for a another delivery within 90 days, and one third spend more than half their clothing wallet share on Stitch Fix. Stitch Fix has achieved a valuation of $300 million since its founding in 2011 and is reportedly considering an IPO.
Amazon is already known for using AI to power its product recommendations. But the launch of Outfit Compare suggests that to become a fashion brand, Amazon realizes it needs to apply more than algorithms. It looks to me that Amazon is learning from Stitch Fix to apply the human touch. Amazon is a fast learner. And what Amazon wants, Amazon usually gets.
