London, UK — A lack of real-time visibility and operational blind spots within physical retail are creating preventable friction points in shoppers’ bricks-and-mortar buying journeys, according to the latest data from SAI, the leading active intelligence solution for stores.
Original research of over 1,000 shoppers by SAI revealed that more than half (55%) believe retailers suffer from operational blind spots and don’t have full visibility of their stores. Meanwhile, a similar number (56%) think retailers aren’t actively monitoring bricks-and-mortar operations, with poor visibility limiting their ability to identify and resolve issues as they happen.
While three quarters (75%) of consumers now expect stores to be able to adapt in real time, six in ten (60%) say retailers are unaware of what’s happening in their bricks-and-mortar locations, and a further 55% think stores are too slow to respond, leaving preventable friction points unaddressed.
On average, SAI’s poll found that shoppers are left waiting an average of 4 minutes and 17 seconds for staff assistance in-store – valuable time where customer experience can become compromised. Indeed, over a quarter (27%) say poor staff availability and slow assistance have caused them to abandon a purchase, rising to 33% of Gen X, while unresponsiveness by staff also prompted a third (34%) to question their loyalty to a retailer.
“Delays in responding to real-time customer and operational needs don’t just compromise customer experience, but risk abandoned sales and lost loyalty among shoppers. Yet many operational delays and in-store friction arise from problems that are visible long before retailers act to address them, making them preventable,” said Som Sinha, Co-Founder & CEO of SAI.
“Retailers can’t fix what they can’t see,” Som continued. “And that means stores need to operationalise intelligence, allowing them to predict, prepare and respond in real time, ensuring customers aren’t left paying the price for operational blind spots.”
Using its patented Visual Language Model (VLM), the SAI One platform blends computer vision with GenAI to turn traditionally ‘passive’ store surveillance systems into an active, operational platform for real-time store intelligence. Proprietary AI innovation within the platform analyses live data from video feeds using advanced VLM to build a comprehensive, contextual picture of how stores actually operate, surfacing meaningful operational signals, insight cues and timely staff alerts that drive estate-wide performance.
