The Capabilities and Limitations of Video Analytics
Curious to see how these technologies could be put into practice? Take a look at “Symphoni”, which imagines how retailers and consumer packaged goods companies might orchestrate activities in the physical world by deploying smart sensors to transmit up-to-the minute information.
Genie IT Solutions
In part one of this series on sensors and analytics in retail, we explored how retailers can use beacon technologies to create a customized shopping experience and gather rich data about a shopper’s habits and interests. Another powerful tool in understanding the customer journey through a store is video analytics.
While video as a technology is nothing new, the maturity of computer vision algorithms has enabled automated tracking of objects appearing within a video. With the application of parallel processing platforms such as Hadoop, these process intensive tasks can be performed at scale. Combined, these tools empower retailers with an understanding of the types of customers who are entering their stores, their precise movements and how they can direct their attention. Below are just a few of the capabilities retailers could utilize with video analytics:
- Traffic Flow: Define virtual tripwires to understand conversion rates from sidewalk to store or whether the majority of customers turn left or right upon entering a store
- Dwell times: Determine the effectiveness of an advertisement or endcap display by tracking what percentage of customers stop to notice the ad and what percentage do not
- Demographics: Understand the age and gender breakdown of customers entering a store
- Heat maps: Develop a visual representation of the activity within a store to optimize store layout and the sale of high margin items
- Queue Analysis: Determine relative queue size to optimize staffing for both normal and peak shopping periods.
- Security and Safety: Use machine learning algorithms to automatically detect suspicious or out of the ordinary behavior in real time.