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A data mining approach to developing the profiles of hotel customers

A data mining approach to developing the profiles of hotel customers. M964020028 廖文柏 B934020004 蔡郁槐 9142026 陳建宏. 指導老師: 黃三益 教授. 1.background and motivation. 1.1 南韓觀光及飯店產業變化. 近年來南韓的觀光旅遊業快速發展 觀光旅遊相關收入,在十年內成長了一倍 新旅館快速增加 原有旅館均積極的增加房間數 過快的飯店房間供給量擴展 供過於求,競爭激烈. 1.2 旅館業的競爭.

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A data mining approach to developing the profiles of hotel customers

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  1. A data mining approach to developing the profiles of hotel customers M964020028 廖文柏 B934020004 蔡郁槐 9142026 陳建宏 指導老師: 黃三益 教授

  2. 1.background and motivation

  3. 1.1南韓觀光及飯店產業變化 • 近年來南韓的觀光旅遊業快速發展 • 觀光旅遊相關收入,在十年內成長了一倍 • 新旅館快速增加 原有旅館均積極的增加房間數 • 過快的飯店房間供給量擴展 • 供過於求,競爭激烈

  4. 1.2旅館業的競爭 • 旅館業生存的關鍵在於滿足顧客的需求 • 關注於”有價值”的顧客 • 常客 • 較願意付費使用服務的客人 • 提高既有顧客的回流率 • 了解顧客消費的習慣及特性 • 顧客關係管理(CRM)相關的問題

  5. 1.3提升顧客滿意度 • 顧客對一家飯店的滿意程度 • 房間的狀況 • check in/out 速度 • 服務態度 • 價錢 • 等等其他

  6. 1.4有效針對問題改善 • 光是盲目的提升品質是沒有效率的 • 要能了解 • 顧客的各種相關資訊 • 客人的需要 • 對客人在意的項目優先做改善

  7. 1.5提升飯店競爭力的重點 • 什麼樣的客人會在一次的光顧 • 什麼樣的客人容易轉向其他競爭者 • 什麼樣的服務性質對於什麼樣的客人是相對重要的 • 如何區隔有/非助於收益的客人 • 什麼類型的客人最符合目前飯店能提供的服務能力

  8. 1.6為何使用data mining • 使用data mining技術來探討以上問題的原因,因為data mining可以 • 找出hidden knowledge • 找出unexpected patterns • 找出new rules

  9. 2.Data Set

  10. Data Collection • Questionnaire • Target select from 11 hotels( Westin Chosun,Grand Intercontinental,Hilton,Grand Hyatt,Grand Hyatt… ). • All the hotels have the same characters: • 1.in terms of price • 2.location • 3.services amenities

  11. Questionnaire items • Demographic • Gender • Age • Occupation • Nationality • Frequency of their hotel visitations • the Purpose of their travel • Relative importance of services attributes to overall hotel service quality • the level of customer satisfaction based on their service

  12. Questionnaire items • Non-Demographic • Service attributes critical to hotel service quality • courtesy of employees • prompt / smooth handling of customer complaints • convenience of reservation

  13. Questionnaire Target • Skip out potential participants • Focus on those customer who had just checked out and were waiting in the lobby for a shuttle bus, or taxi. • No more than $5 financial incentive • Each hotel select 30 people to fill out the questionnaire

  14. Feedback • 281 return(85.15%) • 74% visited more than one of these hotels at least once in the past • 91.1% having stayed at one of these hotels for more than one night

  15. 3.Research methodology

  16. Research instrument Traditionally, data collected from the questionnaire survey were analyzed using statistical techniques although hypothesis testing may allow us to validate some intuitive premises, causal inferences made by hypothesis testing may not be sufficient for us to accurately predict behavioral patterns

  17. Data Mining Process Step 1:資料的蒐集(Data collection) Step 2:資料的格式化(Data formatting) Step 3:規則的歸納(Rule induction)

  18. Data Mining Steps 例如:年齡(Age) 20 – 29  1 30 – 39  2 40 – 49  3 50 – 59  4 60以上5 Step2 Data formatting Step3 Rule induction Step1 Data collection

  19. SPSS Clementine

  20. KDnuggets 2005 年票選 DM工具

  21. Example: 決策樹(Appendix 4)

  22. 4.If-then rules 結果整理

  23. 4.1.Summary of if-then rules for the hotel choice • 什麼樣消費行為和特性的客人通常會傾向於選擇哪家飯店 • 若符合 1.非常滿意員工的服務態度 2.住宿目的是休閒旅遊 3.有點或非常滿意飯店對於他再次光臨的設想程度 • 且若:非信用卡付費通常選擇Plaza hotel • 且若:信用卡付費通常選擇Hyatt hotel

  24. 4.2.Summary of if-then rules for the nationality of hotel guests • 什麼樣消費行為和特性的客人通常會是什麼樣的國家來的客人 • 若符合 1.選擇兩張床的房型 2.住宿的目的是商務或會議 • 且若:顧客認為房內設施有重要性通常是美國人 • 且若:顧客認為房內設施非常重要通常是韓國人

  25. 4.3.Summary of if-then rules for the occupations of hotel guests • 什麼樣消費行為和特性的客人通常會是什麼樣工作職位 • 若顧客是男性,且 • 選擇Amiga或Plaza hotel通常是企業家 • 選擇Chosun,Coex International,Hyatt,Ritz Carlton或Sheraton hotel通常是經理人 • 選擇Grand International或Hilton hotel通常是專業工作者

  26. 4.4.Summary of if-then rules for the gender of hotel guests • 什麼樣消費行為和特性的客人通常會是什麼性別 • 如果顧客住宿的原因是休閒旅遊,且工作職位是經理人或政府工作通常顧客是男性 • 如果顧客住宿的原因是休閒旅遊,且工作職位是專業工作者,且認為房間的清潔是極度重要的通常這樣的顧客是女性

