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Performance Marketing Ad-Fraud Decoded

mFilterIt advanced solution along with meticulous data analysis helps identify these instances and patterns are generated to isolate such inferior quality campaigns which could still be high on KPIs targetted.

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Performance Marketing Ad-Fraud Decoded

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  1. Performance Marketing Ad-Fraud Decoded Primer on Performance Marketing Ad-Fraud September 2019 India | South Asia | Middle East

  2. CONTENTS Single View of Performance Marketing Frauds .................... 1 App Ad-Frauds ..................................................................... 2 Web Ad-Frauds .................................................................... 6 Brand Safety ........................................................................ 8

  3. Single View of Performance Market Frauds Performance Marketing Brand Safety Ad Fraud App Web Incent Monitor APK Protection Search Abuse Protection Rewards Monitor App Fraud CPS Fraud Web Fraud CPS Fraud PERFORMANCEMARKETINGFRAUDS / PAGE1

  4. PerformanceMarketingAdFraud AppbasedAd-Fraud AppAd-Fraudisthesetoftechniques AppFraud usedbyfraudstersintheperformance AcquisitionFraud:Anaggressive marketingvalue-chaintofakeauser, growthbrandwouldbeinvestingover behaviouroratransaction.Thefocus 70% ofperformancemarketing inperformancemarketingisKPI budgetinacquiringnewusers.On intensive,whichopensuphuge theotherside,astablebrandwould motivationtofraudforthepartnersin stillspendaround40% ongettingnew thevaluechainwhoengageatavery users.So,irrespectiveofthestageofa transactionallevel. brand,acquisitionisabigspendfor AppAd-Fraudtakesplaceacross marketers. performancemodels,evenifa marketersetsveryhardandtangible mFilterItinternalanalysisshows35% KPIs.Atthesametime,ittraverses offraudrateonappinstallation throughthecustomerjourneyright campaigns.Fraudstersresorttoill- fromacquisitionallthroughre- practicestoachieveKPIswhich targeting. determinethepayouts.Someofthe main 'techniques' throughwhich fraudstersachievefakeinstallations include:- PERFORMANCEMARKETINGFRAUDS / PAGE2

  5. Fake Attribution Click Fraud Fake Devices A fraudulent app is used to fake the attribution of an app download, organic or inorganic. Clicks are injected after an install to capture the credit from organic as well as inorganic sources. BOTS are used to mirror human behaviour to make distinction between real users and fake users difficult. Fake / Blacklisted IPs Device Farms Incent Fraud Fake engagements through large number of devices to disguise a legitimate activity. Non-incent campaigns run over incent platforms which attracts wrong profile of users. Clicks / installs / engagements originating from suspicious IPs. mFilterItsolutiontodetectapp Thesolutionworksforanytypeof performancemarketingcampaignlike:- acquisitionfraudtracksandcomputes asetofdevice,userandenvironment CPI (CostperInstall) parametersusingproprietarymachine CPR (CostperRegistration) learningalgorithms.Thisprotects CPT (CostperTransaction) fromfakeattribution,clickspam, Event devicefarms,fakeusersandmany Retargeting suchtechniquesresortedto,by fraudsters. KEYADDITIONALRESOURCE - CASESTUDY https://www.mfilterit.com/case-studies-pdf/Ecommerce-Case-Study.pdf PERFORMANCEMARKETINGFRAUDS / PAGE3

  6. Retargetingfraudcanbetriggeredin RetargetingFraud threemainways. Thetaskofamarketerisalsotokeep anacquiredusermotivatedand OrganicPoaching:Clicksarefired chargedtobehighonengagement inthebackgroundwithout withtheplatform.Beitan customerevenbeingawareof. entertainment,shoppingorgaming Attributionplatformsregisterthese app; higherengagementonlyresults linkingwithorganicsessions. inhighratioofactiveuserswhichalso InvalidTraffic (IVT):Parallelclicks hasitsimpactonthevaluationofan aretriggeredbypartnersto appledbusiness. increasetheclickcountsinflating thepayoutsfromadvertisers. Evenagenuinelyscoutedusersmight AcquisitionPoaching:New golowonengagementasthetime acquiredusersaretargetedwho passesforvariousreasons.To aregenuinelyactive.This counterthis,marketersrunretargeting increasestheRoIforacampaign, campaignswheretheobjectiveisto justifyingclickcostcharged. induceinterestinuserstore-start usingtheapp. mFilterItadvancedsolutionalongwith meticulousdataanalysishelps Re-engagementorre-targeting identifytheseinstancesandpatterns campaignsarealsosusceptibleto aregeneratedtoisolatesuchinferior fraud.Thisisprimarilybecausethe qualitycampaignswhichcouldstillbe payoutsareclickbased. highonKPIstargetted. KEYADDITIONALRESOURCE - CASESTUDY https://www.mfilterit.com/case-studies-pdf/Retargeting-Case-Study.pdf PERFORMANCEMARKETINGFRAUDS / PAGE4

