Based on artificial intelligence, VisionAI smart cameras can analyze face attributes from ages, genders, emotions to accessories. This is truly the technology solution that helps businesses optimize image dataset and provides the basis for business decisions.
According to reports from MarketsandMarkets, the global image data analytics market size will reach $6.51 billion by 2022, with a compound annual growth rate (CAGR) of 20.4%. The primary motive behind this trend is the rapid growth in both the quantity and the variety of business data (including image data), as well as the need for data-driven decision making.
Currently, in particular, consumer image data has become a valuable resource to retail businesses including convenience stores, supermarkets, shopping malls, etc., performing various tasks including efficiency analysis of advertising campaigns, target customer identification, movement and purchasing tracking, etc. Therefore, besides surveillance, these data also directly impact consumer behaviors and business performance.
To analyze customer traffic, footfall systems have been installed in supermarkets and shopping malls. However, it is able to count the number of people in and out only, rather than comprehensively analyze consumer characteristics & behaviors as well as turning data into valuable insights for business decision making and trend prediction.
AI analyzes customer face attributes
Compared to traditional footfall products, artificial intelligence (AI) solutions are capable of collecting and analyzing larger amounts of data, thus performing more tasks in the same amount of time.
A typical instance is VisionAI smart camera developed by VinBigdata. By applying computer vision technology, besides counting people, the product can also identify customer information (e.g. genders, ages and emotions), recognize VIP or foreign guests and notify of strangers, with the accuracy of facial recognition and analysis technology up to 99%.
With this feature, from the collected image data, businesses can easily identify target customers, conduct in-depth analysis and make appropriate alterations, which is the basis for personalized marketing campaigns to recommend the products to the target audience, increasing the probability of selection.
AI analyzes customer behavior
In addition to collecting customer traffic and volume (hours per day), VisionAI can also track traffic flow and analyze user behavior. Data on crowded areas or shopping time customers pay for each area are also recorded to determine the locations attracting customers, thereby serving the allocation of products and supporting resources.
Combined with facial recognition and customer analysis, collecting behavioral data helps VisionAI evaluate specific customer shopping trends. For instance, young customers are more interested in fashion, while the older are more likely to spend time at food or promotion stalls. The information will be suggestions for businesses to set up customer-oriented changes.
AI accelerates payment speed
Another activity of retailers is the payment process. In fact, payment processing speed greatly affects customer satisfaction and assessment of service quality. With VisionAI, the system will quickly determine the exact size of the payment queue as well as the time needed, which is the first step for retailers to accurately identify service problems and shift towards database establishment for important decisions.
Thus, with VisionAI – the new AI solution, retail businesses will have an effective assistant in collecting, processing and utilizing customer image data, before specifically application to optimize production and business efficiency as well as improve user experience. In fact, VisionAI has been implemented at a number of Vincom Retail shopping malls, providing statistics and identification 30% better than the traditional footfall system.
VisionAI belongs to the product line developed from Computer Vision technology by VinBigdata. Currently, besides VisionAI, in this product line, there is also VinOCR – a system that supports the detection, identification and extraction of handwriting information from document photos.