1、毕业论文（设计）外文翻译APRACTICALYETMEANINGFULAPPROACHTOCUSTOMERSEGMENTATION原文INTRODUCTIONTHEREAREMANYANALYTICMETHODSFORMARKETSEGMENTATIONDEMOGRAPHICSEGMENTATIONISTHEMOSTTRADITIONALAPPROACHTOSEGMENTATIONNEWERAPPROACHESHAVEALSOTAKENINTOCONSIDERATIONBUYERATTITUDES,MOTIVATIONS,PATTERNSOFUSAGEANDPREFERENCESCOMPANI
2、ESTHATCAPTURECUSTOMERANDPURCHASEINFORMATIONUSESUCHINFORMATIONTOANALYZEANDMARKETTOTHEIRCUSTOMERBASETHISPRACTICEHASCOMETOBEKNOWNASDATABASEMARKETINGINTHEPASTDECADE,DECLININGCOSTSOFTECHNOLOGYALONGWITHADESIRETOBETTERUNDERSTANDCUSTOMERSANDTOENHANCEANDMEASUREMARKETINGEFFORTSHAVERAPIDLYEXPANDEDTHEUSEOFDATAB
3、ASEMARKETINGACROSSAVARIETYOFINDUSTRIESINDEED,ANALYSISOFCUSTOMERANDPURCHASEINFORMATIONHASBECOMETHEFOUNDATIONOFDATABASEMARKETINGPRACTICEADEEPERUNDERSTANDINGOFCUSTOMERSHASVALIDATEDTHEVALUEOFFOCUSINGONTHEMITISNOWGENERALLYACCEPTEDTHATITCOSTSABOUTFIVETIMESMORETOGAINANEWCUSTOMERTHANTOKEEPANEXISTINGONE,ANDT
4、ENTIMESMORETOGETADISSATISFIEDCUSTOMERBACKMASSNICK,1997STUDIESACROSSNUMEROUSINDUSTRIESHAVEALSOSHOWNTHATAFIVEPOINTINCREASEINCUSTOMERRETENTIONCANINCREASEPROFITSBYMORETHAN25PERCENTREICHHELD,1996WITHNUMBERSLIKETHESE,ITISNOWONDERTHATDATABASEMARKETINGISQUICKLYBECOMINGAPOWERFULTOOLFORMAINSTREAMBUSINESSESITI
5、SEXPECTEDTHATTHEOVERALLMARKETFORSOFTWAREANDSERVICESUSINGDATAMININGTECHNOLOGYWILLGROWFROMAPPROXIMATELY33BILLIONIN1996,TOMORETHAN8BILLIONBY2001METAGROUP,1997DRIVINGSUCHRAPIDGROWTHAREDATABASEMARKETINGAPPLICATIONSSUCHASCUSTOMERRETENTIONCROSSSELLINGANDUPSELLINGCAMPAIGNMANAGEMENTMARKET,CHANNEL,ANDPRICINGA
6、NALYSISANDCUSTOMERSEGMENTATIONANALYSISWHILETHEAVAILABILITYOFCUSTOMERPURCHASEINFORMATIONHASALLOWEDMARKETERSTODEVELOPRICHER,MORESOPHISTICATEDCUSTOMERSEGMENTATIONSCHEMES,SIMPLICITYHASALSOPROVENITSPLACEFORYEARS,CATALOGCOMPANIESANDOTHERDIRECTMARKETERSHAVEUSEDRFMRECENCY,FREQUENCYANDMONETARYVALUEANALYSISTO
7、SEGMENTTHEIRCUSTOMERBASEANDOPTIMIZETHEPURCHASERESPONSERATESOFTHEIRMARKETINGEFFORTSHUGHES,1994TIMEANDTIMEAGAIN,RFMHASBEENCHALLENGEDBYINNOVATIVECONCEPTUALAPPROACHESMADEPOSSIBLEBYNEWTECHNOLOGIESSUCHASNEURALNETWORKSYETDIRECTMARKETERSCONTINUETORELYONRFMBECAUSETHELIFTEXPERIENCEDUSINGALTERNATIVEMETHODSDOES
