Adobe’s Digital Price Index: Tracking the Fast-Moving Online Fashion Economy
For the first time, Adobe’s Digital Price Index (DPI) took a deep dive into online apparel sales for the month of May, closely following the online fashion world. With a goal to examine how the speed of fashion impacts sales and where consumers can find dropping prices, we implemented a new methodology to track long-term trends in spite of a market that features quick turnover and frequent discounts. And we think the data may help shed light on some of the biggest shifts we’re seeing across retail.
The Fast Pace of Fashion Impacts Online Shoppers, Especially Women
One of the biggest findings is just how much the fast pace of fashion impacts apparel purchases. Revenue from sales of new apparel products, those that have been on the market for a year or less, accounts for 80.5 percent of spending in the category – the largest share of spending among all categories that the DPI tracks. Nearly one third, 30.8 percent, of all spending on women’s clothes goes towards products that are month old or less; for men’s clothes it’s 18.0 percent.
Our apparel numbers also show how intense fashion velocity is for women. Of the more than 7,000 new apparel products that appear online every day, nearly half are aimed at women (3,150), while only 1,750 are geared toward men, and the rest fall into the children’s, babies’, and footwear categories. And women respond—more than half of all online spending for women’s apparel (56 percent), goes toward products that have just hit the market in the previous three months, compared with 38.8 percent of spending on the newest men’s items.
“The gender differences we see in the DPI are really intriguing,” said Sid Kulkarni, data science analyst for the DPI. “Women’s apparel sees much more turnover in response to a quicker fashion cycle than other categories of clothing. Moreover, women’s clothes purchased online span wide range of items of clothing than men’s or children’s apparel and women’s clothes are sold in the same ratio at the high and low end.”
Among the other interesting gender differences: women’s purchases vary more by season, with a spike in dresses in the spring and sweaters in the fall, while men tend to buy shirts all year long, and snag underwear online frequently.
Deflation Happens at the High and Low Ends
In May, the DPI tracked -4.3 percent deflation year-over-year (YoY) in apparel. Over nearly the same period, the CPI, which measures prices in retail stores, saw relatively flat apparel inflation. “We think the difference reflects online shoppers’ dedication to seeking out deep discounts, and the fact that consumers are more likely to buy off-season clothes online,” explains Sid.
Online deflation wasn’t equal across the board. For apparel at the highest prices (the top 25 percent), we tracked -5.5 percent deflation YoY, while the cheapest 25 percent of online apparel showed -7.5 percent deflation. The middle-of-the-road items showed only minimal deflation YoY.
A New Method to Track Complex Ups and Downs, and What’s Ahead
Calculating inflation for apparel is notoriously tricky, whether economists are looking at in-store or online sales. Consider how quickly products rotate to keep pace with the seasons and the velocity of fashion, and the steep discounts retailers offer to keep the cycle moving. This means that if you follow the same product’s pricing over time, as standard economic models do for things like electronics and groceries, you get a skewed picture—the sweater that went on the market in September will be much cheaper by March, but this doesn’t reflect the overall state of apparel pricing, or the YoY prices of sweaters. So, to better estimate prices in this sector, we developed a new method.
Our new approach groups products by subcategories, such as men’s sport coats or women’s swimwear, and further divides the categories by price bins—so, for example, we examine separate groups of similarly priced sport coats: $0 to $100, $100 to $200, $200 to $300 and $300 and above. The process yields 684 narrowly defined categories which we can roll up to the six main categories that the CPI also tracks: men’s, women’s, boys’, girls’, baby and footwear.
The Method Behind the Numbers
The data behind the Adobe DPI is sourced through Adobe Experience Cloud. It represents 80 percent of all online transactions from the top 100 U.S. retailers, including aggregated, anonymous data from 15 billion website visits and 2.2 million products sold online. Unlike the Consumer Price Index (CPI), the DPI can track real-time prices and quantities of items sold. The data also enable unprecedented views of the U.S. economy, including state-by-state analysis, and new methods, like the price-bin approach to tracking apparel.