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Proximity Marketing Using Bluetooth Low Energy

机译:使用低功耗蓝牙的近距离营销

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Proximity marketing is a type of marketing that involves a local approach to advertising using wireless media. Technically, it can be used for use cases which involve advertising to potential users at a particular location. In this paper, we propose to use the technology of Bluetooth Low Energy (Bluetooth 4.0) for proximity marketing at a retail store. Bluetooth Low Energy, a wireless PAN technology, is an eco-friendly form of Bluetooth specifically designed for IoT applications. With the advent of the practice of using the IoT framework for automating processes, an approach to use this technology at a retail store could potentially eradicate the need to hire marketing staff and invest in traditional marketing strategies. This process of automation makes use of devices called beacons for transmitting BLE signals, a mobile application on a smartphone and centralised data storage on a server. Beacons can be detected by a mobile application on a smartphone and beacon specific data regarding particular offers and products can be collected from the centralized storage hosted on a server, which can be used for marketing the retail store's products and offers. This application basically acts as a shopping guide for the customers of that particular retail store. In addition to the automation of the marketing task, machine learning can be used for personalizing offers based on each customer's purchase history. Some other features that can be incorporated into the product include an indoor positioning system, a click and collect facility, payment wallet integration, etc. This approach automates the entire shopping experience and is a novel application of IoT in automating trivial tasks.
机译:邻近市场营销是一种市场营销类型,涉及使用无线媒体进行本地广告投放的方法。从技术上讲,它可以用于涉及向特定位置的潜在用户做广告的用例。在本文中,我们建议在零售商店中使用低功耗蓝牙技术(蓝牙4.0)进行邻近营销。低功耗蓝牙(Bluetooth Low Energy)是一种无线PAN技术,是专为物联网应用而设计的一种环保形式的蓝牙。随着使用IoT框架实现流程自动化的实践的到来,在零售商店中使用该技术的方法可能会消除对雇用营销人员和投资于传统营销策略的需求。这种自动化过程利用称为信标的设备来传输BLE信号,智能手机上的移动应用程序以及服务器上的集中式数据存储。可以通过智能手机上的移动应用程序检测信标,并且可以从服务器上托管的集中存储中收集有关特定优惠和产品的信标特定数据,该数据可以用于营销零售商店的产品和优惠。该应用程序基本上充当该特定零售商店客户的购物指南。除了自动执行营销任务外,机器学习还可用于根据每个客户的购买历史来个性化报价。可以整合到产品中的其他一些功能包括室内定位系统,点击收集设施,支付钱包集成等。这种方法可以使整个购物体验自动化,并且是IoT在自动完成琐碎任务中的一种新颖应用。

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