8、NOTTYPICALLYWARRANTTHECOSTSOFIMPLEMENTINGTHOSEMETHODSTHEREARECOSTSASSOCIATEDWITHINCREASEDTECHNICALCOMPLEXITY,ESPECIALLYTHATOFTAKINGTHEANALYSISAWAYFROMMARKETERSANDPUTTINGITINTOTHEHANDSOFPROGRAMMERSANDSTATISTICIANSALSOIMPORTANTARETHECOSTSOFINTERPRETATIONANDCOMMUNICATIONASMARKETERSNEEDTODEVELOPACTIONAB
9、LESTRATEGICANDTACTICALDECISIONSFROMTHERESEARCHFINDINGSTHEPURPOSEOFTHISARTICLEISTOINTRODUCEASIMPLEYETPOWERFULAPPROACHTOCUSTOMERSEGMENTATIONITISCALLEDTHECUSTOMERVALUEMATRIXITSEFFECTIVENESSLIESNOTONLYINTHATITIDENTIFIESKEYCUSTOMERSEGMENTS,BUTALSOINTHATITHIGHLIGHTSSUITABLEMARKETINGSTRATEGIESANDTACTICSINA
10、MANNERTHATCANBEREADILYCOMMUNICATEDANDEASILYIMPLEMENTEDBACKGROUNDTHECUSTOMERVALUEMATRIXWASDEVELOPEDFROMADESIRETOAPPLYRFMTOTHESMALLBUSINESSRETAILENVIRONMENTAFTERMONTHSOFWORKINGWITHSEVERALSMALLRETAILERSTRYINGTOAPPLYRFMWITHINTHEIRBUSINESSES,ITBECAMEOBVIOUSTHATRFMWASTOOCOMPLEXANDTIMECONSUMINGFORTHEMTHEPR
11、OBLEMWASTHAT,WHILERFMWASRELATIVELYSIMPLECONCEPTUALLY,THERESULTINGSEGMENTATIONWASOFTENDIFFICULTTOUNDERSTANDANDEVENMOREDIFFICULTTOPUTINTOACTIONUSINGJUSTTHREEVALUESPERVARIABLE,RFMANALYSISYIELDS27CUSTOMERSEGMENTSSEETABLEIRFMANALYSISFORRFMANALYSISTOBEACTIONABLE,THEMARKETERMUSTUNDERSTANDWHICHGROUPSCANBECO
12、MBINEDFORAPARTICULARSTRATEGYORTACTICGROUP1R250GROUP4R90180DAYS,F180DAYS,F6TIMESANDM180DAYS,F6TIMESANDM100250GROUP27R180DAYS,F6TIMESANDM250CLOSEREXAMINATIONOFTHERFMANALYSISHIGHLIGHTEDTHECOLINEARITYOFTHEFREQUENCYOFPURCHASEANDTHETOTALMONETARYVALUEVARIABLESTHATIS,ANADDITIONALPURCHASEBYAGIVENCUSTOMERRESU
13、LTSINANINCREASEINTHETOTALMONETARYVALUEOFTHATCUSTOMERGIVENTHISFINDING,CHARLESEDMUNDSONALSOAPRINCIPALATTARGETSMART1,INCSUGGESTEDUSINGAVERAGEPURCHASEAMOUNTINSTEADOFTHETOTALMONETARYVALUEOFACUSTOMERINDOINGSO,WEREMOVEDTHECOLINEARITYBETWEENTHETWOVARIABLESALSO,FORTHESAKEOFGREATERCLARITY,THEVARIABLEFREQUENCY
