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EduardoAsher,CharlesGeigner,JenniferHeth,JonathanMonjazi,ChristianSanchez
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TableofContents
Overview.....................................................................................................................................2History.........................................................................................................................................4ECommerceBusiness............................................................................................................7Phorm..........................................................................................................................................8GoogleAnalytics.................................................................................................................... 11Testimonials........................................................................................................................... 15CostcoTravel ................................................................................................................................... 15Vueling ............................................................................................................................................... 17DiscountTire ................................................................................................................................... 18AmericanCancerSociety ............................................................................................................. 19
FutureofDataMining ......................................................................................................... 20WorksCited ............................................................................................................................ 22
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OverviewThe field of E‐commerce has transformed the way companies communicate with
theiremployeesandcustomers.Whatwasonceconsideredofficesuppliessuchasa
computer has transformed into a network of interdependent devices transferring
informationfromcustomerstobusinessestomanufacturerstosupplierstobrokers
toclients.
Inordertogainandsustainacompetitiveadvantage,acompanyrequiresasimple
and easy way to deliver and access information. The E‐commerce model has
changed dramatically and in our essay we will explore the application of data
mininginthemoderne‐commercebusiness.
Datamining is part of business intelligence. Business intelligence uses computer‐
basedmethodstofindandanalyzebusinessdata,suchsalesrevenueorunitsales.
There are different aspects of business intelligence, which includes technologies
that facilitatemethodssuchasanalytics,dataminingandpredictiveanalysis.Data
mining is the process of extracting data and using statistical techniques to find
relationshipsandpatterns,whichbusinessescanusetoincreasetheirbottomline.It
has been customary for businesses to contact prospective clients through such
mediums as: standardmail, e‐mail, or call centers. Thismethod has proven to be
ratherinefficientaswellascostlytomanycompaniesduetothefactthattheylack
theproperinformationtheyneedtoassessclientneeds.
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Datamining’sbeginningisrootedinthreedifferentdisciplines.Theearliestofthese
three disciplines is classical statistics. Statistics is the main reason we have data
mining,sincestatisticsisthefoundationofthetechnologiesonwhichdataminingis
built.Instatistics,theconceptsofregressionanalysis,standarddeviation,variance,
and confidence intervals to name a few, are all used to study data and the
relationships data can represent. The second earliest discipline to influence data
mining isartificial intelligence.Artificial intelligence tries toapplyhuman thought
processestostatisticalproblems.Thethirdandfinaldisciplineismachinelearning.
Machine learning attempts to make computers “learn” about the data they are
mining by developing certain programs. These programsmake different bases on
thedifferentqualitiesrepresentedbythedata.Dataminingisbecomingincreasingly
popularinscienceandbusiness.Thesedisciplinesneedtoanalyzelargeamountsof
datasothattheymaydiscovertrendstheyotherwisecouldnotfind.
Sincethetopicofdataminingisquitelargeandintricate,theprimaryfocusofthis
paperwillbe Internetdataminingapplications. Inbusinesses,almosteverymajor
retailerintheUnitedStatesusesdatamining.Wal‐Martusesittostockitsinventory
and toanticipatecustomerneedsandAT&Tuses it to setupplans forcustomers.
Wewill show how companies such as Google and others can allow companies to
focus their energy on prospective clients increasing the likelihood in response to
salespitchesandproductmatchesonthetypesofproducttheysearch,clickon,and
buy.Dataminingcanbehelpful inmanywaysand isa toolheavilyusedbymany
Marketing departments. The information that data mining provides can also be
appliedtootherdepartmentssuchasHumanResourceswithregardstoidentifying
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prospectiveemployees thatwillprovidevalue to firms.The sophistication indata
mining applications has increased dramatically allowing companies to broadly
targetcustomerswithproductstheywouldliketobuyaswellasitemsrelatedtothe
customer’s tastes and preferences. Businesses pursue data mining, because they
expecttoreceiveareturnoninvestment.
