BUSINESS INTELLIGENCE BEYOND SWEETHEARTING!

VIDEO ANALYTICS IN RETAIL STORES

There is a significant difference in video surveillance and the use of complex video analytics.  One major type of retail fraud, sweethearting, where a cashier intentionally fails to enter one or more items into the transaction in an attempt to get free merchandise for the customer, can be easily detected by a surveillance video camera that is monitored by an employee. This helps prevent losses and increase cost efficiency but does not substantially improve efficiency and increase sales since we have not captured any knowledge of what is influencing a client in a store.

Thus, understanding consumer behavior can be a very useful tactic to maximize store productivity and add value to a store’s business operations. Sucess is crucially dependand on understanding the PSYCHOLOGICAL PROCESS BEHIND A CLIENT’S PURCHASE BEHAVIOR.

Video analytics comes into play by using refined algorithms that calculate what factors are influencial on the clients experience in a retail shop and DELIVERING A BEHAVIORAL SNAPSHOT of the shopper.

Surveillance captures consumer behavior

By analyzing captured video material, basic data can be collected such as the simple counting of entrance and exit data, queuing behavior and respective waiting times or the effectiveness of the customer flow within the store. We can collect traffic statistics to determine optimal staff deployment and promotional plans and optimize overall planning. This gives information about specific customer as well as employee experiences and conclusions can be drawn how they may be marketed to. Moreover, Video Analytics helps to identify potential stock cuts and reports on shelf availability. The retailer is given the possibility to establish an automated anticipation alert and is able to replace products on the shelves that are running out.

Something revolutionary about video analytics is that it allows retail managers to gain insights into customers’ interaction with the employees and analyze consumer behavior. Touch points of engagement are videotaped and analyzed, making it possible to draw conclusions out of these interactions and improve them towards the client’s desires. Furthermore we can observe which parts of the store are the most frequented and follow the customer’s buying pattern. Trough surveillance we observe the paths customers navigate through the store, observe dwell time etc. This gives valuable information as to how to arrange product placement, take merchandizing decisions, improve customer satisfaction, product promotions, optimize staff allocation and deliver valuable, personalized customer messages. Moreover, organizations can use consumer information to learn about the needs and opinions of shoppers in ways not previously possible. Big data analysis offers companies a way to identify those shoppers who are the most valuable as returning customers. DATA COLLECTION BOOSTS CUSTOMER LOYALTY. We may thus add value through better customer service and are also by utilizing the ability to influence the customer’s buying pattern subconsciously.

Video Analytics shows a motion path and the dwell time of consumers

The productivity and accurate data interpretation is also crucially enhanced by the use of Video Analytics. In order to make managerial decisions, executives need accurate and reliable information. Retail Video Analytics is providing the means to drive business decisions that rely on hard facts. Retailers used to have to draw their own conclusions from obersavation. Now, the hiring of trained personnel becomes obsolete due to an automated data analysis displayed on dashboards that PRESENT,VISUALIZE AND INTERPRET LIVE METRICTS FROM THE STORE.

References:

http://www.forbes.com/sites/xerox/2013/09/27/big-data-boosts-customer-loyalty-no-really/

http://www.agentvi.com/images/Agent_Vi_-_Retail_Applications.pdf

http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=4425348&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D4425348

http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=4959867&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D4959867

http://www.retailnext.net/analytics-technology/visualization