14、OFPURCHASEWASCHANGEDTONUMBEROFPURCHASESTHESECHANGESREPRESENTEDREFINEMENTSOVERCONVENTIONALRFMANALYSISHOWEVER,THEYDIDNOTRESOLVETHEPROBLEMOFENDINGUPWITHTOOMANYSEGMENTSTOINTERPRETANDTOWORKWITHWHATWASNEEDEDWASASIMPLIFIED,MOREPRACTICALVERSIONOFRFMVARIABLEVALUE1VALUE2VALUE3RECENCYOFPURCHASE180DAYSFREQUENCY
15、OFPURCHASE6TIMESMONETARYVALUETOTAL250NUMBEROFPURCHASESANDAVERAGEPURCHASEAMOUNTTHETHIRDVARIABLE,RECENCY,PROVIDESINTERESTINGINFORMATIONTHATCANBECOMBINEDWITHTHETWOKEYVARIABLES,BUTSOCANOTHERIMPORTANTVARIABLESSUCHASTYPEOFPURCHASEORLENGTHOFRELATIONSHIPUSINGJUSTFREQUENCYOFPURCHASEANDAVERAGEPURCHASEAMOUNTWA
16、SPARTOFTHEANSWER,THEOTHERWASSIMPLIFYINGTHESEGMENTATIONTOA22MATRIXMATRICESHAVEBEENEFFECTIVELYUSEDTOASSISTINTHEUNDERSTANDINGOFINFORMATIONFORDECISIONMAKINGPURPOSESPERHAPSTHEMOSTCOMMONLYKNOWNMATRIXISBOSTONCONSULTINGGROUPSBCGGROWTHSHAREMATRIX,WHICHFOCUSESONALLOCATIONOFRESOURCESGIVENTHEMARKETSHAREPOSITION
17、ANDGROWTHPOTENTIALOFAGIVENSETOFBUSINESSOPPORTUNITIESHENDERSON,1967PORTER,1980THEBCGGROWTHSHAREMATRIXCANBEAPPLIEDTOMARKETSEGMENTS,PRODUCTSOREVENCOUNTRIESBCGSGROWTHSHAREMATRIXSEGMENTSBUSINESSOPPORTUNITIESINTOCLEARLYDEFINEDGROUPSCASHCOWS,STARS,DOGSANDQUESTIONMARKSTHEUSEOFARELATIVELYSTRAIGHTFORWARDSCHEM
18、EANDEASYTOUNDERSTANDQUADRANTIDENTIFIERSHASMADETHEBCGMATRIXANEFFECTIVEANALYTICALTOOLTHEBCGMATRIXADDSFURTHERVALUEBYIMPLYINGWHATMANAGERIALSTRATEGIESANDTACTICSARETOBEFOLLOWEDWITHEACHBUSINESSSEGMENTBUSINESSESTHATHAVEHIGHRELATIVEMARKETSHAREINLOWGROWTHMARKETSCASHCOWSCANBEUSEDTOFUNDOTHERDEVELOPINGBUSINESSES
19、,WHILELOWRELATIVESHAREBUSINESSESINLOWGROWTHMARKETSARELIKELYTOBECASHTRAPSDOGSSIMPLIFYINGTHERFMANALYSISTOFOCUSONTHECUSTOMERVALUEBASEDVARIABLES,NUMBEROFPURCHASESANDAVERAGEPURCHASEAMOUNT,ANDUSINGA22MATRIXTOCOMMUNICATETHERESULTINGSEGMENTATIONPROVEDTOBEINSTRUMENTALINARRIVINGATAPRACTICALYETMEANINGFULAPPROA
20、CHTOCUSTOMERSEGMENTATIONMETHODOLOGYCREATIONOFACUSTOMERVALUEMATRIXREQUIRESSOMEBASICCUSTOMERANDPURCHASEINFORMATIONANDINVOLVESARELATIVELYSIMPLEMETHODOLOGYDATATHEDATANEEDEDTODEVELOPTHECUSTOMERVALUEMATRIXAREACUSTOMERIDENTIFICATIONIDNUMBER,THEDATEOFAPURCHASEANDTHETOTALAMOUNTOFTHEPURCHASETHECUSTOMERIDNUMBE