In order to ensure the proper application of datamining, the proper predicative
models must be used. The process of applying the appropriate model is where
business acumen comes into play. We will explore how these data mining
applicationsareusedE‐commercebusinessesandhowtheyaffecttheirbottomline,
thetypesofdataminingapplicationsoffered,andempiricalexamplesofcompanies
such asDiscountTireCompany andCostco that have it in use.Keep inmind that
dataminingisanewfield,andmanycompanieshavetakendifferentapproachesin
creatingdataminingtoolsaswellasusingthem.
HistoryData mining has gone a long way since its beginnings in the late 1960's. Before
softwarewastheprimitive fileprocessingsystems, fromhierarchicalandnetwork
databasestothedevelopmentofrationaldatabasesystems,datamodelingtools,ad
indexing, and data organization techniques. The first data mining software or
packages where based on simple algorithms. With the introduction of Customer
RelationshipManagement(CRM)software,datamininggrewinpopularityanduse
among companies, especially those interested in E‐commerce (Mailvaganam). In
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addition, users have developed flexible data access through query language, user
interfaces, optimized query processing, and transaction management. (Han &
Kamber,2001)
Themainreasondatamininggainedsomuchattentionintheworldmayhavebeen
duetothevastamountofdataandtheneedtoturnthisdataintoinformationthat
can be used. The information obtained from data mining can be used for many
applications such as “business management, production control, and market
analysis,toengineeringandscienceexploration.”(Han&Kamber,2001)
Inordertounderstanddatamininganditsmotivationaldrivingforceitisimportant
to understand that data mining evolved naturally through the process of
informationtechnology.“Anevolutionarypathhasbeenwitnessedinthedatabase
industry in the development of the following functionalities: data collection and
database creation, data managemet (including data storage and retrieval, and
database trasaction processing), and data analysis and understanding (involving
datawarehousinganddatamining)”(Han&Kamber,2001).
New advances in technology in the mid‐1980s gave way to powerful database
systems.These systemsuse advanceddatamodeling such as: extended‐relational,
object‐oriented,object‐rational,anddeductivemodels;andthemostwidelyknown
global database systems such as theWoldWideWeb (WWW)whichplays a vital
roleintheinformationindustry.
Due to all these innovations in the last fewdecades, databasesbegan to establish
their architecture, For example the data warehouse is “a repository of multiple
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heterogeneous data sources, organized under a unified schema at a single site in
order to facilitate managment decision making” (Han & Kamber, 2001). Data
warehouse technology includes such systems as On‐Line Analytical Processing
(OLAP), amultidimensional tool that allows to extractmultiple sets of data from
differentpointsofview(Wikipediacontributors,2010).
Morerecentlystatisticalcollinearityhasestablishedtheimportanceofdatamining
anditsinterelationshipwithmostaspectsofbusinessmangement.Takingsubsetsof
datacouldnotdetermineadomainpatternasawhole,newdevelopmentinthefield
of human‐like decisionmodels have been employed alongside standard statistical
models creating a Choice Modeling system that experimentally mimics human
behaivior.Thissystemsallowforlargequanitiesofdataandcanresultinthousands
ofpossibleoutcomes.Sincethelate1990’sdatamininghasonseveralocasionsbeen
theobjectofbusinessandpoliticalpressureinattempttodefinestandardsfordata
miningsuchastheCrossIndustryStandardProcessforDataMining(CRISP‐DM1.0)
and more recently the 2004Java Data Miningstandard (JDM 1.0) thus creating
standard approaches that data miners could use to tackle problems that have
alreadybeensolvedbyotherusers.
Dataminingtoday isused ineveryaspectofour life, fromourmedicalrecords, to
our grocery coupons, andmail admarketing,whichwe usually throw away.Data
mininghasbecomeavitalroleineverybusinessandgovernment.Dataminingwill
continue to change through natural evolution of information technology. (Han &
Kamber,2001)
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E‐CommerceBusinessData mining in the business world has created what the Stanford University
ProfessorAndreasS.WeigendPh.D.hascalled the “SocialDataRevolution (SDR)”.
