餐廳雲端服務平台與客戶滿意度調查數據分析

Abstract

餐廳業者為了提升服務而不斷的嘗試許多新的電子雲端服務，例如電子點餐，線上訂位等；但因為尚未有平台提供完整的整合性服務，導致店家需要使用這些功能時，必須要導入多個不同的系統，造成管理上的困難。此外，大多數的平台接無法提供有效的數據分析給店家作為決策參考，浪費了這些數據的價值， 本研究希望透過研究Tagfans雲端平台之應用服務，提供一套完整性的解決方案，來解決餐廳在營運上遇到的問題（例如：點餐、排隊、預約、客戶滿意度調查…等），此外提供滿意度調查表數據案例，結合資料探勘分析，來提升各項功能收集到數據的分析價值與決策參考。

In present days, restaurants in the market are trying constantly to enhance their services by utilizing new technologies such as cloud, electronic ordering, and online booking. However, there has not a completed and vertically integrated system emerging to the market just yet. Restaurants, usually with insufficient IT experiences, struggle to manage and integrate above functions and control systems. Consequently, this increases the managing difficulties and cost to provide a user friendly service. Moreover, most of the platforms cannot collect data effectively, wasting the value of data, where managers could have analyzed those patterns and then feedback to their restaurants as a decision reference.

The purpose of this study aims to provide a complete solution to address the problems above by studying the application services of Tagfans cloud-based platform (eg, ordering, queuing, booking, customer satisfaction survey, etc.). The Tagfans service platform is presented to provide integrated services to restaurants. The satisfaction survey data are collected and analyzed by various data mining methods. The analytical result can be used to to enhance the follow-up data value of each function for further decision making.