21、RISUSEDTOASSOCIATEPURCHASESWITHTHEAPPROPRIATECUSTOMERTHISCUSTOMERIDMAYCOMEFROMABUSINESSACCOUNTINGPROGRAM,POINTOFSALESYSTEMORANYOTHERMEANSTHATABUSINESSHASTOCOLLECTCUSTOMERANDPURCHASEINFORMATIONONEOFTHESMALLRETAILERSWEWORKEDWITHSTARTEDWITHTWOYEARSOFCUSTOMERINVOICESSTOREDINSHOEBOXESTHETOTALNUMBEROFPURC
22、HASESISSIMPLYACOUNTOFTHEUNIQUEDATESFORAGIVENCUSTOMERSINVOICESNOTETHATTHISMETHODELIMINATESTHEPROBLEMOFOVERCOUNTINGMULTIPLEPURCHASESINASINGLEVISITBUTMAYUNDERCOUNTMULTIPLEVISITSONTHESAMEDAYTHETOTALAMOUNTOFEACHPURCHASEISUSEDTOCALCULATETHEAVERAGEPURCHASEAMOUNTOTHERVARIABLESTHATCANBEUSEDINCONJUNCTIONWITHT
23、HECUSTOMERVALUEMATRIXMAYORMAYNOTREQUIREADDITIONALDATARECENCYCANBEDETERMINEDBYTHEDATEOFTHELASTPURCHASELIKEWISE,THELENGTHOFRELATIONSHIPCANBEDERIVEDFROMTHEFIRSTANDLASTPURCHASEDATESUSINGTHETYPEOFPURCHASEINCONJUNCTIONWITHTHECUSTOMERVALUEMATRIXREQUIRESTHECOLLECTIONOFPRODUCTTYPEDATASKU,PRODUCTCLASSORCATEGO
24、RYGEOGRAPHIC,DEMOGRAPHICOREVENCUSTOMERPREFERENCEINFORMATIONCANALSOBEUSEDINCONJUNCTIONWITHTHECUSTOMERVALUEMATRIXASLONGASSUCHDATAARECOLLECTEDONMOSTOFTHECUSTOMERSTHEAMOUNTOFHISTORICALDATATOBEUSEDWITHTHECUSTOMERVALUEMATRIXDEPENDSONTHEFREQUENCYOFPURCHASEFORANYGIVENBUSINESSARETAILORSERVICEBUSINESSWITHRELA
25、TIVELYHIGHPURCHASEFREQUENCY,SUCHASADRYCLEANER,FLORISTORTAKEOUTANDDELIVERYRESTAURANT,MAYREQUIREONLYONEYEARSWORTHOFCUSTOMERPURCHASEINFORMATIONONTHEOTHERHAND,ABUSINESSWITHRELATIVELYLOWPURCHASEFREQUENCY,SUCHASABIKESHOP,JEWELERORHIGHENDAPPARELRETAILER,MAYPREFERTWOTOFOURYEARSOFCUSTOMERPURCHASEHISTORYSEGME
26、NTATIONTHESEGMENTATIONPROCESSUSINGTHECUSTOMERVALUEMATRIXFIRSTREQUIRESTHECALCULATIONOFTHEAVERAGEVALUESFORTHENUMBEROFPURCHASESANDAVERAGEAMOUNTSPENTONCETHEAVERAGEVALUESFORTHEAXESAREDETERMINED,EACHCUSTOMERISALLOCATEDTOONEOFTHEFOURRESULTINGQUADRANTSTHEFINALSTEPISTOOBTAINQUADRANTSUMMARYLEVELINFORMATIONTHA
