Adobe announced the latest online inflation data for the month of November on Thursday, with online prices hitting a record high at a 3.5 percent year-over-year (YoY) increase, while prices were down 2 percent month-over-month (MoM) due to holiday discounts.
This was the highest YoY increase since Adobe first began tracking the digital economy in 2014 and it marks the 18th consecutive month of YoY online inflation.
Apparel was a standout category with prices up 17.3 percent YoY and down just 0.4 percent MoM, reaching a record high of inflation.
Since 2014, only three months–August 2016, January 2020 and February 2020–saw apparel prices rise online by 9 percent or more YoY. For the past eight consecutive months, online prices for the category have risen by more than 9 percent YoY every month.
The Adobe Digital Price Index (DPI) provides a comprehensive view into how much consumers are paying for goods online, covering more than 100 million products in the U.S. and is modeled after the Consumer Price Index (CPI) issued by the U.S. Bureau of Labor Statistics.
“Ongoing supply chain constraints and durable consumer demand have underpinned the record high inflation in e-commerce, with apparel seeing high volumes of out-of-stock messages online compared to other categories,” said Patrick Brown, vice president of growth marketing and insights at Adobe. “With offline prices surging in the Consumer Price Index, however, it is still cheaper to shop online for categories such as toys, computers and sporting goods.”
In November, 11 of the 18 categories tracked by the Adobe Digital Price Index saw YoY price increases. Apparel prices rose faster than any other category, while price drops were observed in seven categories–electronics, personal care products, office supplies, jewelry, books, toys and computers.
Furniture and bedding prices increased 2.91 percent YoY, but were down 1.15 percent MoM.
Powered by Adobe Analytics, the DPI analyzes 1 trillion visits to retail sites and over 100 million SKUs in 18 product categories. Adobe uses a combination of Adobe Sensei, Adobe’s AI and machine learning framework and manual effort to segment the products into the categories defined by the CPI manual.