Asbusinesscontinuetheirsearch foreffectivetools theyhavebecomeengulfed in
the data mining field trying to find a way to leverage data to create innovative
productsandbusinessmodels(WeigandPh.D.,2009).
InaretailmodelforE‐business,itisimportanttounderstandthecomponentsofthe
model.There are typical browser software such asWindows InternetExploreror
GoogleChrome,aswellasadatabasethatexists intheback‐endthatsupportsthe
architectureofthefront‐enddatabase.Insomeinstancesamiddlelayer(software)
may serve to convert the architecture of different browsers so that the back‐end
databasecanunderstandthedata.
Once the user or customer inputs information into the request form about the
information he/shemaywant to purchase the information is passed through the
middle layer into theOLTP systems and records it. Once the data is storedmany
algorithmscanbeappliedtothedatatotrytodeterminetheconsumerpotentialby
structure. (A Breif History of Data Mining, 2006). The data obtained through
customerinputhelpsthecompanydeterminewhethertheirwebsiteistargetingthe
right cluster of people, or if the site design is user friendly, attractive, and
professional. The basic questions is,will the hardwork payoff? This information
canalsodeterminewhetherothermarketingstrategiesofthecompanyareresulting
ininterestintheirgoodsorservices(Markov&Larose,2007).
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AsubscriptionfeaturehasbecomecommonintheE‐businessmodel,becauseallthis
datathathasbeenminedandclusteredshouldbeeasilyaccessiblebythecompany
andalsoby the customerwhomhasmade inquires and/orpurchases in thepast.
This historical access to data makes the purpose of data mining relevant (Goel,
2006).
PhormPhormisdataminingcompanywhousestheircollecteddatatobenefitconsumers
and businesses. Phorm has offices located in “London, New York, Sao Paulo, and
Seoul (and is knownas) aDelaware,US incorporated company, publicly listed on
the London Stock Exchange’s Alternative Investment Market since 2004”
(Phorm.com).Phormofferstwodifferentplatformsfor itsdatamining.Thefirst is
known as the Open Internet Exchange (OIX) and the second is known as
PhormDiscover.
TheOpenInternetExchangeisusedforadvertisersandagencieswishingtobroaden
their reach and depth of acquiring new customers. According to the company’s
website, “the OIX connects buyers and sellers of online advertising media, with
pricesestablishedinacompetitive,auction‐basedmarketplace”.Alsoonthewebsite
isatutorialonhowtheOpenInternetExchangeactuallyworks.TheOIXworkswith
anonymous interest matching and relevant ad serving. Any website that is
participatingwithOIXwillplaceatagontheir“advertisinginventory”ofwhichads
willbeplacedtargetedforusersnotpages.Thoserelevantadswillbeauctionedoff
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and the highest bidderwill win the advertising slot, gaining a relevant, potential
new customer. In comparison to other data mining companies in the industry,
Phorm’sOpenInternetExchangedoesnotstorenorretainpersonaldata,doesnot
have the possibility of accidental ormalicious disclosure, and offers the ability to
undopreviousparticipationandopt‐outoftheprogramatanytime(Phorm.com).
Phorm’s PhormDiscover is the consumer‐based product. According to the
company’swebsite,PhormDiscoverisa“freeserviceofferedbyyourISP,whichwill
bring a personalized and safer Internet experience”. Meaning that ISPs that are
partneredwithPhormwilloffer theircustomersanopt‐in toPhormDiscoverwith
thepromiseofmorerelevantadvertisingandmorerelevantinformationregarding
that person’s interests. If opted into, PhormDiscoverwill act as a security system
warning about potential fraudulent sites aswell as protecting from phishing and
malware.