27、TBEGINSTOHIGHLIGHTTHEKEYDIFFERENCESBETWEENTHERESULTINGCUSTOMERSEGMENTSTHEAVERAGEVALUEFORTHEXAXIS,ORAVERAGENUMBEROFPURCHASES,ISCALCULATEDBYTAKINGTHETOTALNUMBEROFPURCHASESFORTHECUSTOMERBASEANDDIVIDINGITBYTHETOTALNUMBEROFCUSTOMERSINTHECUSTOMERBASETHEAVERAGEVALUEFORTHEYAXIS,ORAVERAGEPURCHASEAMOUNT,ISDER
28、IVEDBYTAKINGTHETOTALREVENUEANDDIVIDINGITBYTHETOTALNUMBEROFPURCHASESSEETABLEIIAVERAGEPURCHASEAMOUNTTHEAXESAVERAGESTHENSERVETOSEPARATETHEHIGHANDLOWVALUESONEACHSCALETHENEXTSTEPINTHECUSTOMERVALUEMATRIXPROCESSISTOCOMPAREEACHCUSTOMERSAVERAGENUMBEROFPURCHASESANDAVERAGEPURCHASEAMOUNTTOTHEDERIVEDAVERAGEVALUE
29、SFORTHEWHOLECUSTOMERBASEEACHCUSTOMERISTHENUNIQUELYALLOCATEDTOONEOFTHEFOURQUADRANTSBASEDONWHETHERTHEYAREABOVEORBELOWTHEAXISAVERAGESTHEDERIVEDCUSTOMERSEGMENTSARESUMMARIZEDASFOLLOWSSEEFIGURE1THECUSTOMERVALUEMATRIXSUMMARYSEGMENTINFORMATIONSUMMARYCUSTOMERANDPURCHASEINFORMATIONFOREACHOFTHEFOURQUADRANTSREV
30、EALSINSIGHTSINTOTHEDERIVEDCUSTOMERSEGMENTSEXAMINATIONOFTOTALSANDAVERAGESFOREACHCUSTOMERSEGMENTPROVIDEUSEFULMEASURESSEETABLEIIISEGMENTSUMMARYINFORMATIONDETAILEDSEGMENTINFORMATIONEARLIER,ITWASDISCUSSEDTHATTOSIMPLIFYCUSTOMERSEGMENTATION,THECUSTOMERVALUEMATRIXFOCUSEDONTHENUMBEROFPURCHASESANDTHEAVERAGEPU
31、RCHASEAMOUNTASTHEPRIMARYVARIABLES,ASTHEYBESTPORTRAYTHEVALUEOFACUSTOMERUSINGTHECUSTOMERVALUEMATRIXASTHEFOUNDATION,ANYNUMBEROFVARIABLESMAYBEOVERLAIDONTHESEGMENTATIONTOGAINGREATERDETAILWITHREGARDTOTHECUSTOMERBASEADDITIONALVARIABLESMAYBEGEOGRAPHIC,DEMOGRAPHICORPURCHASERELATED,SUCHASTHERECENCYOFAPURCHASE
32、SEETABLEIVCUSTOMERVALUEMATRIXWITHRECENCYORTHELENGTHOFTHECUSTOMERRELATIONSHIPINADDITIONTOBEINGABLETOCOMPARETHEPROPORTIONOFCUSTOMERSORDOLLARSASSOCIATEDWITHAPARTICULARVALUEFOREXAMPLE,RECENCYOFPURCHASEOF0TO3MONTHS,THESAMETYPEOFSUMMARYINFORMATIONTHATWASOBTAINEDFOREACHOFTHEQUADRANTSORKEYCUSTOMERSEGMENTSCA
33、NBEDERIVEDFOREACHVALUEWITHINEACHSEGMENTSEETABLEVSUMMARYINFORMATIONONRECENCYFORBESTCUSTOMERSANEVENDEEPERLEVELOFDRILLDOWNINFORMATIONCANBEOBTAINEDBYHOLDINGAVALUEFORAPARTICULARVARIABLECONSTANTFOREXAMPLE,CUSTOMERSWHOPURCHASEAPARTICULARBRANDOFSUITSTOTHENEXAMINETHESECUSTOMERSALONGOTHERVARIABLESSUCHASRECENC
