At the beginning of lockdown in the UK, many supermarkets were facing panic buying mayhem, with stores experiencing Christmas-level shopping without any of the stock preparation. After this initial surge, stores have been hit hard during the prolonged lockdown period with The Office for National Statistics stating retail good’s sales fell by 18.1% in April, with even more drastic drops for department and clothing stores.
Whilst doors are now re-opening for non-food retailers and supermarkets are starting to see an increase in footfall, there are still months of reduced or in some cases a complete loss of revenue to make up for. After facing this slump and customers still feeling apprehension about returning to normal shopping levels, retailers need to focus on
Shrinkage is a massive cost for retailers in the UK, with last year’s figures showing a loss of almost £5.5 billion in retail shrinkage alone and the average shrinkage rate was 1.42%.
Source: British Retail Consortium (2019) Retail Crime Survey
Self-checkouts have always experienced the highest rate of theft, with people simply not scanning products or ticket switching and with social distancing regulations, a greater demand for autonomous checkouts can be predicted, increasing these figures further.
Traditional solutions like video surveillance or security tags are no longer making the cut, as they are only reducing theft figures on a small basis and are not providing an overall substantial reduction, even when the technologies are combined. Shoplifters are becoming increasingly more aware of these tactics and they are no longer having a substantial impact.
One of the ways retailers can reduce shrink in their stores is to leverage security technologies that are powered by artificial intelligence.
Retailers currently have relatively little data on where shrinkage occurs and have hardly any accurate figures around shrinkage levels, any information they do receive is generally out of date.
Edge-based machine vision technology that is used in our Loss Prevention solution provides real-time loss insight through object identification at self-checkouts. This technology is specifically trained through machine learning algorithms on a store’s inventory and can identify products on a granular level. Our technology even has the potential to be trained on brand-own products.
Our solution can be integrated with self-checkouts’ barcode scanners and can identify loss when items are not scanned or substituted. It can even identify when irregularities occur and can be capable of locking the checkouts down to avoid loss completely. Alternatively, it has the capability to send real-time alerts to managers so they can intervene before loss occurs.
Over time, all the data surrounding shrinkage is collated and can be analysed on both a store and estate-wide basis. This means trends and correlations can be detected, such as identifying when a product has a higher than average theft rate in certain stores. A manager can review this information to gain a better understanding of their retail shrinkage and why it’s occurring; is the item close to the exit and easy to steal? Is there no security surveillance in that area of the store? From this, store managers can make more informed decisions and implement effective changes to minimise future shrinkage.
Our solution focuses on catching incidents as they occur at the point of sale with a high level of accuracy without interfering with customers’ experience. Whilst loss prevention is a priority issue, it should not come at the expense of customer satisfaction. When adopted correctly, AI-driven machine vision can prevent loss and improve the bottom line.
As shoppers begin to return to the aisles, a robust, data-driven loss prevention strategy could make up the losses retailers have seen earlier in the year and continue to produce value in their bid against retail shrinkage, for years to come.
If you would like to find out more about how our loss prevention solution could reduce your store shrinkage, then get in touch.