Who's Driving and How Much?

This article is brought to you by Arity. 

As fuel prices spiked earlier this year, consumers were stopping less often for gas, groceries and other goods.

Mobility data and analytics company Arity identified those patterns through mobility-based analysis that can provide additional context alongside traditional datasets.

“Arity found that gas prices rose by an aggregate average of roughly 33% between early March and late April. During that same period, consumers did not necessarily switch retailers; instead, they made fewer trips overall,” said Anthony Johnson, solutions engineer at Arity.

According to the company’s data, on average, for every 1% bump in gas prices, stops per user fell 0.74% for gas, 0.67% for restaurants, 0.66% for grocery stores and 0.57% for retail (excluding gas).

Using billions of anonymized driving events, Arity generates intelligence about where and when people travel and how those behaviors change, said Johnson. “Sales reports tell you what was purchased. Loyalty data tells you who made a purchase. Mobility intelligence can help provide context about the travel patterns preceding those transactions.”

Arity’s Road Traffic Analytics help bring that view into focus by showing how traffic, visits, dwell time and competitive patterns are changing around specific locations.

A March analysis revealed that as fuel prices increased, miles driven by people from lower-income communities fell sooner than they did for people from higher-income communities, who largely maintained their normal driving patterns.

“In a separate analysis, we observed that consumers altered travel patterns most noticeably during periods of sharp price movement, suggesting that behavioral responses may be driven by the perception of economic pressure as much as the absolute cost of fuel,” said Johnson.

He added that the extent to which consumers change their behavior in reaction to changing gas price varies based on geography, income level and local market conditions. Arity data can help highlight these distinctions. For example, trip frequency often declines before spending data shows any changes—an early signal that retailers can use to adjust their plans. 

“We encourage businesses to focus less on whether gas prices are at a specific threshold and more on how mobility is changing in their markets in near real time,” said Johnson. “Mobility data can help retailers assess how demand may be changing in their markets, even before those changes show up in sales.”

This is the first in the two-part article series brought to you by Arity. To learn more about how retailers can use mobility data to stay ahead of changing demand, look for part two tomorrow.

Consumer Insights