34、YOFPURCHASEWITHINTHECONTEXTOFTHECUSTOMERVALUEMATRIXSEGMENTSITISIMPORTANTTONOTETHATWHENASPECIFICVARIABLEISSELECTED,THECUSTOMERVALUEMATRIXSTILLREFLECTSTHETOTALVALUEOFTHERELATIONSHIPWITHTHESELECTEDCUSTOMERSEVENWHENTHESELECTIONISFORAPARTICULARTYPEOFPURCHASE,THESEGMENTSORSUBSEGMENTSSTILLREFLECTTHEOVERALL
35、CUSTOMERVALUE,NOTJUSTTHATOFTHESELECTEDITEMTHEMETHODOLOGYFORTHEDEVELOPMENTOFTHECUSTOMERVALUEMATRIXDEMONSTRATESTHATARELATIVELYSIMPLEYETEFFECTIVECUSTOMERSEGMENTATIONISINDEEDPOSSIBLEFORSMALLRETAILERSWHOARETIMECONSTRAINED,THEBASICLEVELOFTHECUSTOMERVALUEMATRIXPROVIDESSUBSTANTIALVALUEBUSINESSESTHATDESIREAG
36、REATERDEPTHOFUNDERSTANDINGCANACHIEVEITBYOVERLAYINGADDITIONALVARIABLESONTOTHEBASICCUSTOMERVALUEMATRIXSEGMENTATION出处CLAUDIOMARCUSJOURNALOFCONSUMERMARKETING,VOL15NO51998PP494504二、翻译文章标题一种实用而有意义的客户细分方法译文简介市场细分有很多的分析方法。人口统计是一种最传统的细分方法。新办法还考虑到购买者的态度，动机，使用方法和偏好。公司获取和使用消费者购买信息来对客户群和市场进行细分，这种做法被称为数据库营销。在过去的十
37、年中，伴随着技术成本的下降，更好地了解客户并加强营销力度和措施的愿望使数据库营销横跨多种行业使用并迅速扩大。事实上，客户和购买信息分析成为数据库营销的实践基础。深入了解客户已经证实了集中在他们身上的价值。人们现在普遍认为获得新客户是保持一个现有的客户成本的5倍，多于十倍使不满意的顾客回来（MASSNICK，1997）。在众多行业的研究还表明，每增加五个百分点的客户保留可以增加超过百分之25（赖克尔德，1996）的利润。有了这样的数字，也难怪，数据库营销是迅速成为主流企业的有力工具。据预计，软件和服务在数据挖掘技术的市场上大约在1996年为330亿美元，增长到2001年超过80亿美元（META集
38、团，1997年）。推进如此迅速的增长是数据库营销。应用如客户保留；交叉销售和向上销售；活动管理；市场，渠道和价格分析，以及客户细分分析。虽然客户购买信息的可用性使得营销人员开发更丰富，更复杂的客户细分计划，简单的证明它的位置。多年来，目录公司和其他直销人员已经使用RFM（与上次购买时间的间隔，频率和货币价值）的分析细分他们的客户群和优化营销力度购买反应率（休斯，1994）。一次又一次，创新的概念性方法如神经网络新技术的提出使RFM遭到质疑成为可能。然而，直销人员继续依赖RFM，因为经验的提升使他们用替换方法通常无法保证实施这些方法的成本。与技术复杂性增加的相关成本，尤其是把分析远离营销人员投入
39、到程序员和统计人员的手中。同样重要的是解释和沟通的成本。作为营销人员需要从调研结果中制定可操作的战略和战术。本文的目的是介绍一个简单但功能强大的客户细分方法，这就是所谓的客户价值矩阵。其功效不仅在于它确定的主要客户群，而且还因为它强调在适当的营销策略和一种可以很容易地沟通和易于实现的战术。背景客户价值矩阵是由发达国家将RFM应用到小企业零售环境的愿望发展而成的。经过几个月试图将RFM应用到几个零售商的工作，RFM对他们来说明显太复杂和消耗时间。问题是，虽然RFM概念比较简单，但由此产生的分割往往很难理解，更难以付诸行动。仅仅使用三个变量值，RFM分析27个客户群（见表IRFM分析），对于RFM
