DATA & TARGETING 2017: CRAWL, WALK, THEN RUN

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Gartner for MarketersDATA & TARGETING2017: CRAWL, WALK,THEN RUN 2018 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. or its affiliates.For more information, email info@gartner.com or visit gartner.com. GML 409958Gartner for /marketing1

EXECUTIVE SUMMARYDigital’s promise of unified data and one-to-one marketing alwaysseems to be just out of reach for brands. There is always theperceived need for one more site relaunch, one more CRM system,or one more vendor.In reality, very few brands effectively deploy data on a consistent basis,and brands may never achieve the perfect system for storing andleveraging customer data. Even brands that are considered relativeleaders in data and targeting, like Nike, acknowledge the difficulty ofconsolidating cross-channel data to personalize marketing in newcampaigns. But brands cannot let perfect be the enemy of good.Rather than throwing money at bloated data and targeting operations,brands should focus on incrementally improving data collection anddeployment mechanisms.The third annual L2 Intelligence Report: Data & Targeting evaluatesthe longitudinal performance of 107 consumer brands across sevenverticals. Our aim is to provide data, best practices, and case studiesto help brands achieve greater return on investment.TARGETED MARKETINGReal-timepersonalization itself presents a hierarchy of risks. At the highData & Targeting: Data Capture, Personalization, and Targeted Marketing Performanceend, decisions about which offers or prices to present to which customersbased 12%on segmentationcan have legal11%andethical repercussions,STREAMLINERSLEADERSparticularly in regulated industries. Even unregulated industries must abideby antidiscrimination laws, which vary by state in the U.S. and by country.An AI algorithm can predict a surprising number of personal details —includingmembership in a legally protectedclass — from a remarkably53% LAGGARDS24% DATA MINERSlimited number of clues. Figure 3 illustrates this point with data from a2013 study that demonstrated how Facebook Likes could predict a rangeof sensitive personal attributes, including sexual orientation, race, andreligious and political views.2Key Questions What are the most valuable customer data points brands can collectacross digital touchpoints? How are brands using data, both collected and implicitly observed,across channels? Which digital channels merit brand investment in personalization? How have loyalty programs changed recent data collection andpersonalization efforts?Key Recommendations Don’t skip the basics: Customer data explicitly collected throughaccount signup forms or newsletter opt-ins is low-hanging fruit, butimplicit user behavior data gathered as customers navigate a site is apowerful asset. Brands that collect and use implicit data should notifycustomers that their information is being stored to personalize marketingcommunications. Integration is critical: A given set of customer data has a tendency tolive in the channel against which it was collected, but true data-drivenmarketing adds value when data sets from disparate channels areconsolidated. Content models must keep pace: The best data ecosystems fall flat ifunsupported by relevant, cost effective content. Technology is a means, not an end: Third-party analytics andretargeting vendors are often necessary, but over-reliance can leadto data leakage and the erosion of consumer trust. Choose partnersjudiciously and optimize your customer data sets for the bestpossible results.DATA CAPTURE & PERSONALIZATIONNovember 2017, n 107 BrandsSource: L2 Intelligence Report: Data & Targeting, December 2017Gartner for /marketing2

BRAND LISTACTIVEWEARBEAUTYSPECIALTY RETAILBIG BOX, continuedadidasAthletaL.L.Beanlululemon athleticaNew BalanceNikeOakleyPatagoniaREIThe North FaceUnder ArmourVansbareMineralsBenefit CosmeticsBobbi BrownChanelCharlotte TilburyCliniqueCoverGirlDiorEstée LauderGarnierKiehl’sL’Oréal ParisLancomeMAC ashboxTarteToo FacedUrban DecayYSL BeautyAbercrombie & FitchAeropostaleAmerican Eagle OutfittersAnn TaylorAnthropologieCrate & BarrelDesigualExpressForever 21GapGuessH&MIkeaJ. CrewPier 1 ImportsPottery BarnSephoraUltaUNIQLOUrban OutfittersVictoria’s SecretWarby ParkerWest ElmWilliams-SonomaZaraThe Home DepotLowe’sPetSmartRite vin KleinCoachDiane von FurstenbergGucciHugo BossKate SpadeLouis VuittonMarc JacobsMichael KorsPradaRalph LaurenRebecca MinkoffTommy HilfigerTory BurchGartner for MarketersTRAVELFairmont HotelsHilton Hotels & ResortsHyatt HotelsIntercontinental Hotels & ResortsMandarin OrientalMarriott Hotels & ResortsPeninsula HotelsSofitel HotelsStarwood Hotels & ResortsDEPARTMENT STORESAmazonBarneys New YorkBergdorf GoodmanBloomingdale’sKohl’sMacy’sNeiman MarcusNordstromSaks Fifth AvenueTJ MaxxBIG BOXBed Bath & BeyondBest rketing3

