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在過去，模具是經常被使用於工業中的器具，而近年來，模具更延用於高科技產業中。然而，模具在製造的過程中，若模具的誤差過大勢將產生產品的不良率提高，故模具精密度的高低便成為另一項產品品質的管理認知。因此，精密模具是指模具的精密度相當高，以國內模具的製造程度而言，模具企業所製造之模具已可達到二微米的誤差，壽命可達三億沖次以上。在如此高技術及高專業製作的產業領域及內外銷總值與銷售值存在著高度影響的關係中，如何能在市場上占有一席之地，將成為本研究所欲探討的方向。 　因此，在產業、廠商、經營模式等條件不同的條件下，對於經營成效的影響因子探討，則成為值得探討議題。故本研究藉由獨立性檢定、平均數檢定及RFM分析等方法的導入，研究不同經營模式、不同產業及不同廠商對S公司的經營成效的影響，茲將研究分析發現概分下列幾項： (1) 外銷經營模式受環境變遷影響較為是明顯； (2) 汽車產業之訂單多數是以外銷為主； (3) 內銷的經營成效較外銷為佳； (4) B公司與S公司之交易概況較為活絡。

本研究根據過去藥局經營文獻中，所提出之藥局經營關鍵因素進行數據實證，以了解在過去訪談或其他質化研究中所整理之藥局經營關鍵因素是否能實際影響藥局的經營狀況。 　　由研究結果，利用Y藥局之POS資料實證：具有不同特性的消費族群對Y藥局而言，具有不同的顧客價值以及消費行為，實證過去文獻所提出之結論。 　　而針對不同客群的分群方式，本研究利用購買品類的頻率及數量，將顧客做集群分析，共分出五種類型：家庭育兒族、新婚未孕族、高齡保健族、新生兒養育族及愛美小資族。整體而言愛美小資族因為購買產品之特性，有較高的顧客終生價值，且在購買行為上，以購買多樣性的表現顯著高於其他族群，但在購買頻率及近期性表現則較差，顯示出該族群有較多的可能至其他通路購買。而連鎖藥局的主要顧客，家庭育兒族，則有最低的顧客價值，在購買行為上品類較為單一，數量零碎雖購買行為頻繁，卻未能實際創造價值。 　　另外針對藥局經營關鍵因素也發現，藥局在活動促銷上，主要能促進消費者的購買頻率及縮短消費者購買的近期性，整體而言是能提升短期的消費次數，但在金額上卻未有較顯著的相關性，也顯示了金額的促銷並未能持續將顧客價值提升，僅能刺激短暫的消費行為。 　　針對未來相關研究之建議也認為，透過資料採礦，能有效將實際銷售資料轉化為消費行為的刑為變數，為未來藥局經營做更多實際數據的驗證，改善過去多使用店長經驗及質性訪談方式衡量經營成效之狀況　。 / As the concept of the Customer Relationship Management (CRM) is getting more and more popular. The analysis way of data mining used not only extrapolating data but revealing the meaning of what the customer will think and what kind of customer will be the most valuable. This research focuses on the study of utilizing the model of RFM which meaning regency, frequency and monetary. The research not only using three measures but also adding the profit of each customer to find who the most valuable one is. And establish a better way to cluster the customer then finding the best marketing strategy for them. According to understand the pareto principle of the 80/20 rule, the research combine RFM model and cluster to measure the customer value. As well as analyzing the basic information of customer and the transaction data to understand the customer’s buying behavior and provide customer suitable products and services. The result showed that, the different types of pharmacy customers have different customer value which confirming the past researches. According to the research purposes we also clustering the pharmacy customer in five types which are family, newly-married, petty budget, elder and pregnancy. And the result showed that the petty budget is the most valuable cluster in all of the pharmacy customers.

本研究主要探討藥妝零售產業提升預測顧客行為的模型與方法，並以RFM模型為基礎進行延伸。RFM模型在行銷領域中是廣泛被使用的模型，具有良好預測和分群顧客的能力，本研究在此模型中加入了兩項新指標：集中度 (C) 和 廣度 (B)，並針對顧客的「交易頻率」和「交易利潤」進行分析，藉此找出優於RFM的指標組合。首先將RFM、C、B共五項指標進行排列組合，並以迴歸分析驗證新增的兩項指標能顯著提升模型解釋能力，接著將RFM指標組合及RFMCB指標組合分別作為機器學習方法的解釋變數以預測顧客行為。對顧客交易頻率而言，C和B兩項指標的加入能顯著提升其預測能力，對顧客交易利潤而言，新指標的加入，平均而言對於預測精準度有所提升，但在部分資料中會使誤差值增加以致整體誤差的最大值有所提升。 / This research proposes modeling techniques to better predict customer behaviors in the retail industry. Extending the widely-adopted RFM model in marketing, we introduce two new metrics – clumpiness (C) and breadth (B). Using more than two million transaction records from over 100 retail pharmacy stores in Taiwan, we fit a set of regression models, in which we assess the explanatory power of different combinations of RFMCB for customer purchase frequency and profitability. Our analysis shows that the RFM model is significantly inferior to models with C and/or B, suggesting that C and B are indeed promising metrics. In the next stage, we will apply machine learning methods to incorporate C and B into predictive models and assess their out-of-sample prediction performance. On Average, RFMCB outperforms RFM in predicting Frequency & Profit. However, there are some cases where RFMCB leads to larger prediction error.

