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Title:	網路資料庫在新成屋及預售屋精準行銷之運用分析
Authors:	陳韻如
Contributors:	林祖嘉陳韻如
Keywords:	網站大數據忠誠訪客精準行銷看屋成交率 Big data Repeat Visitors(Returning Visitors) Precision Marketing Open Houses Sales Closing Ratio
Date:	2016
Issue Date:	2016-09-02 00:00:56 (UTC+8)
Abstract:	自2003 年以來，房地產市場面臨不少景氣波動波段，在2016 年實施房地合一稅之後，更開始醞釀一個新的產業結構。目前建商及代銷業者在銷售時最大的困境，便是難以取得潛在及顯在買方的相關資訊，無法洞悉買方從何而來，無法掌握買方的心態。在過去傳統行銷媒體效果已經逐漸式微的情況下，該運用何種方式與買方接近，適當有效地投送媒體預算，已經成為維繫房地產業者生存的當務之急。本研究嘗試運用Y 網站大數據資料庫的分析，搜集買方資訊，並以台灣北、中、南不同區位及不同型態新建案為案例，分析案例在網站上的訪客反應，藉由新建案訪客來源縣市、訪客造訪前一頁及忠誠訪客行為等不同面向的分析，過濾出精準的忠誠訪客，再針對這些目標客戶採取積極性行銷，將行銷資源集中在這些相對高意願的訪客，以達到精準行銷的目的，達成銷售預期。經由Y 網站對四個案例的分析顯示，台北買方長期投資的選擇區位似乎有南移跡象。本研究中的案例皆位於六都，顯示台北客對於六都其他都會區的新建案都抱持頗高的查閱意願，顯示台北客的潛在購買意願高。另，關注新建案的買方來源的前一頁，約有六成以上來自於Google，在行銷預算的配置上，應可加強Google 的預算比例。新建案的買方，無論北部、中部或是南部，其忠誠客戶的比例皆約佔兩成左右，新建案行銷時應集中加強行銷強度，將忠誠買方從線上導向實體的預約看屋行為，提升看屋成交率。 Real Estate market has gone through several economic fluctuations since 2003, and the industry is currently undergoing restructuring after the consolidated housing-and-land income tax reformed in 2016. The biggest predicament confronted by both of the real estate developers and advertisement sale-agents is often difficult to gather the list and the information of prospective and obvious buyers, and clearly understand their minds. To stay in business, the top priority now is: how to plan and manage a cost-effective marketing spend to approach buyers when traditional methods of marketing have become less effective. This thesis focuses on the application of web analytics from Y website to gather buyer’s information, and demonstrated with samples from the different areas across North, Central, and South region of Taiwan, also different types of new construction real estates; by further studying the geographic, referral traffics, and sticky contents and hits of returning visitors, and further screen out the shortlist target buyers from the repeat visitors, then focus the marketing resources to take proactive sales approach and precision marketing in targeting the most potential buyers and meet the sales expectation. The web analytics from Y website on these four cases indicates that Taipei web visitors’ favored long-term investment choice is shifting toward South. All samples from the 6 special municipalities in Taiwan shows web visitors from Taipei are most interested in new construction real estates located in the other 5 special municipalities; even higher than web visitors from its own district area, which reveals that there are more potential buyers in Taipei, and the developers in those 5 special municipalities should try to distribute more marketing resources in Taipei. Similarly, study shows up to 60% of the referral traffics are from Google, it is suggested to allocate more marketing funds in Google. Statistics from across all region also articulate that about 20% of closing sales are repeat visitors, the sellers should screen out the shortlist target buyers from the repeat visitors, then focus the marketing resources to take proactive sales approach in getting buyers to show up in open-house for on-site sales to follow up and increasing the closing ratio.
Reference:	圖書(Books) (1)Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die、陳琇玲譯，2014，『預測分析時代-讓數據告訴你，誰會買、誰說謊、誰會離職、誰會死！』初版，台北，大牌出版/遠足文化事業股份有限公司 (2)Brian Clifton(2010)，黃志雄、戴文彬、陳誼峰譯，『流量的秘密』初版，台北，松崗資產管理， (3)曾文龍(1993)，『房地產過去、現在、未來』，台北，大日出版社 (4)周俊吉(2015)，『2015台灣地區房地產年鑑』初版，政治大學商學院信義不動產研究發展中心編著，台北，行義文化出版 (5) Viktor Mayer-Schonberger、Kenneth Cukier(2013)，林俊宏譯，『大數據Big Data:A Revolution That Will Transform How We Live, Work, and Think』，台灣，天下文化出版 (6)張明義、許惠瑜，2013，『完銷力』，台北，詹氏書局 (7)城田真琴(2013)，『Big Data大數據的獲利模式：圖解‧案例‧策略‧實戰』，鐘慧真與梁世英譯，經濟新潮社 (8)胡世忠(2013)，『雲端時代的殺手級應用：Big Data海量資料分析』，天下雜誌 (9)財團法人資訊工業策進會前瞻所(2014)，『巨量資料簡介』，取自http://www.nacs.gov.tw/NcsiWebFileDocuments/3c2136cf0801ea10c866aaa770aa3e94.pptx (10)劉文良(2010)，『顧客關係管理：新時代的決勝關鍵，碁峯資訊股份有限公司』研究報告或技術報告(Technical Reports) (1)亞太地區數位趨勢報告(The APAC Digital report) Adobe ,CMO Council,Paul Robson(2015) (2)2016年全球IT行業報告(IDC FutureScape: Worldwide IT Industry 2016 Predictions- Leading Digital Transformation) IDC,(2016) (3)2016：決定客戶時代成敗的十大關鍵成功因素（The 2016 Top 10 Critical Success Factors To Determine Who Wins And Who Fails In The Age Of The Customer）Forrester(2016) (4) Gartner研究報告(2015) 報紙報導(Newspapers) (1)蘇蘅(2014)，『擁抱大數據與新石油共舞』，聯合報，取自http://udn.com/NEWS/OPINION/OPI4/8767536.shtml。英文部分電子資源(Electronic Documents) (1) 智庫百科(http://wiki.mbalib.com/zh-tw) (2) Alexa排名網站(www.alexa.com)
Description:	碩士國立政治大學經營管理碩士學程(EMBA) 99932091
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0999320911
Data Type:	thesis
Appears in Collections:	[Executive Master of Business Administration] Theses

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