MethodologyDATA CAPTUREPERSONALIZATIONLOYALTY & TARGETINGThe third annual L2 IntelligenceReport: Data & Targeting evaluatesthe performance of 107 consumerbrands across seven sectors:activewear, beauty, big box,department stores, fashion,specialty retail, and travel. Themethodology includes acomprehensive review of branddesktop and mobile sites in termsof data capture, personalization,and loyalty features and capabilities.Targeted communications, such aspersonalized site content, emails,programmatic retargeting, and textmessages, were also analyzed forconsistency and effectiveness.Lastly, L2 tracked third-party tagson brand sites to identify adoptionof technology vendors.Newsletter:SignupSignup IncentiveDemographic InformationAdditional Data RequestCommunications:Email FrequencyEmail ContentFederated LoginSMS AlertsFurther CustomizationFavorite/Nearest StorePersistent CartLoyalty Program RegistrationCoalition Loyalty ProgramEmail SegmentationThird-Party TagsDisplay SpendAccount:SignupSignup IncentiveBenefits ListedEmail SubscriptionApp IntegrationPhone NumberGenderBirthdayAddress or Zip CodeHousehold InformationCheckout:Check Out as GuestPhone NumberSMS UpdatesGenderBirthdaySave Credit Card DetailsEmail PreferencesProduct Detail Pages:Personalization Product LookCross-Selling: Recent ViewsCross-Selling: Most PopularCross-Selling: Also Looked AtCross-Selling: May Also LikeGeolocation for InventoryGeolocation for ShippingTools & Services:Guided Selling ToolsSaved ResultsLive ChatCustomer Service:Email AddressPhone NumberProblem CategorizationGartner for /marketing4

E XCERPTE XCERPTE ENCEREPORTDATA2017& TARGETING 2017INTELLIGENCE REPORTDATA &TARGETINGINTELLIGENCEREPORT DATA & TARGETING 2017REPORTREPORTStreamliners collect less information than the averagebrandbutREPORTeffectivelyuse what they do collect to segment and market to consumers. These brandsare typified by efficient account signup processes and adept use of implicit,customer browsing data. However, a choice of streamlined data collectionforgoesthe possibility of more intricate segmentation.Streamliners collect less information than the average brand but effectively use what theyData & Targeting LandscapeMETHODOLOGYMETHODOLOGYMETHODOLOGYL2 developed a rubric to score brands on two axes in terms of data and targetingsophistication: data capture on brand site to achieve personalization and targetedData & DataTargetingLandscapeDataacross& TargetingLandscape& Targetingmarketingthe web.Brandswere Landscapegrouped into four archetypes: Leaders,L2developedarubrictoscorebrandsontwo Streamlinersinformationthan lessthe sophistication:Streamliners, Data Miners,and formationthanaverage usebrandbuttheyeffectively use what theyL2 developeda rubric to scoreondatatwoaxestermsof dataand targetingsophistication:collect untcapturebrandsiteto achievepersonalizationandtargetedmarketingacross s.Thesebrandsaretypifiedbyefficientaccountdata capturedataon brandsiteontoachievepersonalizationand targetedmarketingacrossthe withcustomersbut edby ationandtargetedmarketingtheweb.associations by archetype, but differentiating factors tend to include brand age,signupandprocessesandadeptuseof implicit,customerbrowsingdata.However,a choiceaofweregroupedintofour archetypes:Leaders, ands ta Miners,and pedinto four ndMiners,and Laggards.to take advantage of it by implementing an effective targeting strategy. This isdigital sophistication,andadoptionof digital ascore to growth.streamlineddatacollectionforgoes theof moreintricatesegmentation.Therewereno clearassociationsbybutarchetype,but collectionforgoesthecollectionpossibilityof possibilitymoretheintricatesegmentation.There were ferentiatingfactorsto includestreamlineddataforgoespossibilityof more intricatesegmentation.Therewereverticalno clearassociationsby archetype,but tenddifferentiatingfactorstend to ialinvestmentinsite customersbut fail taintheirinteractionswithcustomersbutfailto ptionofdigitalascoretogrowth.Data Miners collect a ton of data in their interactions withfail to takebrand effectivelyage, digital sophistication,and adoptionof digitalas coregrowth.Leaders are brands thatcollect andleveragedatabothto thatallowsthemusethatof it by implementingan effectivetargetingstrategy.Thisis usuallyindicativeof tobrandsarebrandsarethateffectivelycollect andleveragebothonandbrandsitebrandand advantageinsite and in ofadvantageit by implementinganiteffectivetargetingstrategy.Thisis usuallyindicativeareLeadersbrands ein onadvantageofby randsusually indicativeof brandsLeadersbrandsthat leverageeffectivelycollectleveragedatabothsite and Leadersin verallmadean initial investmentsitedatainvestmentharvesting,to build an infrastructurethat an infrastructure thattargeted digital marketing.Leadersadoptadvancedsite featuresthat add valueto the overallthat madeinaninitialin butsitefaileddata harvesting,but failed to buildtargeteddigitalmarketing.Leadersadopt advancedfeaturesthat add valuethatto theoverallthat add valueexperienceto the untto usethatto targetcustomersacross theweb.the web.like lowsthem allowsto use themthatdatato targetcustomersthecustomersweb.experience like guided ptions.customizationTheyoptions.also maintainallowsthemto ards dodonotnotcollectoruse usecustomerdataeffectively,missing missingantoopportunityto put to orsforprogrammaticretargeting,emailcampaignnot collector vely,opportunityputan opportunityeffective ticretargeting,emailcampaignLaggardsdo notorcollectoruse customerdataeffectivepartnershipswithvendorsfor programmaticretargeting,email Laggardscampaign alizedcontent.party management,vendors forwardand personalizedcontent. content.and site ata.forward aticsite management,performanceanalyticsto processandutilizeconsumerforwardengagingand personalizedandsite performanceanalyticstoandprocessandutilize consumerdata.and site performance analytics to process and utilize consumer data.LeadersLEADERS STREAMLINERSDATA MINERSDataMinersDATA MINERSDATAMINERS7, 2017December 7,December2017December 7, 2017Gartner for m/marketing665

