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BradFayEdKeller
RickLarkinKoenPauwels
DerivingValue
From
Conversations
AboutYourBrand
Researchshowsthatbothonlineandoff-linecustomer
conversationsdrivepurchasedecisions—buttheyrequireseparatemarketingstrategies.
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DerivingValueFromConversationsAboutYourBrand
BRADFAY,EDKELLER,RICKLARKIN,ANDKOENPAUWELS
Researchshowsthatbothonlineandoff-linecustomerconversationsdrivepurchasedecisions—buttheyrequireseparatemarketingstrategies.
Nordstrom,theSeattle-basedretailer,hadamemorable2017.InearlyFebruary,DonaldTrump,thenthenewly
electedU.S.president,tooktoTwittertoberate
NordstromfordroppingtheIvankaTrumpclothingline,complainingthatthecompanyhadtreatedhisdaughter“sounfairly…terrible!”Thetweetsetoffapowerful
reactioninsocialmedia.Ourresearchshowedthe
numberofweeklymentionsoftheNordstrombrandonTwitterandothersitessurgedby1,700%,whilethetone
ofthoseconversations(asmeasuredusingnatural-
languageprocessing,whichinterpretsmeaningfrom
adjacentwordsandcontext)swungsharplyfrompositivetonegative.
1
However,inof-lineconversations
(measuredviasurveys),thesentimentstayedpositive.Amidstthesemixedsignals,Nordstromrolledthroughthe2017holidayseasonwitha2.5%salesincreaseovertheprioryear.
Divergentconversationsaboutbrandsarefairlycommon
—andnotonlyforbrandsthatgetcaughtupin
controversies.
2
Indeed,westudiedmorethan500
leadingconsumerbrandsandfoundthatinmostcasestherewaslittlecorrelationbetweenwhatconsumerssaidaboutthebrandsonlineandwhattheysaidoff-line,eventhoughbothstreamsofconversationcanhavebigeffectsonacompany’ssales.
3
Marketershavelongrecognizedwordofmouthasa
powerfulforceaffectinghowwellproductsperform.
SincetheadventofTwitterandFacebook,somepeople
nowthinkofsocialmediaas“wordofmouthonsteroids”
—theconversationthatrepresentswhatconsumersaresaying.
4
Yetwefoundthatonlineandoff-line
conversationsmatterfordifferentreasons.
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Moststudiesonsocialmediamarketingeffectiveness
havelookedathowbrandengagementonspecific
platformssuchasFacebookorTwitter(forexample,thelikes,shares,retweets,andcomments)respondsto
marketinginitiativesasopposedtoconsideringthesocialecosystemasawhole.Thereislittleresearchlookingat
off-lineconversations—thosethatoccurface-to-faceattheofficewatercooler,overthekitchentable,orata
healthclub—becauseofthedifficultyandcostof
measuringthem.However,weaddressedthatchallengebyaskingselectedconsumerstorecalltheproductand
servicecategoriesandbrandstheytalkedabouttheday
before,includingwhetherthebrandconversationswerepositiveornegative.Weexaminedthissurveydatafor
off-lineconversationsalongwithsocialmediadataso
thatwecouldcomparethetwotypesofconversationsandidentifytrendsinboth.Wealsolookedatweeklyad
expendituresforspecificbrandsfromNumerator,an
advertisingtrackingcompany,andsalesdatatocreateacomprehensivepictureofthefactorsthatleadconsumers
tobuycertainbrands.(See“AbouttheResearch”)
AbouttheResearch
Forourresearch,wedevelopedaproprietarydata
platformtoincorporateonlineandoff-lineconversationdataon501U.S.brands.Fortheanalysispresentedhere,wecollectedonlinedatafor2015and2016andoff-linedatafor2013through2016.Onlinedatawascollected
throughkey-wordsearchesofTwitter,publicFacebookposts,blogs,forums,andconsumerreviewsites.Usingnatural-languageprocessing,weanalyzedwhetherthe
conversationswerepositiveornegative.Ourcontinuoussurveyresearchprogramyieldeddataonbrandsfromanaverageof7,000off-lineconversationsperweekwith
consumersages13to69.Respondentswereaskedto
reportonwhethertheirconversationabouteachbrand
waspositive,negative,neutral,or“mixed”O(jiān)urinitialstepwastocorrelatetheonlineandoff-linedatastreamsfor
allbrands.Wethendidaregressionanalysistolinktheonlineandoff-lineconversationstothird-partyweeklysalesdatathatweacquiredfor175brands,andtoweeklyadexpendituredataforasubsetof21ofthosebrands
usingamethodknownasmarketmixmodeling.
