Orbital Insight Correctly Predicts Retail Sales Miss, Hit Rate Grows to 78%
On January 12th, Orbital Insight’s US Retail Traffic Index predicted a miss of Bloomberg consensus estimates for Retail Sales ex-Auto in December (+0.2% MoM). On Friday, January 15th, the census reported a -0.1% MoM decrease in Retail Sales ex-Auto, in line with Orbital Insight’s forecast of a miss of analyst estimates.
Since 2013, Orbital Insight has correctly predicted a beat or miss of Bloomberg consensus estimates 78% of the time.
Orbital Insight uses deep learning algorithms to accurately identify cars from satellite images at 55,000+ parking lots of major retail chains across the U.S. Its proprietary methods turn these raw car traffic counts into continuous time series; the ”normalized” time series correlate with same-store-sales trends at the chain level.
Orbital Insight’s U.S. Retail Traffic Index is a best estimate for the aggregate consumer traffic at 40 of the retail chains tracked by Orbital Insight. Our collection of retail chains include many of the U.S.’s largest, and span in business type across 9 NAICS segments. We capture NAICS-segment level trends by aggregating revenue-weighted car traffic data from individual retail chains belonging to each segment. Individual NAICS segments are combined into a top-line index — the Orbital Insight U.S. Retail Traffic Index — using census sales numbers lagged by two months as weights. Note that Orbital currently does not include estimates for NAICS segments we do not cover.