A question worth USD 10T: What percentage of US Retail sales will shift online?

We think online penetration should remain elevated vs. pre-pandemic levels and expect further disruption going forward. ÃÛ¶¹ÊÓƵ built an interactive eCommerce penetration model based on 10 years of proprietary survey data from ÃÛ¶¹ÊÓƵ Evidence Lab. Based on this analysis, we forecast online share reaching 26% of US Retail sales by 2027, up from 23% in 2023. This roughly reflects 75 bps of annual digital share gains. Our forecast implies eCommerce sales should rise at a 6.9% 4-yr.Compound annual growth rate (CAGR), not far from our previous Q-Series estimate of 6.0%. While we expect online adoption to increase over time, the latest survey iteration shows consumers continue to value in-person shopping. We therefore anticipate a more modest digital adoption rate going forward vs. the gains seen in 2020-21.

We expect more store closures and an increasing focus on omni-channel:

We see the shift to eCommerce as structural. Penetration rates are likely to increase modestly over time as young people, who buy goods online more often, gradually become a bigger part of the demographic mix. We forecast brick and mortar sales expanding less than 2.5% annually, assuming US retail sales rise at a ~3.5% CAGR. We think this relatively low sales growth rate will result in more physical store closures since slow sales growth likely pressures margins. However, we believe brick and mortarÌýstores should remain relevant because survey results indicate many consumers still like to try products in stores before buying and enjoy the in-store experience.

ÃÛ¶¹ÊÓƵ Evidence Lab market research and data science analysis power our views:

ÃÛ¶¹ÊÓƵ Evidence Lab surveyed 2.5K US adults age 18+ regarding online and offline shopping habits by category. The survey has been administered annually since 2014, with questions kept consistent in order to provide y/y comparisons. ÃÛ¶¹ÊÓƵ Evidence Lab then leveraged data science techniques to build detailed penetration models for each retail category. We derive our eCommerce sales growth forecasts based on these models and channel trends within each category. We acknowledge the math for how we formulate eCommerce penetration partially relies on the most recent survey data. As such, behaviors may differ from a steady state or normalized behavior, potentially influencing the long run forecast from the data science team.