i
Weusedthisapproachtostudytherelationshipbetweenonlineandoff-lineconversationsin15industries,
includingelectronics,packagedfoodsandbeverages,
telecommunications,finance,andtravel.Formanyofthe500brands,wewereabletoobtainthird-partysalesdata,andwepaidparticularattentiontoasubsetof21brands—includingApple,Intel,A&W,Budweiser,Campbell’s,Lay’s,Pepsi,RedBull,andRevlon—forwhichwewerealsoabletoobtainadvertisingdata.
Ouranalysisshowsthateventhoughonlineandoff-lineconversationsbothdrivesales,theyoperate
independentlyfromeachother,sotheyneedtobe
measuredandmanagedseparately.Indeed,managers
can’trelysolelyonsocialmediatorepresenttheentiresocialecosystemthataffectsbrandsuccess.Wedescribeourfindingsingreaterdetailbelowandexplainthe
implicationsforcompanies’marketingefforts.
HowCustomer
ConversationsAffect
Sales
Knowinghowpeoplemakebrandandpurchasedecisionscanbetremendouslyvaluableforcompanies,particularlythosethatrelyheavilyonnew-customeracquisition.U.S.consumersspendapproximately$51trillioneachyearon
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allmannerofgoodsandservices,fromsoftdrinksandmobilephonestoairlineticketsandautoinsurance.
5
Giventhepotentialpayoff,companiesarealwayslookingforwaystoinfluencethosechoices—andconsumer
conversationsandrecommendationsrepresentamajoropportunity.
Overall,wefoundthatoff-lineandonlineconversationshadsimilarimpactsonsales.Forthe21brandswecloselystudied,wefoundthat9%ofpurchasedecisionscouldbetracedbacktopublicconversationsandengagementthatoccurredinsocialmedia(includingFacebook,Twitter,
Instagram,YouTube,blogs,andcustomerforums).A
slightlylargershare—10%ofsales—wasrelatedtooff-lineconversationsasmeasuredthroughourcontinuoussurveys.Thatmeanssome19%ofU.S.consumer
purchasescouldbetracedtoconsumerstalkingto
friends,relatives,colleagues,orothers(someofwhomtheyknewonlythroughsocialmedia)aboutbrands.
Yetwesawnotabledifferencesacrossproductandservicecategories.(See“WhatYou’reSellingMakesa
Difference”)Forexample,wehadassumedthat
technology-orientedofferingswouldskewmoretowardonlineconversationsthaneverydayconsumergoods,andthatproductslikefood(whichareoftenconsumedin
socialsituations)mightbehighlyinfluencedbyoff-line
conversations.However,wefoundthatsalesoftech
brandslikeAppleandIntelweredrivenmorebyoff-lineconversationsthanonline,whilesalesofgroceryandfoodbrandssuchasCampbell’stendedtobedrivenmoreby
socialmediathanbyoff-linerecommendationsfromfriends.
WhatYou’reSellingMakesaDifferenceAlthoughmanymarketersarefocusedonconsumers’
socialmediaactivity,insomecategoriesoff-line
conversationscanbeevenmoreinfluentialindrivingpurchases.
Source:EngagementLabseconometricmodelfor21leadingbrands
Thepricepointofaproductorservicewasoftenakey
factor.Higher-pricedgoodsandservicesweremoreapttobeinfluencedbyoff-lineconversations,perhapsbecausethestakeswerehigherandoff-linediscussionspermitteddeeperexplorationofabrand’sprosandconsthanonline.Significantly,though,foreveryproductcategorywe
studied,theratiobetweenonlineandoff-linewasnevermorelopsidedthan60-40ineitherdirection,meaningthatbothtypesofconversationsmatteredalot.
Whileonlineconversationsaremorevisible,off-line
conversationsaremoreplentiful.Oursurveyrevealsthattwo-thirdsofpeopletalkaboutbrandswithatleastonefriend,relative,orneighboronanygivenday,whereas
only7%post,tweet,write,orcommentaboutthe
productstheyuse.Onlineconversationstendtobeabout“socialsignaling”toone’snetwork,atermacademicsusetodescribethemotivationbehindpostsabouthightech
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andhighfashion.