AlloverPhorm’swebsiteitbecomesevidentthatthecompanybelievesitselftobe:
innovative, privacy‐concerned, and confidential. They say that have “adopted a
privacybydesignapproach”forseveraldifferentreasons.Thefirstbeingthatthey
giveconsumersthechoicetoopt‐inandoutofthesystemattheirdiscretion.They
havegiventhesystemtheabilitytobeshutdownat theuser level. Theyarealso
said to not store: personal data, browsing history, nor IP addresses, therefore
making the users anonymous. Their concern for privacy is what makes them
innovative as well, because users are assigned random numbers. Part of their
innovationcomesfromtheirownmarketingoftheirproduct.Theirwebsiteseems
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tobeprimarilyfocusedontheconsumerinsteadoftheadvertisersorbusinesses.In
fact, their website offers no information regarding how much it would cost to
participateasanadvertisernordoes inoffertestimonials frombusinessthathave
orarecurrentlyusingPhormastheirprimarytechnologyfordatamining.
Phormhasdevelopedaninterestingrepertoirewiththepressandifonefollowsthe
progressiononPhorm in thenews itbecomesclear thatPhorm ison itsway toa
downward spiral. The progression of Phorm follows the path of anticipation,
hesitation, and finally withdrawal. In March 2008, theNew York Times wrote an
article stating the Phorm was “boasting that it will collect the most complete
informationofall”andthat“BT,CarphoneWarehouse,andVirginMediahavesigned
toworkwithPhorm”.InApril2008,theNewYorkTimeswroteanotherarticleabout
Phorm.This time theArticlewas titled, “Phorm’sAll‐SeeingParasiteCookie”. The
articleclaimsthatPhorm’scookie“couldtrackeverypageyouvisitontheInternet”
by piggybacking on other website’s cookies without permission. The anticipation
portionofPhorm’sarrivalisnotnecessarilyapositiveonefromthegetgo,butthese
articles are being written at about the same time as the article written on
MarketingCharts.com.Thisarticlestates,“threeoutoffourconsumersarewillingto
provide somemeaningful amountofpersonal information inexchange for amore
personalizedrelevantshoppingexperience”.Thisshowsthatdependingonwhowas
being talked to, their feelings towardsdataminingvaried. InMarch2009another
articlewaswrittenaboutPhorm,thistimeonSeobook.Thisarticlestatedthatthe
“behavioral ad targeting” that Phorm uses to gain information gave “commercial
incentiveforcompaniesorindividualstomisuse(theinformation)”. Also, in2009
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theNewYorkTimes yet againwrote an article regardingPhorm.This time itwas
aboutBT choosing not to “adopt Phorm” because of “budget limitations” and this
factcausedPhorm’sstockto“plunge40percent”.ThemostrecentarticleonPhorm
was that by The Register. This article was written about the Crown Prosecution
Servicedecisiontoprosecuteanyoneover“BTandPhorm’ssecretinterceptionand
profiling of Internet traffic”. Apparently BT was using Phorm’s technology on its
clientswithoutaskingpermission.Withthehotwaterthattheyareinnow,itisno
wonderwhyPhorm’s currentwebsite stresses theutmost importanceon security
andprivacyas theyseemtohavebeengetting resistanceon thatmatter fromthe
start.
GoogleAnalyticsOnedatamining application that stands out among all others isGoogleAnalytics.
Google Analytics is a unique application that allows users to gather specific data
fromtheirwebsitesandanalyzethatdatain‐depththroughmanydifferentmethods.
Google markets this process as, “Enterprise‐class web analytics made smarter,
friendlier, and free” (GoogleAnalytics, 2010). The utilization of the analyzed data
can prove to be very beneficial for E‐commerce businesses and lead to an
exponentialincreaseinonlinesales.Thequickandsimplesetup,aswellasseamless
integrationwithotherGoogleApps,demonstratesthatGoogleAnalyticsisessential
toanyE‐commercebusiness.
