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  • Yvonne Xu

Uncovering Loss Prevention through AI: How retailers can address shrink challenges


Guest Article | Yvonne Xu - Customer Success Manager, Black.ai


Yvonne Xu is Customer Success Manager at Black.ai. Black.ai is a cutting edge research and development start up in the artificial intelligence space. We admire the work they are doing, building advanced systems that utilise computer vision and high performance data organisation and association to enable human behaviours to be searchable through software.


Black.ai has gone through accelerator programs such as MAP and StartMate, and we have worked closely with companies such as CSIRO, Waterfront Toronto, Microsoft, Volkswagen and Audi Research.

 

The battle continues for retailers in 2023 through increased economic uncertainty, a cost-of-living crisis, a recruitment upheaval, and supply chain challenges. Standing still is not an option for anyone operating in the sector. While there are no magical solutions, the ability to empower a retail business to navigate customers' ever changing behaviour, needs to contain some incredibly innovative thinking and tools. Much can be gained from investment in technology and digitisation that surfaces the data of what is happening on-the-ground and how that can be transformed into actionable insights.


Shrink isn’t shrinking anytime soon

Shrink, which is largely impacted by theft, is a widespread and expensive problem for the retail industry. Some of the world’s biggest retailers say that this has grown into a multi-billion-dollar problem. According to the NRF’s 2022 “Retail Security Survey,” the average retail shrink rate in 2021 was 1.4%, representing $94.5 billion in losses.

Some retailers have taken a fixed approach of physically “locking down” product in-store and putting it behind plexiglass cabinets creating a staggered customer experience which can impact conversion rates significantly. Other retailers are exploring solutions that harness AI technology to prevent and tackle theft which maintains the seamless experience, however these too have additional factors such as consumer privacy.


Over the last few years, retailer’s such as Home Depot, Lowe’s, Best Buy, Walgreens and CVS have made extensive investments into solutions, yet the actual data is largely qualitative and cannot be fact checked. The enormity of the problem is not truly understood and those $94.5 billion in losses might be misrepresented as the shrink difference accounts for items that were shoplifted but also includes inventory that was damaged, lost or stolen by employees. But the answer lies in understanding these millions of behaviours and interpreting them in real time enabling appropriate and targeted interventions for customer-centric outcomes.


Reimagining retail

Black.ai is leading the way in surfacing retail interactions into actionable insights. CEO Keaton Okkonen has a vision to empower retailers with data and insights based on what is happening on their shop floor, helping them identify improvements and enhancements to how they operate by increasing sales, improving operational efficiency, and reducing theft. “Many retail store networks already have IP cameras installed for security purposes that monitor what is happening on shop floors. Our purpose at Black.ai is to accelerate the way businesses use valuable insights from all those customer behaviour interactions and allow them to deliver stronger customer-centric initiatives.”


Okkonen says that in talking to retailers he identified that the industry didn’t just need a solution to do a better job of seeing what was happening. The real opportunity was interpreting and understanding the behaviours at scale. “Just imagine being a store associate having to watch dozens of camera feeds for hours on end. This is a tedious and difficult role that makes it difficult to transfer knowledge into something meaningful and scalable for the business ongoing.”


The right solution for now and the future

If we break down the key challenges retailers are facing, Black.ai transforms the behaviours and activities occurring on the shop floor and enables retailers to deliver more robust, customer-centric solutions.

Currently in retail networks around the world, IP camera footage requires hours of manual review to find a moment of insight that is useful for either understanding and interpreting what is happening on-the-ground in stores. That interpretation can be highly subjective and influenced by how focused a staff member is from moment-to-moment, making it also prone to conscious and unconscious bias. It is impossible for any individual to recall, interpret or remember thousands or millions of interactions to make informed recommendations for action over one – ten – a hundred – a thousand stores.

“A real highlight retailers tell us, is that the Black.ai solution delivers data that is anonymised. Current solutions are invasive of personal privacy and are subject to both conscious and unconscious bias,” says Keaton.

For example, through the anonymised data the Black.ai system can identify potential theft behaviours which would enable an alert to the loss prevention team to deploy staff to help prevent theft. Research shows that simply acknowledging a person or having a staff member presence close to a situation can disrupt any possible theft and make the location undesirable, all without having an uncomfortable intervention.

Solutions for today and the future need to be focused on continual learning. The innovation that Black.ai delivers is ensuring that through machine learning a cumulative understanding of store-based activity will improve and enhance insights and decision-making based on a day-to-day basis. The key to real customer-centricity lies in being the best in taking action on the continued understanding and interpretation of customer behaviour as it happens and as it changes.

The race for effective and efficient retail operations and customer-centricity will be won by those businesses that understand and interpret customer behaviour as it happens. Black.ai can help deliver the insights, metrics and actions at scale in real time.


 


To find out how you can surface your shop-floor behaviour contact Yvonne, one of our retail experts for a demo of our solution at contact@black.ai.


Yvonne Xu is Customer Success Manager at Black.ai a cutting edge research and development start up in the artificial intelligence space. We admire the work they are doing, building advanced systems that utilise computer vision and high performance data organisation and association to enable human behaviours to be searchable through software.

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