There is some easing in the rate of online price growth.
Online prices rose for the 24th straight month in May, but displayed a promising trend.
Online prices increased 2%year-over-year (YoY) in May—down from 2.9% YoY in April and the record 3.6% YoY increase in March—while decreasing 0.7% month-over-month (MoM), according to the latest Adobe Digital Price Index (DPI).
While these results mark two full years of inflation online YoY, May is the second month where online price increases have slowed. The majority of categories tracked by the DPI (10 out of 18) saw MoM price decreases in May.
In May, consumers spent $78.8 billion online, which represents 7.1% YoY growth and over $1 billion more in spending than the month prior, when consumers spent $77.8 billion online (4.5% YoY growth), and below the $83.1 billion (7% YoY growth) that was spent in March. In 2022 so far, consumers have spent a total of $377.6 billion online, growing 8.9% YoY.
Price trends vary Price performance during the month varied by product category. In electronics and apparel, major categories that made up 33% of e-commerce spend in 2021, prices have continued to draw down. Electronics prices were down 6.5% YoY and 1.4% MoM, a greater YoY decrease than April (down 5.2% YoY), and a record YoY low for the category over the last 24 months.
Meanwhile, prices for apparel increased 9% YoY but dropped 1.5% MoM, down from the 12.3% YoY increase in April. Toys are down 6.5% YoY and 1.3% MoM, a record low for the category over the last 24 months. Prices have not eased for groceries, which climbed 11.7% YoY and 1.3% MoM, a record YoY high for the category.
This is the first month where Adobe has tracked prices for groceries as rising the most of any category, overtaking apparel. Groceries remains the only category to move in lockstep with the CPI on a long-term basis, with online prices rising now for 28 consecutive months.
Overall, during May, 12 of the 18 categories tracked by the DPI saw YoY price increases, with groceries rising the most. Price drops were observed in six categories: electronics, jewelry, books, toys, computers and sporting goods.
Eight of the 18 categories in the DPI saw price increases MoM. Price drops were observed across 10 categories including electronics, personal care products, jewelry, books, toys, home/garden, appliances, computers, sporting goods and apparel.
“Despite the modest increase in consumer spending online, an uncertain economic climate and rising costs in core areas like groceries are putting a hamper on overall demand,” said Patrick Brown, VP of growth marketing and insights, Adobe. “Slower consumer spending on discretionary items has driven slower, single digit e-commerce growth since March, and this pullback mirrors the easing in online inflation.”
The DPI provides the most comprehensive view into how much consumers pay for goods online, as e-commerce expands to new categories and as brands focus on making the digital economy personal. Powered by Adobe Analytics, it analyzes one trillion visits to retail sites and over 100 million SKUs across 18 product categories: electronics, apparel, appliances, books, toys, computers, groceries, furniture/bedding, tools/home improvement, home/garden, pet products, jewelry, medical equipment/supplies, sporting goods, personal care products, flowers/related gifts, non-prescription drug and office supplies.
Adobe DPI provides a comprehensive view into how much consumers pay for goods online. Powered by Adobe Analytics, it analyzes one trillion visits to retail sites and over 100 million SKUs across 18 product categories: electronics, apparel, appliances, books, toys, computers, groceries, furniture/bedding, tools/home improvement, home/garden, pet products, jewelry, medical equipment/supplies, sporting goods, personal care products, flowers/related gifts, non-prescription drugs and office supplies.
The DPI is modeled after the Consumer Price Index (CPI), published by the U.S. Bureau of Labor Statistics, and uses the Fisher Price Index to track online prices. The Fisher Price Index uses quantities of matched products purchased in the current period (month) and a previous period (previous month) to calculate the price changes by category. Adobe’s analysis is weighted by the real quantities of the products purchased in the two adjacent months.