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The integration of Google Analytics onto a website is almost effortless. To begin
collecting vital website visitor information, a user must first go to the Google
Analyticswebsiteandcreateanaccount.Onceanaccountiscreatedtheusermust
direct the application to the desired website URL. In addition to creating the
account,apieceofJavascriptmustbeaddedintothecodeofeverysinglewebpage
thattheuserwishestocollectdatafrom.Oncetheaccountislinkedtoaspecificsite
and the script is added,Googlewill begin collecting basic information fromevery
singlewebsitevisitor.“GoogleAnalyticsissimpleenoughforbusinessesnewtoweb
analytics to get started quickly, and sophisticated enough for themost advanced
online marketers” (Harris, 2008). Initially the data gathered will range in its
usefulnessdependingonthewebsite’s traffic. If thewebsitehasa largeamountof
daily visitors the data gathered may be analyzed after only one full day. If the
website has a small amount of traffic the datamay be gathered for one to three
monthsbeforeanaccuratein‐depthanalysisiscomplete.
InvaliddataorlimiteddatamisusecanbedetrimentaltoanE‐commercebusiness.
Identicaltoanyotherformofdataanalysis,theactualdatainformationisessential
to acquiring legitimate beneficial data analysis. When considering using Google
Analytics to guide website management, users must be aware of monthly visitor
trendsanduserpreferences.Ifdataisgatheredintooshortofaperiodtoaccurately
demonstrate the random visitor variances then incorrect analysismay be carried
out. Incorrect analysis can lead towebsite layout reconstruction that can actually
hurt sales. In order to prevent these issues users must be fully aware of the
applicationtermsandformsofanalysis.
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GoogleAnalyticsallowsuserstodissectvisitordataintomanydifferentformssuch
as:returnon investment,bouncerate,clickthroughrate,andconversionrate.For
an E‐commerce business this type of data analysis is essentialwhen determining
howtoincreasesales.Thebouncerateisknownasthepercentageofvisitorswho
immediatelyleavethewebsiteuponenteringit.Itiskeytoevaluatingonlinetarget
marketing and the overall website appearance. The conversion rate is the
percentage of peoplewho complete a target goal. It is very useful in determining
howmanyvisitorsactuallymakeanonlinepurchase.Theconversionrateistherate
at which data can be used to project sales based upon the number of expected
visitors in the next month or for a defined period. A typical conversion rate can
rangefromzeropercentuptofivepercentforwell‐designedandmarketedwebsites
(GoogleAnalytics,2010).Sincetheoverallamountofpeoplewhomakepurchasesis
so small, it is essential to make sure the majority of the site visitors are your
targetedvisitors.
InadditiontoGoogleAnalytics,therearetwootherkeyapplicationsthatcangreatly
benefit an E‐commerce website: Google AdWords and Google AdSense. Google
AdWords andGoogleAdSense allowusers of GoogleAnalytics to integrate all the
collecteddata informationwithonlinemarketing tools.AdSenseadsaredisplayed
toeverysingleGooglesearchengineusereverytimetheytypeinaspecifickeyword
orphrase.UsersofGoogleAnalyticsareabletomarkettheirwebsitethroughonline
advertisementsthatonlyshowupwhenpeoplesearchfortheirspecificallydefined
keywords. Keywords are chosen by the AdWords user and can be anything from
“SanDiegoPizzeria”to“SkiBoots”.Inadditiontojustbeinganorganictrafficsearch,
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thespecifickeywordswhentypedinwilldisplayallappropriateandpre‐approved
advertisementsonthesideofthesearchengine.Whenakeywordadvertisementis
clickedonitisconsideredapay‐per‐clickadvertisementandwillcosttheownerof
the specific advertisement a varying amount of money. Every single person that
clicks on that specific advertisement will cost the owner money. The amount of
money varies depending on the popularity of the word and depending on what
othersarebiddingonforthatword.Pricescanrangefromfivecentstoovertwenty
dollarsaclickandcancosttheownersthousandsofdollarseveryday.Thetargeted
keyword advertisement data can be analyzed using the same criteria as website
visitorsandifanalyzedcorrectlyandusedproperlycansignificantlyincreaseonline
salesinashortperiodoftime.