[pt] A pandemia de Covid-19 alterou o comportamento do consumidor no varejo a nível mundial. Este trabalho apresenta uma análise longitudinal do comportamento do consumidor ao longo entre 2018 e 2021, possibilitando, dessa forma, a comparação entre o comportamento do consumidor pré e pós pandemia de covid-19 em uma loja do varejo brasileiro. Para realizar essa análise, o modelo RFM é aplicado a partir de métodos de inteligência artificial para a análise de grandes volumes de dados transacionais com o objetivo de classificar os clientes de acordo com os seus comportamentos de consumo. Para o caso apresentado foram identificados 5 segmentos de consumo distintos e de grande utilidade para a gestão de CRM da empresa. / [en] The Covid-19 pandemic has changed consumer behavior in retail worldwide. This work presents a longitudinal analysis of consumer behavior between 2018 and 2021, thus making it possible to compare consumer behavior before and after the covid-19 pandemic in a Brazilian retail store. To perform this analysis, the RFM model is applied using artificial intelligence methods to analyze large volumes of transactional data in order to classify customers according to their consumption behaviors. For the case presented, 5 distinct and very useful consumer segments were identified for the company s CRM management.

Kundlojalitet är ett begrepp som aldrig tycks försvinna ur marknadsföringens ordlistor, kanske eftersom det för många företag är det ultimata marknadsföringsmålet. Den samtida konkurrensen har tack vare globalisering och digitalisering blivit hårdare än någonsin och lojalitet har aldrig varit mer relevant. Men kundlojalitet som forskningsområde är långt ifrån tydligt och enat i sina åsikter, och i det värsta fallet tycks det vara oklart vad lojalitet ens är eller om det kan skapas eller påverkas. Därmed uppfattas ett behov av att närmare undersöka hur kundlojalitet hanteras av företag inom detaljhandel via onlinekanaler, en bransch som har drabbats av en hårdare konkurrens. En kartläggning av forskning kring ämnet förtydligar att kundlojalitet som koncept har studerats, omdefinierats och kritiserats i en stor utsträckning, men att det nu finns en enad syn på kundlojalitet som ett flerdimensionellt koncept bestående av både beteende och attityd. Men detta synsätt har enligt forskning inte översatts väl till praktiken och många av de strategier som tillämpas såsom lojalitetsprogram kritiseras för att inte främja sann lojalitet. Samtidigt har mycket av den forskning som genomförts fokuserat på konsumentsidan och varför det som görs i relation till lojalitet inte fungerar. Denna masteruppsats fortsätter studien av kundlojalitetens praktiska situation genom att med intervjuer undersöka hur detaljhandelsföretag inom onlinehandel tacklar kundlojalitet för att tydligare kartlägga vad som görs och varför. Åtta intervjuer resulterade i ett flertal teman som beskriver hur kundlojaliteten uppfattas och behandlas i praktiken. Resultaten visar att de definitioner, strategier, metoder och mätetal som används inte stämmer överens med den nyare synen på lojalitet som flerdimensionell. Detta har lett till strategier som varken främjar relationer eller lojalitet och som snarare leder till minskade marginaler och uppmuntrar ett ohållbart konsumentbeteende. Resultaten lyfter även fram fem utmaningar inom det praktiska arbetet med kundlojalitet. Dessa kan härledas till ett övergripande problem som bottnar i att kundlojalitet inte behandlas som en ledningsfråga. / Customer loyalty is a term which is seemingly ubiquitous in the proverbial dictionary of marketing, perhaps because it often is considered the ultimate goal of many marketing activities. Thanks to rising globalisation and digitalisation the current competitive landscape has intensified to a point previously unheard of, which renders loyalty more important than ever before. But, as a field of research customer loyalty is quite split in terms of how loyalty should be defined, and it seems uncertain if loyalty even should be seen as something which can be created. With all this uncertainty in mind there would appear to be a need to more closely examine how Customer Loyalty is actively handled by businesses, using the Swedish e-retail market as a point of reference. A mapping of research on the subject clarifies that customer loyalty as a concept has been studied, redefined and criticized to a great extent, but that there now is a unified view of customer loyalty as a multi-dimensional concept consisting of both behaviour and attitude. However, according to research, this approach has not been translated well into practice, a lot of the strategies applied within loyalty programs has been criticized for not encouraging true loyalty. At the same time, much of the research that has been carried out has focused on the consumer perspective and why the loyalty efforts do not work. This master thesis elaborates on the study of the practicals of customer loyalty by conducting interviews with laypeople to determine how Swedish business within online retail deal with the challenge of maintaining loyalty. A total of eight interviews yielded many themes which thoroughly describe how customer loyalty is viewed, defined, measured and dealt with in practice. Our results show that the definitions, strategies, methods and measurements currently used within the field of loyalty management are not up to snuff when compared with the views of academic research, which define customer loyalty as a multidimensional construct. This has lead to strategies which neither favour loyalty nor relationships but rather result in lessening margins while encouraging unsustainable consumer behaviour. The results also highlight five distinct challenges within the practice of loyalty management. These can largely be contributed to the fact that customer loyalty rarely is given the level of attention on a leadership level that it should warrant.

