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Industry Solutions Retail

The Benefits of Using Retail Loss Prevention Cameras for In-Store Analytics

Even with heavy investments in security technology, retail loss and shrinkage is still proving to be an issue for retailers.  According to the National Retail Federation, inventory shrink totaled $44 billion in losses for retailers in 2014. Retail loss prevention cameras are a requirement for businesses these days – not because they necessarily prevent theft from occurring, but because they allow business owners and managers to review incidents and gather evidence after theft has occurred.

Identifying the various sources of loss and shrink can be daunting. Return fraud is difficult to detect, as is “sweethearting” (deliberate employee theft or fraud) at the register. Utilizing cameras – as well as other physical security measures like RFID and electronic article surveillance (EAS) tags – has helped with inventory shrinkage.

However, retailers need to start thinking about other uses for cameras within the four walls of their businesses. Many retail loss prevention cameras are nothing more than recording devices, but newer options make it easy for cameras to also track customer statistics and provide in-store analytics for business owners. These solutions combine analytics software, video cameras, and in-store sensors to provide accurate, real-time data about store traffic and sales.

Newer cameras, which can detect specific movements and activities, can be used to assess basic motion/movement, queue lengths, dwell times, and customer traffic patterns. We have reached a point where most of the technologies we own have multiple purposes – cell phones, for example, are also cameras, computers, and much more. It is time to ensure that loss prevention cameras are maximizing their value for retailers.

Data is more important than ever before, and cameras are perfect for collecting information about all the customers in every section of a store – at all times. While this might seem a little bit like Big Brother at first, in-store analytics can be used to benefit both the retailer and the customers. Managers can assess lines/queues and have the right employees on hand to handle busier days or times. In-store analytics create a more holistic understanding of traffic patterns can help owners identify and eliminate bottlenecks.

As for benefits to the retailers themselves, in-store analytics can be tied into promotions and sales in order to assess and improve effectiveness. Dwell times – how long customers stay in certain areas of the store – should be used when framing the locations of promotions within the store. Also, after a sale has concluded, owners can see how the sale impacted dwell times within the store.

Analytics systems – which go hand in hand with retail loss prevention cameras – can help measure sales conversions, more effectively deploy staff, and improve register wait times and dwell times. That same data can help identify suspicious behavior in the store before merchandise is stolen. These systems can also help note when there may be employee return fraud (if a customer is not present during the transaction), and note if a shopper is trying to enter a restricted area or move in an unexpected or wrong direction.

Retailers will always experience a certain amount of loss or shrink, but by combining in-store analytics solutions with traditional video surveillance and other technologies, stores can more quickly identify and stop theft, spot employee fraud, and implement strategies that will further justify the ROI and open up new areas of profitability.

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Retail RFID Hardware RFID Software

In-Store Analytics: The Future of Retail

The balance of power when it comes to information has shifted from retailers to shoppers with the advent of e-tailing. Shoppers now have access to an infinite amount of competitive pricing information. Even if customers walk into a retail location, they may simply evaluate products in person, then purchase online from another retailer, or hustle down the street to a competitor who is offering a better deal.

Retailers need to be able to evaluate real-time consumer data in order to capture customer business more effectively. More importantly, they need access to in-store analytics capabilities to turn that data into actionable business information. According to the Forrester Consulting and RetailNext study “Real-Time Data Drives the Future of Retail,” consumer and retailer perceptions are not aligned, and many stores lack the technology to utilize shopper data across channels. The study also found that retailers struggle to measure customer behavior. Just 33 percent, for example, reported always measuring conversion rates.

Forrester believes the store of the future will be powered by real-time in-store analytics that can predict shopper behavior over the entire “shopping journey” across multiple channels.

This means more than just head counts and point of sale data. In-store analytics allows retailers to evaluate everything from the effectiveness of a display, apparel size selection, and store layout by tracking how customers interact with merchandise. Why did they try something on and not buy it? Are there areas of the store that customers simply don’t walk through? Is end-cap display placement affecting sales of nearby products?

Consumers shop with their mobile devices and expect to encounter sales associates who can use that same technology to help them find the right product at the right price. Those shoppers also want to experience a consistent sales experience and consistent pricing across channels.

Using analytics, retailers can evaluate traffic, conversion, fixture engagement, shopper paths, and other data, and use that information to rapidly adjust their marketing and in-store operations, as well as provide better data so that buyers and planners can make better decisions. The data can help stores evaluate why a particular item didn’t sell or help prepare for a potential out-of-stock situation.

Real-Time Data Fuels Analytics

Getting that data requires the integration of point-of-sale data, online channel data, information from in-store sensors and RFID systems, and data pulled from other mobile and online interactions. This investment in in-store analytics, combined with the ability to quickly share data across operational areas, can help retailers respond more quickly to sales trends, provide information that can be useful in vendor negotiations, and create more effective buy plans.

Analytics can also help address other data gaps in retail. When customers enter a store but don’t purchase anything, retailers gain zero data. Additional information from sales associates and sensor/RFID systems could help provide a better understanding of those shoppers. In-store analytics can provide information that will help improve product mix optimization, and gain a better return on investment in their data collection activities. Analytics can also improve the use of campaigns and promotional displays based on actual customer behavior.

By linking in-store mobility systems to customer data, sales associates and managers can respond more quickly to customer needs while they are still in the store, which can help increase conversions and turn shoppers into buyers. Stores can also improve staffing levels based on shopper volume, improve store layout, or co-locate products that are frequently purchased together. Getting shoppers into your store is only half the battle. Analytics can help you better understand the customers you’ve already attracted, keep them coming back, and encourage them to buy more from you, and do so more often.