InadditiontoAdWordsadvertisementsthatappearontheGooglesearchengine,E‐
commercemarketers can also use AdSense. Google AdSense is a tool designed to
worksimilarly toAdWords,except itdisplaysadvertisementsonactualwebpages.
AdSensewillfilterthroughallthetextdisplayedwithinawebpageandfindrelative
advertisementsbaseduponthecontentandposttheminalinkbox.Thismethodof
advertisement provides the web page owner with income generated from the
AdSense traffic andgives thewebpagevisitors advertisements that are specific to
theirwebpageinterests.AdSenseworkstheexactsamewayasAdWordswithpay‐
per‐clickadvertisementsandkeywords.
Theimpactthatdatamining,dataanalysis,andtargetmarketingcanhaveonanE‐
commerce business is phenomenal. Google Analytics and its advertising tools can
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allow a small home business grow into amedium‐sized business over just a few
weeks.Analyzingwebcontentandvisitorsgrantsathoroughunderstandingofwhat
isactuallygoingonwhenvisitorsarriveatawebsite.Evenmajorbusinesseshave
started using Google Analytics, “Google Analytics has been a key facilitator in the
transformation of PBS online. Stakeholders are no longer focused on monthly
reports. Increasingly, theyareusingAnalytics to informactualbusinessdecisions”
(Tonkin,2009).Theeraofguessingandpredictingmarkettrendsandotheraspects
of a business is now evolving into a precise science through datamining. Google
Analytics allows a business to anatomically deconstruct website visitors and
reconstructthatinformationintoeffectiveandprofitabledata.
Testimonials
CostcoTravelCostcoTravel is a subsidiaryofCostcoWholesaleCorporation.Since2000,Costco
Travelhasprovideditscustomerswith:vacationpackages,cruises,hotels,andcar
rentals. In 2008, Costco Travel launched its online booking engine, allowing their
members topurchasepackagesover the Internet.Bycreating thiswebsite,Costco
Travel will be able to expand their offerings to their customers with more
destinationsandcruisepackages.
ThechallengethatCostcoTravelfacedwasthatsellingtravelpackagesonlineisnot
assimpleasitlooks.Thecustomerhastochoosefromahugevarietyofoptionsfor
example,buyingpackagesbasedon:thetimeofyear,differenthotels,severalflights,
combinations of flight and trains with different hotels, car rentals, different
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destinations,etcetera.EachproducthasanIDforeachcombination,whichisadded
tothecustomer’sbasket,makingthecustomerconfused.“Asatravelbookingsite,
wetrackthousandsofuniquevariablesandparameterswhereusersspecifyhotels,
flights, dates, and locations” said PatMitchell, head ofWeb Analytics and Airline
PartnershipatCostcoTravel.BecauseofthisproblemCostcoTravelcreatedauser‐
friendlysystemthatreliesheavilyonAjaxcallsanddatabasemanagement.
In2008,after launchingtheirwebsite,CostcoTraveldecidedto implementGoogle
Analytics as their soleweb analytics software. After a few discussionswhether it
wasworking for them they finally decided to stickwithGoogle analytics but also
brought in Stratigient,which is a GoogleAnalytics Certified Partner, to perform a
taggingaudit.TheCostcoTravelwebsitewasdesignedtoworkwithanAjaxserver
request,whichmeantthattheURLwouldnotrefreshwhileacustomerwasutilizing
certain parts of the website. This came to play when Stratigient conducted their
audit.Theynoticedthattheyweresomeareasthatweren’tbeingtracked.Theygave
adviceonhowleverageE‐commercetaggingandeventtracking.TheCostcoTravel
teamalongwiththeStratigentteamworkedonaplantoredefinetaggingwiththe
intenttoenhancecontentreportsusingeasilyinterpretedidentifiers.