化妝品產業發展相當蓬勃，全球市場每年的成長快速，消費者對化妝品需求也越來越廣，加上環保意識抬頭，追求效果同時也希望帶給生態以及地球正面的效益；而消費者在眾多商品之中不僅只是選擇有效的產品，產品本身的訴求更要符合消費者的期待。近年科技進步神速，資料庫的儲存容量越來越大，利用資料探勘技術於事業拓展，將這些知識轉化為業務決策的工具，實現商業價值即所謂的商業智慧，不僅能降低營運成本，更能提供企業的有意義的資訊。 本研究的顧客資料來源為B公司近一年的會員消費紀錄，研究目的如下： 一、對顧客交易資料進行資料探索分析，了解銷售資料本身的基本特質。 二、根據B公司會員之銷售資料進行計算，變數包含銷售日期、銷售數量、銷售金額以及銷售地點等，使用資料探勘找出潛在忠誠顧客。 三、根據忠誠顧客的銷售資料，使用關聯分析方法，歸納忠誠顧客的消費行為與規則，並依照此規則為該族群量身打造銷售策略，有利於未來的業績成長，加強企業與顧客之間的交流。 研究結果發現：銷售狀況受季節性因素影響，建議依照季節變化推出相關商品，吸引會員消費；茶樹系列和白麝香氛系列為B公司之主要熱銷商品，而VIP與Bonus兩種會員身份的的消費方式存在明顯差異，根據RFM分析結果找出價值客戶，並區分為兩種，第一種為忠誠客戶，建議和忠誠客戶維持緊密關係，並持續追蹤忠誠客戶的消費行為；第二種為機會客戶，其和忠誠客戶存在明顯差異，對於茶樹系列商品相當支持，購買比例甚至高於忠誠顧客，且喜好的產品系列集中在茶樹系列以及FIT緊實系列，同時購買同系列產品的比例明顯高於忠誠顧客，建議積極經營機會客戶，量身打造銷售策略。

傳統服飾零售行業大多是小批量，款式豐富，銷售週期短，而且積壓產品不易處理。同時隨著互聯網的高速發展，以往的銷售經驗可能不再適用，造成實體店面成交次數少，加上店鋪租金、人工等成本反而是逐年遞增，雙重衝擊下實體店面生存困難。因此注重客戶關係管理和維護目前黃金銷售通路。所以，無論是通路通路或是不同類型客戶的服飾的交易成效是值得深入探討的課題。 本研究將通過個案公司所提供之顧客購買資料，其中購買資料包含銷貨時間、客戶簡稱、銷貨單號、產品代號、出貨數量、出貨單價、出貨總額等資料，據以透過RFM分析及平均數檢定等方法的應用，分析零售服飾之交易的重要通路銷售管道及識別優質客戶，其研究發現概述如下： 一、 電商通路服飾交易次數約有百分之六十七的比例； 二、 實體通路服飾交易次數未達總交易次數的1%； 三、 團服通路的平均單次交易金額較其餘通路多出逾近萬元； 四、 大型客戶的經營成效最佳； 五、 服飾交易額度較為高之客戶； 六、 服飾交易頻繁度較活絡之客戶； 七、 團服、電商經營成效佳。

Understanding of how to manage relationships with customers has become an important topic for both academic and practitioners in recent years. The effectiveness of business can be greatly improved by identifying the drivers of the most profitable customers and using them to target the right customers. In this study we identify exchange characteristics such as amount of money spent per purchase, customer relationship duration with firm, ratio of cross-buying and demographic characteristics such as age and gender as important drivers of the most profitable customers. The results of the study have important implications for academicians in understanding what drives the most profitable customers in noncotractual settings as well as practitioners to help design more effective marketing strategies. Moreover, the results of knowledge discovery about customers by different data mining techniques also contribute to help researchers identifying feasibility of these methods. Powered by TCPDF (www.tcpdf.org)