基於社群媒體意見預測市場偏好服務套裝

Abstract

本研究提出一個創新的方法，將所有產品皆表達成為元素組合的服務套裝形式，並根據當時的社群網站評論意見，進行市場喜好分析，預測次季熱門的服務套裝，推薦給企業行銷部門做為調整產品內容的參考方向。透過比較上市產品的實際銷售紀錄以及模型預測的銷售結果，兩年間共八季的實驗數據顯示，本研究的分析方法產生的推薦排序相關性超越傳統銷售預測的效能，因而能夠做為服務套裝產品連結輿情分析的解決方案。

This study proposes an innovative method, which presents all the products in packages of multiple elements and conducts market preference analysis based on the opinions in social media at the time collected by Web Crawler, to forecast popular packages for advising marketing departments on the adjustment of product content. An experiment is made to compare the actual sales records by a large enterprise during two years with the sales data predicted by the trained model that can forecast the next quarter according to the relevant online opinions about the previous quarter. With the comparison results of eight quarters during the two years, this analysis method proves to surpass the efficiency of traditional sales forecasting approaches, and therefore can be the solutions of public opinion analysis for service packages.