  7. Inboththecases,therearetwo CPSFraud importantindicatorsidentifyingthe Thisisacomplicatedandoneofthe fraud. mostadvancedformsofappfraud. Here,fraudstersfakeasale!This Clicktoorder:InClickSpam,theclick- lookshardtobelievehowevenasale to-orderintervalisrelativelylong.This canbefake.Butfraudsterstrigger isbecauseclickwouldhavebeen eventstotaketheirshareagainsta firedmuchaheadoftheactualorder fakesale. beingplaced.IncaseofClick Injection,it'sareversecaseasthe Therearetwotechniquesadoptedby clickwouldbefiredjustintimewhen fraudsterstodoaCPS (CostperSale) thesaleisdone. fraud.Theseare:- ClickSpam EventSequence:Hereaswellthe ClickInjection sequenceofevents - search,clickand add-to-cartwillshowunexpected ClickSpam:InthisCPSfraud,random behaviour.Forinstance,orderevent clicksarefiredtocaptureanorganic willbeplacedbeforesearchevent,or, sale.Theclicktosaletimedifference add-to-carteventwillbebeforethe ishigh.Salestakeplaceafteravery actualclick. longgapoftime. mFilterItsolutionchecksallsuch ClickInjection:Thisismoretarget logicsbymonitoringandanalysing specific.Hereafraudsterpublisher thepatternofeventstodecipherthe noticesofanappbeingusedbya fraudulenttransactions. customerandfiresclickinthe background. KEYADDITIONALRESOURCE - CASESTUDY https://www.mfilterit.com/case-studies-pdf/Snapdeal.pdf PERFORMANCEMARKETINGFRAUDS / PAGE5

  8. WebbasedAd-Fraud campaigntypes,payoutislowbut WebFraud volumesareextremelyhigh.Insuch campaigns,fraudstersfakeclicks / Thoughappbasedtransactionsand visitsandgetpaidforinvalidtraffic. activitiesareontherise,webhasnot lostitsrelevance.Forinstance,leads CPL:InCostperLeadcampaignsfake areprimarilygeneratedoverweb leadsaregeneratedeitherthrough platforms.Banking,insurance, BOTSorevensettingupmanual educationalinstitutions,hospitalsand teams.Thisinflatesthefunneland manyotherinstitutionsrelyheavilyon impactsitsquality.Atthesametimeit webapplicationstogenerateleads. increasestheoverheadslikecall centrecostwhichworksonvalidating FraudstersusingaBOToreven suchleads. manually,createmultipleleadsto inflatepayouts. mFilterItsolutionforwebfraud detectsanyIP,click,deviceandother CPC/CPV:CostperClick / Visit potentialtypesoffraudsusingover2 campaignsarerunwhereaffiliatesare dozenparametersdefinedinthe paidonthenumberofusersclicking / algorithm. visitinganadvertiserspage.Insuch KEYADDITIONALRESOURCE - CASESTUDY https://www.mfilterit.com/case-studies-pdf/Club-Mahindra.pdf PERFORMANCEMARKETINGFRAUDS / PAGE6

  9. CPSFraud WebplatformsarealsosusceptibletoCPS (CostperSale) fraud.Publishers / AffiliatesusetwopopulartechniquestoresultinCPSfraudoverweb applications. CookieStuffing:Multiplecookiesaredroppedaftersomeoneviewsapageor clicksalink.Droppingofmultiplecookiesincreasestheprobabilityofauser goingtopurchasefromoneoftheadvertisersitesbeingtargeted. Suchcookiesaredroppedthroughpop-ups,scripts,toolbars,images,and severalsimilarcarrierswhichcanencourageausertoengagewith.Through thisattributionismanipulatedandthecreditisstolenforsomeoneelse's attribution. iFrameSupport:Alsoknownaspixelstuffing,thistakesplacewhen1x1pixel (alsoknownasinvisiblepixel) isplacedonasite.Unbeknowntotheuser, thesepixelscanenduploadinganentirelydifferentwebsite.Thesitethat loadsoutofviewina1x1iFrameoftencontainsadvertisingwhichisnever seenbyauser. mFilterItintegrateswebtrackingplatformandCRMwithitssolutionthat detectsandflags-offfraudulentsales. PERFORMANCEMARKETINGFRAUDS / PAGE7