Since Costco Travel adopted Google Analytics their sales have grown over fifty
percentinvacationpackages.Theteamhasdiscoveredseveralareasofopportunity,
agreatexamplewasthe“what’snew” linkonthehomepage, theyplayedwiththe
placement and the design of it, andwhen they found the perfect spot, the results
werethatthereweremoretrafficcomingintothewebsiteandalotmoreclicks.
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VuelingVuelingAirlinesisaSpanish‐basedcompanyfoundedin2004.Themainbasesarein
MadridandbeautifulBarcelona.Thisisalow‐costairline,sowithinitsfirsteighteen
monthsofoperation,theyexperiencedahugegrowth.Becauseofthedemand,they
movedfromaround100employeestoalmost600,thefleet increasedfromtwoto
fourteenplanes,whichflewmillionsofpeople.Vuelingoffersloscostticketswitha
quality service.Theirmainsales come from theirwebsiteand the lesserextentof
salescomefromtheircallcenter.
Vueling’scontroloveradvertisingbudgetisessentialtothem,andtheyhavealways
triedtocalculateROImetrics.Eventhough,thecompanyusesmetrics,theydecided
to implement Google Analytics, a tool that “measures not only online marketing
budgetperformance,butalsoanalysesin‐depthuserbehaviorandinteractionwith
thewebsite,identifyingwaystoimproveuserexperience”saysAnnaCaceres,Online
MarketingManagerforVueling.
The conversions (or clicks onwebsite ads)were raised twenty percent only two
weeks after the installation of Google Analytics, and therewas also a ten percent
reduction in the cost of the conversions.AlsowithAdWords,Vuelingmodified its
keywords in order to attract potential customers to thewebsite. GoogleAnalytics
was able to discover that many of the company’s current customers didn’t live
where they usually flew, so with this information Vueling launched advertising
campaign inmanyof these cities. “Analytics allowsVueling tounify all sourcesof
informationandeliminateduplicityinconversionaccountancy”(casestudy).
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DiscountTireDiscountTireisacompanythatprovidesitscustomerswithawidevarietyoftires
andwheelsatalowcost.Thesetirescanbepurchasedthrougharetailstoreorthe
Internet. DiscountTireshasbeeninbusinessforoverfouryearandisthe largest
independenttiredealerinthenation.
The Internet isbecoming theirmost important sales channel, aheadof their retail
locations. Customers can interact with tires on the actual website by placing the
tiresonvehiclesandseeinghowtheyactuallylookontheircarbeforetheypurchase
them. Discount Tire uses AdWords in their website and it has been an effective
marketing tool, because it can target customer locations and send seasonal
messages.BecauseDiscount tire is a resultdriven company, theyusemetrics and
haveadepartmentthatisdedicatedtothosemetricsandanalytics.GoogleAnalytics
wasagreatacquisitionforthecompany,becausetheinstallationisverysimpleand
requiresnocustomization.
Google Analytics was able to help the company track all of their marketing
campaigns.Theywerealsoabletofollowsomepurchasingpatternsfromcustomers.
GoogleAnalyticswasable topinpointacoupleofbaddesignpatternsaswell.For
example,thecheckoutbuttonread,“Purchaseandmakeareservation”andGoogle
Analyticssuggestedchangingitto“checkoutandmakeareservation”,thischange
increase sales fourteen percent in just one week. Another problem that was not
taken into consideration was that after selecting their tires and seeing that they
wereunavailableattheirlocalstore,peoplewouldjustleavethewebsite.Whenthe
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marketing departmentwasmade aware of this problem they found a solution by
reassuringtheircustomersthatbythetimetheygettotheirstore,thetireswillbe
waitingforthem.Thissolutionresultedinanincreaseofthirty‐sixpercentinonline
sales. “Every newpiece of informationwe get fromGoogle Analytics gives us ten
newideasthatcanhelpourcustomersfindwhattheyneedonline”,TravisUnwin,
ManagingDirectoratDiscountTire.