6
Particularlywhenindividualsaretryingtoappealtoalargegroupoffriendsand
acquaintances,theycrafttheironlinemessagestoshowtheyareontheleadingedgeofatrend.Off-line
conversations,bycontrast,focusononepersonandare
aboutvariousproductsandservices,manyofwhicharen’t“sexy”enoughtotweetaboutormentiononFacebook.
TheMetricsThatMatter
Most
Forthebrandswestudied,themostinfluentialmetric
wasoff-lineconversationvolumeasrepresentedbythenumberofconversationspeoplehaveaboutthebrandin
aweek.Themoreface-to-faceconversationsand
recommendations,thebetteritisfordrivingabrand’s
sales.Forexample,eachAugust,Lay’srunsapromotionalcampaigncalledDoUsaFlavorinwhichconsumersareaskedtovoteonanewpotatochipflavor.Thecampaigntypicallygeneratesasurgeinoff-lineconversationsthatcontinueslongafterthecampaignends.Theactivity
drivesbrandengagementandpurchasesatthestartoftheU.S.professionalandcollegefootballseason,when
friendsandfamilywatchtelevisedgamestogetherandchipconsumptionrises.
Thesecondmostinfluentialmetricwas“onlinenet
sentimentwhichwecalculatedbysubtractingthe
percentageofnegativesocialmediaconversationsaboutthebrandfromthepercentageofpositiveones.Thiswasfollowedcloselyby“off-linenetsentimentwhichwe
calculatedsimilarly,usingdatafromourconsumer
survey.Theimportanceofthetwonetsentimentmetricssuggeststhatcompaniesshouldpaycloseattentionto
whethertheirbrandsarebeingtalkedaboutpositivelyornegatively,whetheronlineoroff-line.
Howcancompaniesmanagethesemetrics?RedBull,theenergydrinkmaker,offersagoodexample.Wefound
thatiteffectivelydrovepositiveconversationsonsocialmediabycreatinghighlyentertainingandshareable
videosofathleticachievement.Butthebrandhasbeenlesssuccessfulatproducingpositiveoff-line
conversations.Identifyingwaystoencouragemorepositiveface-to-faceconversationsmayprovidenewopportunitiesforRedBulltodrivesalesgrowth.(See“WhatHastheBiggestImpactonSales?”)
WhatHastheBiggestImpactonSales?Foroff-lineconversations,themostimportantmetricwasthevolume,orquantity,ofconversations.Foronline
conversations,sentimentmatteredmore.
Source:EngagementLabseconometricmodelfor21leadingbrands
Onlineandoff-linesentimentoftenmoveinopposite
directions.InthewakeoftheFebruary2018school
shootinginParkland,Florida,Dick’sSportingGoods,thelargesportinggoodsretailchain,tighteneditsgunsale
policiesandceasedsellingassaultweapons.Theonline
reactionwasextremelynegative—peopleconcerned
withgunrightsdenouncedthecompanyonsocialmedia.Buttheoff-linesentimentwaspositive.Infact,the
company’srevenuesrose,andthestockjumpedmore
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than20%upontheannouncementoffirst-quarterresultsin2018.Thisunderlinedtheimportanceofmonitoringbothformsofsentiment—onlineandoff-line.
7
Yetanothermetricworthtrackingistheextenttowhichthebrandisbeingtalkedaboutoff-lineby“influencers”—peoplewhoregularlygiveconsumeradvice.Brands
canleveragetheirmarketpositionbyencouraging
influencerstosharewhattheylearnaboutproductswithfriendsandfamily,expandingthereachofmarketingandthespeedofadoption.
8
Nintendoemployedthis
strategywhenittargetedandcultivated“alphamoms”tointroducetheoriginalWiigamingconsolesthroughtheirreal-worldsocialnetworks.
9
Onemetricthatdidn’tseemtohavemuchinfluence,at
leastonthesurface,was“brandcontentsharingwhichmeasuresthedegreetowhichconsumerstellustheyaretalkingaboutbrandadvertising(off-line)orhavepressedthesharebuttonforbrandcontent(online),astheydid
withRedBull’sshareablevideos.Althoughwefoundthatthemetricrankedlowinitsimmediateimpactonsales,itseffectwaslarger:Ourmodelshowedthatadvertisingexpendituresdroveconversations,which,inturn,ledtosales.Indeed,conversationsamongpeoplewhoknowandgenerallytrustoneanotheraddpersuasivepowertotheadvertisingthatsparksthoseconversations.
