Stores Fall Short on Tech Expectations

A recent survey of over 1,000 shoppers found that 35% of respondents believe physical stores are failing to meet real-time expectations, with many citing the inability to keep pace with AI or respond to data as quickly as online channels. The findings suggest a gap between in-store experiences and the speed consumers associate with AI and eCommerce.

Younger consumers were more likely to hold this view, with 51% of millennials and 48% of Gen Z respondents saying stores are falling behind. This perception is likely driven by the high standards set by digital shopping, which has conditioned consumers to expect rapid responses and seamless experiences.

Three-quarters of those surveyed said stores should be able to adapt in real time, particularly in areas such as queue management, stock allocation, and matching staff levels to pressure points on the shop floor. This expectation is not limited to minor issues, as 65% of respondents said they now expect in-store problems to be resolved as quickly as eCommerce services handle issues online.

The survey also highlighted dissatisfaction with how retailers use data in stores, with six in 10 respondents saying retailers still suffer from “blind spots” and are unaware of what is happening on the shop floor. A further 56% said retailers are not managing store operations effectively, while 55% said physical retail remains too slow to respond when problems arise.

More than half of respondents, 53%, said their in-store experience would improve if retailers made better use of data to guide operations across stores. Younger shoppers were particularly keen on this idea, with 64% of millennials saying store visits would improve if retailers used operational data more effectively. The polling also showed that 74% of respondents see proactive problem-solving in store as important to a positive shopping experience.

Som Sinha, co-founder and CEO of SAI, noted that “with stores becoming more connected, retailers have never had more opportunities to gain visibility across their estates. Yet too often those opportunities aren’t being translated into meaningful operational insight.” He emphasized the need for retailers to leverage data and AI to deliver responsive experiences that meet customer expectations.

In practice, this means that retailers need to find ways to turn data into actionable insights that can inform operational decisions in real time. By doing so, they can reduce operational drag, improve the shopping experience, and ultimately drive business success. This is particularly important for retailers who want to attract and retain younger shoppers, who are accustomed to fast and seamless digital interactions.

The survey’s findings come as retailers face pressure to link digital tools with day-to-day store management, rather than limiting them to customer-facing applications. Although chains have invested in store monitoring, computer vision, and connected systems, the survey suggests that many consumers do not yet see the results in faster service or smoother visits.

SAI’s system is designed to turn surveillance infrastructure into a source of live operational information for retailers managing multiple sites. By leveraging video feeds and AI models, retailers can gain visibility into what’s happening across every location and make data-driven decisions to improve operations. Som Sinha noted that by using this system, retailers can bring all stores up to the standard of their best-performing stores, reducing operational drag and delivering the responsive experiences customers increasingly expect.

They can achieve this by using data to inform operational decisions, thereby improving the shopping experience and driving business success.