How to gain 10x more sales opportunities with AI based video analytics?
Everything from gaining customers to prospective sales identification depends on how well you are able to analyze your customer needs, which is why intelligent video analytics is a perfect fit for all businesses.
A successful company has customers at its core. The more they know about their customers and their needs, the more effective the sales and marketing efforts will be. An enterprise needs constant insights to understand a customer’s needs. Compared to other businesses, retail is a different sector. Consumer preference and buying patterns changes often so businesses
must adapt to these changes and should innovate more or risk losing sales.
Getting to know your customers is a tedious task and that’s where real-time video analytics comes into play. Real-time video analytics is a technology where video feeds are mined for actionable data without having the need to watch the video. Real-time video analytics helps understand the customers better and convert the information gathered into insightful data that can ultimately help retailers generate more sales and retain customers.
By applying Machine Learning Algorithms to video feeds from in-store cameras, retailers can capture the movement and behavior of people and turn it into predictive data. This means retailers can track customers, analyze the buying behavior of each customer, identify demographic information such as age, gender, finding redundancy in day-to-day operations, providing the right product and ad placements etc.
• Insights on in-store consumers
• Helps to better showcase best seller products in stores
• Easier comparison between various categories
• Provides a personalized customer experience
• Better allocation of staffs
• Optimizing inventory management
• Seamless product issues.
• Eliminate complexity
How Emotyx Real-time Video analytics drives more sales ?
Emotyx is a intelligent software suite built using computer vision and artificial intelligence technologies to enable real-time video analytics for security surveillance, customer tracking, data-driven product offers, automated feedback and to generate emotion based business insights from analyzing crowds in a facility.
Some of the most needed features of video analytics suite in retail are as follows:
Real-time video analytics can be used to detect at what time a customer engages with a product, signage or floor staff. The system can also check whether the consumer has compared a particular product with another brand or if they bought multiple products or how much time a customer spends before purchasing a product. The system can accurately keep track of those who have entered the store and made a purchase and those who have not. This information will help to identify the customer who is more willing to buy a product. The data thus collected can also be used to display apt promotions and ads for in-store displays.
Another use case is Segmentation, where we can divide customer data and demographics such as age, gender, location, shopping habits, product usage etc. Using this information, retailers can market their products to appeal directly to individual customer’s needs and interests.
Instead of guessing customer demographics, retailers can better know who they are targeting and provide better customer experiences based on intelligence. This will also allow retailers to identify segments that are most profitable, most valuable and allows them to control money spend on product categories that are less likely to yield any revenue.
Measuring Customer Impressions
Using video analytics, retailers can measure customer flow, customer traffic and can detect any increase in traffic due to an advertising campaign placed in the store. Retailers can measure how much time a customer spends in front of a promotional display, thus calculating ad impressions. These data can then be compared with point-of-sale information to see if an ad campaign got desired results. Another use case is where retailers can test and assess product
display across various store locations to find the most effective product placement.
Overcrowding and bottlenecks to the flow of shoppers will result in compromised customer experience. Video analytics data can be used to analyze crowd behavior by tracking how customers are lining up and being served. The system can count the number of people in the queue along with the estimated wait time for each person. This information can be used to distribute staff efficiently and improve staff management. This in turn, helps to avoid overcrowded areas and ensures a pleasant shopping experience.
Streamline checkout process
Providing a faster checkout time is vital for any retail business. Here too, Real-time video analysis can prevent long queues at the checkout area. The system can trigger real-time alerts when crowds start to form so that retailers can deploy additional cashiers or point-of-sale points before customers starts to abandon their purchase.
Identifying store performance
Video analytics can track store performance by a technique called Heat Mapping. Heat Mapping is a graphical representation that shows in-store roaming and time-spending patterns of customers. With Heat Mapping, retailers can improve the store layout and strategic product placement that will result in more sales. It can also be used to compare traffic patterns in store layouts for different time periods.
Heat Maps can also be used for staff planning as well. By identifying, peak-time, dwell-time and high occupancy locations, a retailer can decide if they need to deploy more staff or security in a particular area or not. This will reduce wait-time for customers, identify underutilized and strategic locations and optimize staff allocation.
Monitoring staff activities
Video analytics also helps to tracks and analyze staff activities such as how much time staff spend engaged with the customers or how much time they spend on the floor or how often they provide value-added activities etc. This information can be used to improve customer experiences.
Theft and Loss Prevention
One of the greatest difficulties in any retail business is securing space, preventing theft and loss happenings. Real-time video analysis can be used to detect intruders, unauthorized entry in areas that are restricted or secure. The system can also detect people who evade payment counters, bypass point-of-sale locations and also tracks event and behaviors that points to theft like
people loitering inside the store.
In today’s world, Real-time video analytics is an absolute requirement for retailers to improve their revenue and sales. With Real-time video analytics, retailers can increase store performance and operations in many meaningful ways. It helps retailers to enhance the customer shopping experience by reducing customer service time, providing ease of shopping, avoiding overcrowding and giving attractive buying options. Moreover, the technology is very easy to deploy and works with existing CCTV infrastructure.
With Real-time video analytics, data is converted into meaningful information. Using this information a retailer can serve the customer in a much better way and maximize store revenue and sales.
Video analytics holds a great potential to retrofit millions of security video installations in retail business. Deep learning and machine learning algorithms would most likely be the foundation to future improvements in video analytic solutions. In the very near future, video analytics is not only going to be used for advanced business monitoring and surveillance but also to drive automated business actions in real time.
Researches estimate that the overall market revenue from AI video analytic solutions would most likely exceed 800 million by 2022. This would contribute to 22% of video surveillance market overall revenue.
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