10
Implicationsfor
Marketing
Marketershaveknownforyearsthatcustomer
conversationsandrecommendationsarepowerfulformsofbrandengagement.
11
Buthowcancompanies
leveragethoseconversationsonbehalfoftheirbrands?
Broadlyspeaking,managersshouldlookforwaystodrivemorepositiveconversationsbothonlineandoff-line.Inmanycases,thiswillmeangoingbacktomarketing
fundamentals—rethinkingproductdesign,market
segmentation,customerservice,messaging,andchannelselection—withsocialstrategyinmind.Toaccomplishthisefficientlyandeffectively,wesuggestfoursteps.
1.Determinewhichconversationdrivershavethe
greatestpotentialforyourbusiness.Largecompanies
withanalyticsdepartmentsmaywanttobuildastatisticalmodelaswedid,tolinkconversationdatatobusiness
results.Butcompaniescanuseotherapproachestofigureoutwhichmetricstheyshouldfocuson.Forexample,youcanlearnalotfromyourcompany’sonlineconsumer
reviews,aswellasthoseofkeycompetitors.Ifthereviewsarealreadylargelypositive(forexample,4.5outof5
stars),youcantrytostimulatemoreconversationvolume—particularlythroughoff-linerecommendations.Ifyouronlinereviewsarelesspositivethanthoseofcompetitors,trytoimprovethem.Reachouttocustomerswhogave
youso-soratings,askingthemwhatyoucoulddobetter,andinvitesatisfiedcustomerstosharetheirexperiencesthroughonlinecommentsortweets.Youcanalso
conductinexpensiveonlinesurveystolearnabout
customers’off-linerecommendingbehavior(forexample,howoftentheyrecommendproductsandwhattheysay).Inaddition,itmightbeworthwhiletoexaminecall-
centerdataforthemesthatcorrelatewithcustomersatisfactionanddissatisfaction.Iftherootcausesofdissatisfactionaresubstantial,trytofixthem,andencouragethosewhoaresatisfiedtosharetheir
experienceswithothers.Manytravelandrestaurant
businessesdothisbygivingfriendlyremindersto
recommendthemtoothersrightafteragreatexperience
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orbyprovidingcustomerswithincentivesforreferrals.Companiesinotherindustrycategoriescandothesame.
2.Identifytheconsumersegmentsthataremostlikelytoenhancesalesperformance.Onceagain,thereareseveralwaystodothis.WorkingwithamajorfinancialcompanyintheUnitedKingdom,forexample,weminedlarge
databasesforinsightsandfoundthatfocusingonthe
needsofaffluentwomenandtargetingtheminmarketingwerethekeystogeneratingtheconversationsthatledtonewaccounts.Alternatively,somecompanieshavefounditusefultoconductsmall-scalesurveysofexisting
customerstoidentifywhoisrecommendingproductsorservicesmostoften,andwhy.Havingthisinformationcanhelpyoudeepenrelationshipswithinfluencers
throughevents,customercareofferings,andotherinitiativesandreachotherprospectsthroughthem.
Prioritizingcustomerswhosimplyhavelargesocial
networkscanalsobeworthwhile;theymightbeabletorecruitothercustomerstoyourbrandbothonlineandoff-line.Wehavefoundthatahighpercentageof
consumerswhocontactabrandviaitswebsite,socialmedia,orcallcentersareinfluencers.
12
3.Refineyourmessagingandstimulateconversation.
Developingshareablemarketingcontentrequires
creativityaswellasstatisticalanalysis.Oneapproachistomonitorsocialmediadiscussionsaboutyourbrandto
identifythemes,andeventhelanguageconsumersare
usingwhentalkingaboutyourproductsandthemarketingeneral,andthenconductasmallsurveytolearnhowthoseideasresonateoff-line.Thenyoucanusethemostcompellingthemesandlanguagewhendeveloping
creativemessaging.Anothermethodistofindawaytosparkaconversationthatislikelytogoviral.A2010
televisioncommercialforOldSpice,thepersonalcare
brand,providesagoodexample.Inthead,the
spokesman,afitex-NFLplayer,tellsviewersthatwhileeverymancan’tlooklikehim,theycansmelllikehim.TheadwassharedmillionsoftimesoverYouTubeandcontributedtoan11%increaseinOldSpicesales.
