1.0 Introduction Modern technologies have severely advanced the retail environment. At the beginning retailers were sufferedwith the intimidating remarks of online opponents without any cost of retailshops. And also they were in a position to make better powerful targetpromotions with more effectively targetpromotions with comprehensive customer shopping and desire information. Thereafterretailers try to develop their own online features, characteristics etc.
Now, afterdeveloping those features, retailers want to learn new channel marketingsystems to adjust an online, analytical and much focused procedure with anaward of hands-in experience environment. Retailers mainly focused on intimidating comments fromonline contestants, in addition to being more effectively targeted forpromotions, at retail stores that are in a position to buy detailed consumershopping and desires information. At the present time, the retailers raisetheir online presence, retailers want complete channel marketing that bringsonline systematics, hugely selected approaches in-store intimacy andexperience. A number of few newtechnologies such as video analytics, Wi-Fi analytics, beacons, smart glasses, microelectro mechanical systems (MEMS) chips, LED Lighting, Bluetooth 4.0 and LoyaltyPrograms have come out to assist retailers optimize their store experience andprofitability. 1.
1 Problem BackgroundMake use of mobileapplications, Wi-Fi, Bluetooth and Beacon technology, now retailers can trackthe customer’s movements, customer’s location within the store. As an example For example, it holds a trackof customer movements and sends relevant information in each time a customerinstalling a store application and gets into the store and connects to theInternet. Now retailers use beacons to track customer location and sendnotifications via Bluetooth for customers without applications.
Some retailersoffer free Wi-Fi to customers and track their locations. Video tracking and facerecognition technology also uses to learn about customer behavior in spite of privacyrelated to in-store. As a better approach, no retailers collect Wi-Fi or GSMsignals from customers’ mobile phones and track customers since this technologyperform with a high accuracy and coverage. Through this study I wish topropose a system that that leverage analytics to refine store layouts withoutdoing any customer disturbance. 1.2 Research Question How can we develop a system that leverage analytics to refine storelayouts without doing any customer disturbance. 1.
3 Research Objectives· Exploring the customerlocation tracking technologies, pros and cons of each technology.· Optimize store layouts applyinga mining approach. 2.0 Literature Review2.1 Existing SystemsPreviouswork of applicability to this study crosses a wide range: localization, vision-basedsensing, human activity sensing, and physical analytics in retail IndoorLocalization and Sensing: We can sensing both environments and users by utilizinggroundwork and the environment.
In spite of the many work on Wi-Filocalization, existing work can achieve high precision only at the price ofhigh arrangement costs or extra information or adjustments on the Wi-Fi ingresspoint. CrowdInside introduces how to build an indoor floor plan using themovements of users with smartphones. Use dead reckoning along with anchorpoints to prevent accumulation of errors. Anchor points are defined by uniqueinertial sensor signatures corresponding to elevators, escalators, and stairs.However, such an inertia-based anchor point may be small or absent in thestore.