Scientists from Queensland University of Technology (QUT) will propose as part of the International Research Team Store design framework based on artificial intelligence For retail sellers. In this way, shop managers can take advantage of the latest progress in AI techniques and its sub -component in a computer vision and deep learning to monitor and analyze the behavior of their clients' purchases.
The efficient store design works to draw customer attention to products that they did not plan to buy, increase browsing time and facilitate finding related or alternative grouped items. Understanding the emotions of customers, because they are looking for products, it can provide marketers and managers with a valuable tool to better understand the reaction of customers to the goods sold.
In addition to recognizing emotions through face guidelines and customer characteristics, system managers can use heat map analytics, human trajectory tracking techniques and recognizing customer activities to inform their decisions. All this can be assessed directly on the basis of a video in the store and can be useful for a better understanding of customer behavior in stores without knowing personal information or identifying customers.
Professor Clinton Fookes said that the team proposed for retailers a medical scope of thinking about thinking and thinking (steel) to achieve all of the above: “First, Sense There is a collection of raw data, say video from CCTV cameras in a store for processing and analysis. Shops managers do it routinely with their own eyes; However, new approaches allow us to automate this aspect of detection and do it throughout the store.
Secondly, Think It is processing data collected through advanced artificial intelligence, data analysis and deep machine learning techniques, such as the way people use their brains to process incoming data.
Thirdly, Work It is to use knowledge and observations from the second phase to improve and optimize the supermarket system. The process acts as a continuous learning cycle. “
According to Professor Fookes: “The advantage of these frames is that it allows retailers to assess store design forecasts, such as movement flow and behavior when customers enter the store or the popularity of store displays placed in different areas of the store.”
The QDATA team came to similar conclusions about the need to analyze the behavior of game users, because continuous monitoring of user involvement is an integral part of the development of the game.
In the analysis of the game processes, QData has developed a comprehensive KPI tracking system from scratch. The system provides for generating a configurable set of reports for selected products, enabling both reflection of the current project performance and the forecasts of the player's behavior using segmentation, conversion analysis, input funnels, A/B testing, purchasing behavior analysis, etc.
Read more information about the analysis of the behavior of the game users by QDATA HERE