E XCERPTINTELLIGENCEREPORTINTELLIGENCE REPORT DATA & TARGETING 2017DATA CAPTUREPERSONALIZATIONLOYALTYE XCERPTEMAILPunch TheMonkeyINTELLIGENCEREPORT DATA & TARGETING 2017LOYALTYpersonalized, targeted, and effective marketing, digital continuesto struggle to realize this potential. In exchange for offering upPunch The MonkeyINTELLIGENCEREPORTData & Targeting: Adoption of Ad Blockers by US Internet UsersLong proclaimedas a harbingerof a new eraPERSONALIZATIONof hyperKEY TRENDSDATA CAPTUREPunch the MonkeyCHECKLISTEMAILCHECKLIST2014–2018En Computers n SmartphonesData & Targeting: Adoption of Ad Blockers by US Internet Usersdata, customersrelevantharbingerof a deservenew eraof and personalized content bothLong proclaimed as aLong proclaimeda harbingerof athenewweb.era ofHowever,hyperin site experiencesand adsasviewedacrosshyperpersonalized, targeted,and personalized,effectivetargeted,marketing,and effectivedigitalmarketing, digital continuesdigital media is increasingly riddled with irrelevant and abrasiveto struggle to realize this potential. In exchange for offering upcontinues to struggle to realizethispotential.exchangefor to toolspromotionalcontent,such thatInconsumershave turneddata, customers deserve relevant and personalized content bothlikeadblockersthatstreamlinebrowsing.offering up data, customers deserverelevantandandin site experiencesads viewed across the web. However,75 millionUS internetusersriddleduseadirrelevantblockersin abrasivedigital mediais increasinglywithandpersonalized content both ntent,such thatconsumersturned to tools2017—slightlymore thana quarterof thetotal UShaveinternetacross the web. However,population.digital mediais increasinglyriddledlikethat streamlineTo adbe blockersclear, consumersarebrowsing.not rejecting advertisingOver 75 millionUS internetusers willuse ad blockers inwith irrelevant and abrasivepromotionalcontent,suchthatper se, just irrelevant ads: 83 percent of internetusers agree with2017—slightly more than a quarter of the total US filter out theconsumers have turned to tools likeadblockersthatpopulation. To be clear, consumers are not rejecting advertisingreally obnoxiousones,”while77percentagreewith:wish agreetherewithper se, just irrelevant ads: 83 percent of internet“Iusersstreamline browsing.112were a way Not allofadsare bad,completely.”but I want to filterout the25%Data& Targeting: Adoption of Ad Blockers by US Internet UsersINTERNET USERSUS INTERNET USUSERSKEY TRENDS2014–2018E20%n Computers n eter tactics whilepercentagreewith: “I wishthereOver 75 million US internetuserswillobnoxioususe adaones,”blockersin asSource: eMarketer data.werea way to ad-filter instead of ad-block completely.” Spray andoutirrelevantoffers.2017—slightly more than a quarterprayoftacticsthehavetotalUSinternetSource: eMarketer databecomefor brands, asclutteredconsumers tuneBrands’ only option to beheardainliabilitythis increasinglypopulation.1 To be clear, consumersare notout irrelevantoffers.rejectingData & Targeting: Share of Respondants Likely to Switch Brands Under Following Conditions landscape