There’s no doubt that online shopping is a wave that is roiling the retail industry — and our culture, for that matter.
But it’s wave that’s not sweeping up all shoppers in quite the same way.
According to new data, the rise of online shopping across the United States is rather uneven, with more affluent states marching more quickly toward a lifestyle in which buying happens on a screen instead of at the mall.
Adobe, whose software runs under many retail websites, analyzes data on billions of website visits to create its Digital Price Index, a real-time snapshot of online consumer spending. Analysts there studied digital shopping patterns over the one-year period ended February 2017. At a state level, they measuring the growth in total e-commerce spending, as well as the online spending per person.
Looking first at the year-over-year growth rates in total spending, you see the choppiness. For example, coastal states such as New Hampshire, Oregon, Rhode Island, New Jersey and California have some of the strongest surges in online shopping. But big pickups are not limited those geographies, with Texas and Mississippi also posting robust e-commerce growth.
Maryland saw an 8 percent increase in spending, while Virginia saw a 7 percent increase.
Meanwhile, online spending actually retreated or held steady in a handful states, including Idaho and South Dakota.
But things get especially interesting is when you look at per-person online spending in relationship to the state’s affluence.The second chart below plots per-person online spending against the most recent Census Bureau figures for state-level median income.
As you can see, there is a noticeable correlation that suggests affluent shoppers are adapting to online shopping especially quickly. Luiz Maykot, a data science analyst at Adobe Digital Insights, said a number of factors could be shaping the difference, including that low-income shoppers are less likely to have credit cards, which are table stakes to participating in online shopping.
There are other interesting lessons embedded in this chart, too. Look, for example, at Alaska and Hawaii, which are affluent states that don’t fit the pattern of having strong per-person online spending. Maykot said this likely reflects the fact that shipping to those states can be pricey and relatively slow — factors that make online shopping less attractive.
The data also offers hints that perhaps our varied adoption of online shopping is not just about relative affluence, but other lifestyle factors.
Take, for example, how much the District of Columbia stands out in the data set. It’s a city, and its growth and spending look much different than in any of the 50 states.
The District’s growth in per-person online spending was 38 percent during the one-year period. The next-largest growth rate, recorded in New Hampshire, was significantly lower: 20 percent. Plus consumers in the District spent a whopping $3,353 per person online. That is dramatically higher than the per-person rate in any state. (New Jersey was the highest, with $1,736 per person.)
So perhaps the gap is telling us that urbanites, in general, have migrated to online shopping much faster than their counterparts in less densely populated areas.
Maykot said that while he can’t say for sure because Adobe doesn’t yet perform city-level analyses, this is a “credible hypothesis” for why D.C. is an outlier.
After all, there are unique pain points to brick-and-mortar shopping in cities: Checkout lines at high-traffic stores can be excruciatingly long. Nabbing an on-street parking spot can feel like a miracle. Many city residents don’t own a car, and it can be hard to lug purchases on public transit or on foot. All these factors may be pushing them to adopt online shopping more quickly than those in smaller towns.
Taken together, this data helps provide valuable context for how we should think about the business strategies of some of the biggest names in retail. For example, Amazon’s same-day delivery service is largely concentrated in affluent cities. Sure, that’s in part because the economics are better when customers are clustered close together. But this information also suggests that Amazon is first trying to make this a habit among the kinds of shoppers who are already the most dependent on e-commerce. (Jeffrey P. Bezos, the chief executive of Amazon, owns The Washington Post.)
Similarly, people sometimes ask me how Walmart, for example, could possibly be sustaining over 4,000 U.S. stores in the digital era. This data helps explain that: You may see a tower of Amazon boxes in your big-city condo building each evening, but that isn’t a good proxy for how people are shopping in, say, rural Tennessee. Even if you’re personally doing less of it these days, there is still enormous appetite for shopping in brick-and-mortar stores.
And yet Adobe’s research suggests there are ways to attract different kinds of shoppers — including low-income ones — to the digital channel. Take, for example, what Adobe observed during the holiday season when it came to purchasing TVs. Researchers looked at how many televisions were bought online during November and December in each state, and then looked at what share of those purchases were made during Black Friday week — the time period when discounts were running highest. States with lower median incomes tended to see a larger share of TVs bought during Black Friday week, suggesting value pricing was important in getting these consumers to fill their digital shopping carts.
“If retailers want to bring more low-income people into the online space, that week is very important for you,” Maykot said.