  27. 4.5.Summary of if-then rules for the purpose of trip If a customer uses a traveler’ check to pay for a hotel room charge, then the customer is likely to be a business traveler If a customer pays the hotel cash for a hotel room charge,and the customer stays at the standard floorthen the customer is likely to be a tourist

  28. 4.6.Summary of if-then rules for the age of hotel guests If a customer is a manager,then the customer’s age group in the 30s(30-39 years old) If a customer is an entrepreneur,and the customer is somewhat or verysatisfied with the hotel’s complimentary items(free newspaper, tea, or coffee),then the customer’s age group is in the 40s and 50s(40 – 59 years)

  29. 4.7.Summary of if-then rules for the frequency of hotel visitation If a customer has visited the hotel where he/she currently stays fours times,and the customer is in his/her 30s,then the customer is likely to revisit the sameor a similar hotel three to four times.

  30. 4.7.Summary of if-then rules for the frequency of hotel visitation(Cont.) If a customers has visited the hotel wherehe/she currently stays more than five times,and the customer is a female,then the customer is likely to revisit the sameor a similar hotel more than tem times.

  31. 4.8.Summary of if-then rules for the patronage of particular hotel If a customer has stayed at the Plaza hotel formore than five nights,then the customer is likely revisit the samehotel more than five times

  32. 4.8.Summary of if-then rules for the patronage of particular hotel(Cont.) If a customer has stayed at the Chosun hotel for a business trip,then the customer is likely to revisit the samehotel at least four times

  33. 9.Summary of if-then rules for the length of a hotel stay • 例:Rule36(b) • If 客戶選擇 standard floor of the hotel, • And 客戶比較喜歡雙人床, • And 客戶是韓國人, • Then 客戶可能會待兩晚

  34. 10.Summary of if-then rules for the payment option • 例:Rule40(b) • If 客戶是因為辦公住房, • And 客戶又是女的, • And 客戶已經在旅遊機構瀏覽過hotel資訊, • Then 客戶可能會使用旅遊卡付費

  35. 11.Summary of if-then rules for the smoking/non-smoking preferences • 例:Rule47 • if 客戶是因為business住房, • And 客戶選擇雙人床, • And 客戶makes a direct reservation of hotel, • And 客戶滿意房間的清潔度, • Then 客戶可能會選擇non-smoking room

  36. 5.Conclusions

  37. Conclusion 1 • 客戶的旅遊目的通常會影響他們選擇下榻哪間hotel的抉擇。 • 例如:如果hotel在房間內可以提供辦公桌,那他們將會比其他業者贏得更多US國籍的客戶。因為調查顯示US客戶都是辦公居多,而日本客戶通常都是為了旅遊而來。

  38. Conclusion 2 • 30s的客戶或是40s的女性客戶通常下次選擇住同家的hotel的機率很高。 • 而問卷調查也顯示,似乎Plaza、Chosun、Hilton、Hyatt、Amiga已經建立屬於自己的客戶型態,這些客戶都具有一定的忠誠度。 • 最有可能的解釋是,這些店家其實在services attributes調查滿意度上,其實都是鰲首。所以店家千萬不可輕忽各項服務所帶給客戶的印象。

  39. Conclusion 3 • 作者發現這項問卷有些脈絡可循,例如男性客戶的職位職稱,對於他們選擇的hotel似乎有連帶關係。 • 例如客戶今天是經理職位可能會選擇Chosun、Coex等hotel;若他身份是醫生或是律師可能會選擇Hilton。這方面顯示,以上所提到的這些hotel其實對於他們的客戶會去做適當的服務區別,例如Coex會提供小白球運動讓他的客戶可以聚在一起聊天以及一邊運動。

  40. Conclusion 4 • courtesy of employees之於客戶的觀感,可以從很多方面去做考量 • 例如待客之道、提供信用卡charge服務、或是各類運動器材與品質滿意度調查。Hilton、Hyatt、Plaza這三家服務滿意度深受客戶推崇的hotel,其實已經建立自己的忠誠客戶。

  41. Conclusion • 根據Data mining的結果發現,作者認為客戶今天的特徵可能會影響他們選擇hotel的決定,而整體性來看會比單一特徵來看具有更象徵性。 • 所以要制定成功具有競爭性的客戶回流策略,作者認為不僅要將客戶的特徵考慮進去,hotel整體的服務表現也當然需要高度的重視。

  42. 6.Critics

  43. 6.1 sample太少 • 「最適樣本數」的觀念包括以下3項: • 1、不能太少 • 2、不必太多 • 3、要有可行性 • 本篇paper作者單只做了281份問卷調查就歸納了許多rules,但是以Appendix4來看,似乎沒法交代如果今天受訪者是別的職業該在該tree中如何判定其性別。

  44. 6.2 No model Evaluation • 一個model由 training samples建立出來後,必須再用testing samples去評估這個model錯誤率,進而調整修改其model。 • 可是在本篇中,作者只單純提到自己所做的281份問卷調查中,有百分之幾的統計量support他的rule,卻沒有提到他將這套model導入真正市場運作情況如何。

  45. 6.3 Business problem  Mining Problem 有瑕疵 • 以整體獲利性來說,旅遊業雖有許多收入來自於既有的客戶,但潛在客戶亦不可忽略的。 • 本篇的Data collection時候,卻將潛在客戶忽略掉,只著重既有客戶,對於本篇作者著重在客戶的回流率策略上可能有幫助;但是對於整個大環境獲利,擬定競爭策略有待商確。

  46. Thanks for your listening…

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