is to focus on providing consistent, targeted, andData & Targeting: Shareof2016,RespondantsLikely to Switch Brands Under Following Conditions Brands’ only option to be heard in this increasingly clutteredOctobern 7,037 Respondantsadvertising per se, just irrelevantads:83percentofinternetrelevant content and messaging. Fifty-two percent of consumersData & Targeting: Share of Respondants Likely to Switch Brands Under Following Conditions landscape is to focus on providing consistent, targeted, andOctober 2016, n 7,037 Respondantssay they arelikely toswitchbrandsif a branddoesnot makeanusers agree with the tcontentmessaging.Fifty-twoof doesnotmakeanwant to filter out the really obnoxious ones,” while 77 percentDIFFICULT PURCHASING74%effortinfluencesto personalizeand 65 percent say thatpersonalizationtheircommunications,loyalty to a brand.ORCHECKOUTPROCESSDIFFICULTPURCHASINGagree with: “I wish there rself-evident:loyalty to a brand.OR CHECKOUT PROCESSThe rewardsfor leaderinfluencesbrands are63 percentThe rewardsfor leaderbrandsare self-evident:63 percentad-block completely.”2 Sprayand consumerspraytacticshavebecomeof millennialagreetheyare willingto shareadatawithNO EFFORT TO52%of millennial consumers agree they are willing to share data withNO EFFORT TOPERSONALIZE COMMUNICATIONScompanies thatsendoutpersonalizedoffers offers.and discounts. Building52%liability for brands, as consumerstuneirrelevantPERSONALIZE COMMUNICATIONScompanies that send personalized offers and discounts. r customers fuels a positive feedbackexperiences for customers fuels a positive feedbackBrands’ only option to be heardthisincreasinglyclutteredloop thatinbenefitsproductmarketing,and, thereforeloop thatbenefitsinnovation,product innovation,marketing,and, thereforeDOESNOTANTICIPATEANTICIPATENEEDS50%DOES NOTNEEDSlandscape is to focus on providingconsistent,targeted, andconsumers lmakeupmorethanone-quarterofinternetusers,”1. “Ad blockersstill make uppercentmore than one-quarterof internet users,”relevant content and messaging.Fifty-twoof consumerseMarketer,eMarketer, February15, February2017. 15, 2017.50%POOREXPERIENCE2. “Why People Block Ads (And What It Means for Marketers and Advertisers),”POORMOBILEMOBILEEXPERIENCE“Why PeopleifBlockAds(AndWhatItMeansforMarketersand Advertisers),”say they are likely to switch2. brandsabranddoesnotmakeanMimi An, HubSpot Research, July 13, 2016.Mimi An, HubSpot13, 2016.3. “2016Research,State of theJulyConnectedConsumer,” Devon McGinnis, Salesforce,Source: “2016 State of the Connected Consumer,” Salesforce, October 2016.3. “2016 State ofOctobertheandConnectedDevonMcGinnis,24, 2016.effort to personalize communications,65 Consumer,”percentsaythatSalesforce,Source: “2016 State of the Connec

L2 developed a rubric to score brands on two axes in terms of data and targeting sophistication: data capture on brand site to achieve personalization and targeted marketing across the web. Brands were grouped into four archetypes: Leaders, Streamliners, Data Miners, and Laggards.

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