AmericanCancerSocietyThe American Cancer Societywas founded in 1913 by fifteen physicians and one
businessman. It is a community based voluntary organization dedicated to
eliminating cancer as a health problem. The society hasmillions of volunteers all
over the country in various research, education and advocacy programs. In 2005,
605 million dollars were funded for these programs, and over 250 million for
managementandfundraising.Thesocietyisusingthewebsite“cancer.org”tohelp
thefightagainstthisterribledisease.
TheAmericanCancerSocietyreallyvaluesmetricsanddatadrivendecisionstoget
the most out of their funding. The society uses many tools to fight cancer, from
research programs to campaigns against tobacco, and even a control diet. Social
networkingwebsites,wikis,chatrooms,contentpages,andopensourceprojectsare
allpartoftheonlinepresenceofthesocietyovertheInternet.Alloftheseneedtobe
evaluatedforperformance.
GoogleAnalyticswithAdWordshadbeenabletohelpthewebsiteinmanyways.For
example,tohighlightmanykeywordsthatcanhelpthesocietygetmoredonations
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and benefits. The society was one of the first companies to use Google Analytics
whenitcameoutin2005,andhassoonastheyadopteditchangeswereseen,like
increasing their ROI (return on investment) over 600% using AdWords
performanceonTLCdirect.org.Alsothesocietybenefited,becausetheywereableto
tracethecancereducationprogramsthathelpleveragethelatesttechnologies.The
societyhasamobileversionoftheirwebsite,andwithGoogleAnalyticstheywere
abletotracethepeoplethatwentintothewebsiteanddialedtheircallcenter,that
waytheycanmonitortheeducationofcanceralloverthecountry.
FutureofDataMiningIntoday’sbusinesses,dataminingonthewebisvital. Just imaginethatthewebis
estimated to have 150million nodes (pages) and 1.7 billion edges (links). This is
aboutfourbillionpagesandwithapproximatelyonemillionaddedeveryday.It is
by far the largest,mostopen,democtraticpublishingsystemintheworld.Coulda
companyaffordnot to findaway toenhance itspublishingand takeadvantageof
thedatacollected?Thefutureofdataminingisveryprominent.Asthefieldofstudy
becomesofmoreinterest,theinformationnowcontainedsecretlywithincompany
wallswillbedevelopedandbecomeopen‐sourceforresearchers,scholars,andmid‐
sized companies to use. Thiswill create a need for far greater specialization and
morecomplexwaystoanalyzedatatodeterminethefuturebuyer.
Perhapsthefutureofdataminingdoesnotrelyonfindingyourpotentialcustomer,
butcouldshiftintoanalyzingdatatolocatethealphabuyers.Alphabuyersarethose
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people who create popularity or trends in the market of goods and services. An
alphaconsumerwill“spreadtheword”aboutaninnovativeanduniqueproduct,this
personwill likely buy the product and serve to promote your product. This new
approach to data mining can result in lower marketing costs. It will prompt a
company toseekoutwhat thesealphaconsumersareshopping foranddevelopa
product that meets that need. Once this product is developed then it can be
marketed to the alpha consumer for consumption. The result of this practicewill
resultinanexpectedboomforgood.
Dataminingcouldbeshiftingitsdatasearchintoamoreaggressiveapproach.This
could result in higher R&D costs for a company and less deficits in surplus of
products. Itcouldeffectivelydeterminewhentheirproductisreachingtheend‐of‐
businesscycleandaccuratelychangetheirproductiontoanewproduct. All inan
efforttomaximizeshareholderwealththroughtheuseofsmartinformationmining.
Thefutureholdsdataminingtolocatealphacustomerandpredictfuturetrends.
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