4.Optimizeyourconsumertouchpointstosupportyourconversationstrategy.Companiesoftenassumethatthebestavenueforincreasingconversationabouttheir
offeringsisthroughsocialmedia.Butaswehaveshown,conversationsspringfromavarietyoftouchpointsa
consumermighthavewithabrand,socompaniescandomanyotherthings.Forexample,in-storeproductdisplayscaninviteconsumerstotakeselfiestosharethroughtextmessageswithfriends.Couponscanbedesignedto
generatebonussavingsforcustomersshoppingwith
friends.Emailmarketingcampaignscanencourage
peopletoforwardmessagestofriendsorfamilymembers.Thekeyistoencouragetalkingandsharing,andtodoitthroughthevariouschannelsyoucanusetointeractwithyourconsumers.
Mostbrandsthatattempttofollowconsumer
conversationschoosetoconcentrateonsocialmedia.
However,aswehavenoted,thiscanpointyouinthe
wrongdirection.HadNordstromexecutivestakenthe
onlineconversationaboutIvankaTrump’sclothinglineasgospel,forexample,itmighthavemadedecisionsthat
wouldhavehurtsalesinsteadofboostingthem.Bothoff-lineandonlineconversationscanhaveasignificant
impactonacompany’stopline.Understandingthevaluethateachtypeofconversationmayprovide—andhow—canhelpbusinessesdevelopsmartermarketingstrategiesandmaketargetedinvestmentsthatleadtogrowth.
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AbouttheAuthors
BradFayisthechiefcommercialofficerandEdKelleristheCEOatEngagementLabs,adataand
analyticsfirminNewBrunswick,NewJersey,whereRickLarkinisvicepresidentforanalytics.KoenPauwelsisaprofessorofmarketingatNortheasternUniversity’s
D’Amore-McKimSchoolofBusinessinBoston.
References
1.C.ManningandH.Schütze,
“FoundationsofStatisticalNatural
LanguageProcessing”(Cambridge,MA:MITPress,1999).
2.B.FayandR.Larkin,“WhyOnline
Word-of-MouthMeasuresCannotPredictOfflineOutcomesJournalofAdvertisingResearch57,no.2(June2017):132-143;B.
Fay,“Dick’sSportingGoodsProvesthe‘Noise’ofSocialMediaCanGivean
IncompleteSignalJune14,2018,
.
3.J.Morrissey,“BrandsCloselyMonitorSocialMedia,butOfflineChatterIsJustas
ImportantTheNewYorkTimes,Nov.27,
2017;and“
ReturnonWordofMouth
workingpaper,WordofMouthMarketingAssociation,September2015.
4.L.Geller,“WhyWordofMouthWorks
May13,2013,
;H.
Conick,“‘WordofMouthonSteroids’:
BrandsFindSuccessinPeer
Endorsements,StudyFindsMarketingInsights,April5,2016;andA.Lane,
“
WordofMouthonSteroids—
UnderstandingtheMotivesofSharing
Content
Nov.27,2017,
.au
.
5.TradingEconomicsandU.S.BureauofEconomicAnalysis,totalforfourquartersendingJuly2018,
.
6.M.J.Lovett,R.Peres,andR.Shachar,
“OnBrandsandWordofMouthJournalofMarketingResearch50,no.4(August2013):427-444;andA.BaraschandJ.
Berger,“BroadcastingandNarrowcasting:HowAudienceSizeAffectsWhatPeople
ShareJournalofMarketingResearch51,no.3(June2014):286-299.
7.B.Fay,“Dick’sSportingGoodsProvesthe‘Noise’ofSocialMediaCanGivean
IncompleteSignalJune14,2018;andW.Duggan,“GunRestrictionsDon’tDampenDick’sStockMay30,2018,132-143,
.
8.B.Libai,E.Muller,andR.Peres,
“DecomposingtheValueofWord-of-
MouthSeedingPrograms:AccelerationVersusExpansionJournalofMarketingResearch50,no.3(April2013):161-176.
9.D.Chmielewski,“MarketingMoms:
NintendoReachesOuttoaRelatively
UntappedSegmentofPotentialUsersinanEfforttoPromoteItsNewConsole
LosAngelesTimes,Dec.25,2006;andL.Richwine,“Disney’sPowerfulMarketing
Force:SocialMediaMomsReuters,June
15,2015.
10.This“two-stepflow”isconsistentwithworkthatgoesbacktothe1950s,whenitwasdevisedbyresearchersatColumbiaUniversityandtheUniversityof
Pennsylvania.SeeP.LazarsfeldandE.
Katz,“PersonalInfluence:ThePartPlayed
byPeopleintheFlowofMass
Communications
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