  10. BrandSafety mFilterIthasbeenafrontrunnerin APKProtection raisingBrandSafetyconcernsin performancemarketing.Alotofad- Fraudsterscreatecloneversionsof fraudissuesleadtoBrandSafety. advertisers' appsandplacethemon alternateAPKappstores.Theseare IncentMonitor kindofparallelapps. Thecampaignsmayalsoincentivisea Maliciouscodeispackagedwithsuch usertoperformanendobjective APKswiththeintentionofad-fraudas activity.However,preferenceisgiven wellasotherdatatheftandprivacy bymarketerstonon-incentcampaigns concerns.Italsohampersthe asitattractsrightfitusers. performanceofdevices. However,affiliatesrunnon-incent mFilterItscansover25suchAPK campaignsonincentplatformsto storesandconductsamicroscopic achievedesiredtargets.Thisleadsto evaluationofthecodeofsuchapp seriousBrandSafetyissues.These copies.Anyinstanceofmalwarecode includeapppromotionovertorrentor isflaggedofftotheadvertiser. pornsites. mFilterItsolutionmonitorscampaigns andreportsanyincidenceofanon- incentappappearingonover50 incentwalls / portals. PERFORMANCEMARKETINGFRAUDS / PAGE8

  11. RewardsMonitor SearchAbuseProtection Brandsoffercouponsandcash-backs InSearchEngineMarketing (SEM) torewardcustomersforusingtheir keywordcampaigns,inflatedbidding services.Thisisexploitedbyfraudster costandkeywordbiddingfraud affiliates / publishers.Theyputfakeor impactstheRoIontheorganicaswell misleadingrewardsschemesontheir asthepaidmarketinginitiativesofan ownwhichmaynotexistatallorthey advertiser. overcommitwithoutanyapproval fromtheadvertisingbrand. Advertiserspaymoreforthehigher bidontheirdesiredkeywordsas Whenauserfallspreytosuchreward biddingcostsgoupwithcompetition programmes,thereisasenseofdeceit aswellasaffiliatesbiddingtoroute andcheatingastheydonotgetwhat trafficthroughthem. waspromised.Theystartblamingthe brand,whichinrealityisnowherein Affiliatesbidhighontrademark thepicture. keywords,etc.,ofabrand,resultingin organictrafficroutingthroughthem, mFilterItrewardsmonitorconstantly whichmakesadvertiserdoublepay crawlsacross25+ suchsitesafteran forsuchtraffic. intervalof4hours.Thiscapturesany suchtallpromisecouponsandflags mFilterIttracescustomerjourney themofftotheadvertiser. originatingfromkeywordsandisable tocaptureanysuchfraud. KEYADDITIONALRESOURCE - CASESTUDY https://www.mfilterit.com/case-studies-pdf/Big-Basket-Case-Study.pdf PERFORMANCEMARKETINGFRAUDS / PAGE9

  12. ABOUTMFILTERIT mFilterIt is a global Ad-Fraud elimination and Brand Safety solutions company, providing neutral, platform agnostic fraud detection solutions for brand and performance marketing. Headquartered in Gurugram India and having offices in Noida and Mumbai, mFilterIt has its presence in Indonesia and United Arab Emirates catering to the needs of clients in these regions. With a vision of becoming world’s only comprehensive Ad-Fraud and Brand Safety solutions, mFilterIt is ramping its presence in other regions of the globe. Founded in 2015, mFilterIt has provided Ad-Fraud elimination solutions to some of the top Mobile & Web Advertisers, Mobile Handset OEMs and Telecom Operators. It’s thought leadership and advocacy around the domain is well recognised. mFilterIt is committed to further the cause of Ad-Fraud and Brand Safety and is a member of Trustworthy Accountability Group (TAG) and Mobile Marketing Association (MMA). mFilterIt solutions are developed on proprietary advanced machine learning algorithms which results in industry’s best performance in detecting and eliminating ad-fraud where users, behaviours and events are faked. mFilterIt is part of 6d Technologies, a tech enterprise catering to the telecom sector since 2002. 6d Technologies is an ISO 9001:2008 certified organisation with operations in 45+ countries across 5 continents. /COMPANY/MFILTERIT /MFILTERIT /MFILTERIT

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