Brands are collecting volumes of data generated by a variety of sources at extreme volume. This collection of data is Big Data. With the volume on an increasingly upward trend, new technologies are required to analyse and make sense out of it. Video data which is collected through various surveillance devices forms a significant part of big data. To leverage video data for better security and business performance, video analytics solution is most commonly used to analyse and translate this data into business insights.
What is video analytics?
Video analytics is a revolutionary technology that translates video footages into meaningful surveillance and business data using computer algorithms. It manages and monitors video from various surveillance devices to provide real-time data. This automation in managing and analyzing video reduces the need for security manpower or additional resources that would previously be required.
The 2 main purposes for video analytics is to provide real-time security alerts as they happen and to translate video data into business insights that can be used to increase business performance.
How does video analytics help retailers?
Video analytics empowers retailers to do much more with their in-store security cameras. With approximately 91% of retailers with surveillance cameras in stores, most retailers see video surveillance as a deterrent and incident investigation tool. However, harnessing the power of video analytics with existing surveillance cameras has opened up endless possibilities for improved decision-making.
KAI Square is a video analytics solutions provider with one of the widest range of video analytics solutions in the market. One main use of video analytics is to gain customer insights and shopping behavior. Some of the analytics that can be used to obtain customer behavior would be people counting, audience profiling, crowd density, human traffic flow and audience attention analytics.
People counting analytics tracks the number of people who enters and exits an area to derive the total number of people within a stipulated zone. Knowing the number of visitors to a store would give retailers an understanding of the conversion ratio. This also allows retailers to optimize staffing allocations and plan retail staff schedules more efficiently to place more staff during peak periods and days.
Audience profiling analytics helps users understand their audience demographics – age, gender and emotions. Knowing the ratio of males and females in store would allow retailers to make changes to selling messages and product displays. In addition, targeted advertising and marketing campaigns can be carried out to achieve better results.
Crowd density analytics helps to measure the overall activity level within an area, to indicate most or least crowded areas. Similar to the crowd density analytics, human traffic flow analytics tracks the path people take within an area, to identify the dominant paths taken by customers. Retailers would be able to optimize sales and profits through identifying the most optimal spots in store for products or advertisement placements. This information would also aid retailers to improve customer service by planning staff allocation within a store efficiently. Furthermore, brands would be able to review their store layout and product display to retain customers who were previously not interested in exploring the store.
Audience attention analytics measures the customers’ attention span captured at specific spots, giving retailers a good understanding of in-store buying behaviors and customer engagement. Besides helping retailers measure the amount of awareness a specific product or a marketing media gains to calculate conversion ratio, audience attention analytics also help retailers know which product or media works best with their in-store customers in retaining their attention.
Besides the mentioned above, video analytics is able to efficiently anticipate and secure retail stores from possible attempts of crime with the integration of security intelligence analytics. With the automation in reporting accurately real-time, live alerts will be sent to security personnel when a threat is detected. With a variety of security intelligence analytics such as face indexing, intrusion detection, perimeter defense, loitering detection, count limit detection and camera tampering, retailers are able to effectively secure their stores while reducing costs. Besides enhancing the overall operational efficiency, security video analytics reduces manpower previously needed to patrol the vicinity.
With the surge in big data trends and big box retailers such as Nordstrom tapping on big data to effectively market their products to customers, retailers need to start taking small steps in adopting new technologies. By first identifying the underlying problems before implementing solutions to it will enable businesses to reap great results. Video analytics makes businesses more agile and provides insights that could not be attained previously. To truly understand the benefits of video analytics, KAI Square is able to provide a free demonstration in your retail store. Simple drop us an email at marketing@kaisquare.com!