40、分析是可行的，营销人员必须了解哪些群体可以合并为一个特定的战略或战术。第1组R为250美元第4组R为90180天，F180天，F6次和M180天，F6次和M100250美元第27组R为180天，F6次和M250美元更紧密的RFM分析检查突出了购买频率和总货币价值变量共同的线性关系。也就是说，一个由给定的顾客的额外购买行为使总货币价值增加。鉴于这一发现，查尔斯埃德蒙森（也是在TARGETSMART1，公司的首席）建议使用顾客的总货币价值代替平均购买额。这样做，我们去掉了两个变量之间的共同线性度。此外，为更清楚起见，购买频率改为购买的数量。这些变化代表了传统的RFM分析的改进，但是他们并没有解决太
41、多的细分问题，他们所需要的是一个简单，更实用的RFM的版本。购买数量和平均购买金额及第三个变量频率，提供有趣的信息，可以用两个关键因素结合起来，也可以用其他的重要变量如购买类型和关系长度。仅仅使用采购频率和平均购买金额只是答案的一部分，另一个是简化了分割为22矩阵。矩阵已被有效地用于协助以决策为目的信息理解。也许最常见的是矩阵波士顿咨询集团（BCG）的增长份额矩阵，其中考虑到市场资源分配和增长潜力商业机会（恒基兆业，1967波特，1980）的集合。波士顿增长份额矩阵可应用于细分市场，产品，甚至国家，BCG的增长份额矩阵明确定义其组成部分（现金牛，明星，瘦狗和问号）。相对简单的计划和易于理解的象
42、限标识符使波士顿矩阵成为一个有效的分析工具。波士顿矩阵通过遵照各个市场细分暗示用什么样的管理战略和战术来增加企业的价值。企业在低增长市场（现金牛）有相对高的份额可以资助发展中国家的生意，而相对份额低的企业在低增长市场有可能是现金陷阱（狗）。简化RFM分析把重点放在以客户价值为基础的变量，采购数量和平均购买金额和使用22矩阵作为客户细分工具。方法学一个客户价值矩阵的创作需要一些基本的客户信息和购买信息，包括一个相对简单的方法。数据开发一个客户价值矩阵需要的数据有客户识别码（ID），购买日期及购买的总金额。客户ID号是用来与客户联系用的。此客户ID可能来自企业的会计软件，点销售系统或任何一个企业收
43、集客户和购买信息的其他方式。总购买数量仅仅是一个给定独特日期的客户的发票计数（其中与我们合作的一个小零售商开始了两年的将消费者发票储存在柜子里），用每次购买的总金额来计算平均购买额。其他变量可以和客户价值联系在一起，矩阵可能会也可能不需要额外的数据。新进度可以由最后一次的购买日期决定，同样，这种关系的长度来源于第一次和最后一次的购买日期，购买类型和顾客价值的结合需要采购的数据，采集产品类型。历史数据量和客户价值矩阵的应用取决于任何业务的购买频率，一个购买频率相对较高的零售或服务的企业，如干洗店，花店或外卖和交付餐厅，可能只需要一年的客户购买价值的信息；另一方面，一个购买频率相对较低的业务，如自
44、行车店，珠宝或高档服装零售商，可能更喜欢二至四年的客户购买的历史。细分在分割过程中使用的客户价值矩阵，首先需要计算购买次数和消费的平均值。一旦轴线的平均值确定下了，每个消费者被分配到四个象限之一。最后一步是获得象限循简易程序级别的信息，开始突出由此产生的客户群之间的主要区别。X轴的平均值或平均购买次数，是为客户采取相应的采购总数除以客户总人数；Y轴平均值，或平均购买额的平均价值，通过采取总收入和除以它派生的采购总数，坐标轴的平均值用来区分每个规模的高值和低值。该进程在客户价值矩阵的下一步是比较每个客户的平均购买次数和平均购买金额为整个客户群的平均值得出的。然后每个客户独特的分配给四个象限之一根
45、据他们是否高于或低于平均值的轴线。衍生的客户群如下（见图1客户价值矩阵）总结细分信息在四个象限中总结消费者和购买信息，显示派生客户的见解，为总的和平奖的客户群提供有益的考试措施。详细分类资料此前，为简化客户细分进行了讨论，客户价值矩阵集中在购买次数和平均购买金额为基本变量，因为它们描绘了一个最好的客户价值。作为基金会的客户价值矩阵，任何变数可能是覆盖获得关于更详细的客户分割群。额外的变数可能是地理，人口或相关的购买，如购买（见表4客户价值矩阵新近度）近因，或者是客户关系的长度。除了能够比较特定客户或与美元相关联的价值比例（例如，0至3个月购买新近度），从每个细分的价值中总结每个象限或者主要的消
46、费群体的信息（见表5最佳客户信息概要新近度）。一个更深层次的信息可以通过持有一个特定变量的值深层挖掘得到（例如，某客户购买了特定品牌），然后检查这些客户的其他变量（如购买新近度）在客户价值矩阵分类情况。重要的是要注意，当一个特定变量被选中时，客户价值矩阵还反映了与选定的客户关系的总价值。甚至当一个特定类型的采购被选择时，分部仍然反映整体客户价值，而不仅仅是选定的项目。客户价值矩阵开发方法表明，一个相对简单而有效的客户细分的确是可能的。对于有时间限制的小零售商，基础的客户价值矩阵能够提供重大价值，有更深入理解愿望的企业可以通过增加额外的变量到客户价值细分矩阵来实现。出处克劳迪奥马库斯消费品营销硕士论文1998年5月15号第494504页
