201305 datalicious data driven media planning v1

7/28/2019 201305 Datalicious Data Driven Media Planning V1

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>MediaPlanning


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>Smartdatadrivenmarke3ng

MediaA5ribu3on&ModelingOp3misechannelmix,predictsales

Tes3ng&Op3misa3onRemovebarriers,drivesales

Boos3ngROMI

Targe3ng&MerchandisingIncreaserelevance,reducechurn

Usingdatatowidenthefunnel

May203 DataliciousPtyLtd 2


3/24

>Widerangeofdataservices

DataPlaHorms

Datacollec3onandprocessing

Adobe,GoogleAnaly3cs,etc

Webandmobileanaly3cs

Tag-lessonlinedatacapture

Retailandcallcenteranaly3cs

Bigdata&datawarehousing

Singlecustomerview

InsightsAnaly3csDataminingandmodelling

Tableau,Splunk,SPSS,R,etc

Customiseddashboards

Mediaa5ribu3onanalysis

Marke3ngmixmodelling

Socialmediamonitoring

Customersegmenta3on

Ac3onCampaignsDatausageandapplica3on

SiteCore,ExactTarget,etc

Targe3ngandmerchandising

Marke3ngautoma3on

CRMstrategyandexecu3on

Datadrivenwebsites

Tes3ngprograms



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>Bestofbreedtechnologies



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>Clientsacrossallindustries



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>Datadrivenmediaplanning

MediamixmodellingPredic1ngfuturemediaperformanceMacroinsightstoinformchannelstrategy

Mediaa-ribu1onAnalysisofhistoricmediaperformanceMicroinsightstoinformchannelop1misa1on



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>Mediamixmodelling

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>Mediamixmodelling

Predictthefuturebasedonthepast,i.e.predictsalesbasedonmediainvestmentusingamodelthatisbasedonhistoricdata

Oldschoolapproach:Regressionbased Looksatcorrela1onbetweensummarydata,i.e.mediainvestmentandtotalsalesperweek

Recommendedapproach:Agent-based Simulatesmarketcondi1onsthroughasetofconsumers(agents)andthenexposesthoseagentstodifferentmediascenariostotestthem(predictsales)beforetheyareevenimplemented



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>ThinkVineagent-basedmodelling


ThinkVineusesagentbasedmodeling(ABM)tosimulatetheac1onsof

consumersinthemarketbasedonacombina1onofinternalclientdataaswellasexternalmarketdata.Thisenablesadver1serstopredictand

testtheimpactofdifferentbudgetmixconfigura1onsbeforetheyhave

beenimplementedthusimprovingoverallmediaeffec1veness.


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>Datarequirementsandprocess


. Trainingthesystem:Dataliciousanalystsdevelopandcalibrateacustommodel

basedonagentsthatrecreatespastsales.

2. Provingthesystem:Oncethesystemistrained,wevalidateitbycomparingpredictedsalestoactualsales.

3. Usingthesystem:Oncethemodelhasbeencalibrated&validated,itcanbeusedto

predictsalesfordifferentmediascenarios

thustes1ngthembeforetheyareexecuted


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>Modellingdatarequirements

Salesdata Asgranularaspossible,i.e.byweekbystore

Mediadata Dataonthemediaac1vitythatleadtotheabovesales

Customerprofiledata Anyquan1ta1veandqualita1veinsightsonexis1ng

customersthathelpconfiguretheThinkVineagents(i.e.simulatedconsumers)

Consumerprofiledata Anyquan1ta1veandqualita1veinsightsonAustralianconsumersingeneralthathelpconfiguretheagents(i.e.simulatedconsumers)

May203 DataliciousPtyLtd


12/24

>Mediamixmodellingoutputs


Theso^wareenablesfast,objec1vecomparisonsofmarke1ngplan

alterna1ves,i.e.youcanvary

spendinglevels,1ming,mixoftac1cs

andconsumergroupstargeted.

Theso^wareenablesyourteamtoeasilyrunwhat

if?scenarios,i.e.youcan

findthebestinvestment

levelstomeetvarious

strategicandtac1calobjec1vesbypredic1ng

poten1alsalesforvarious

differentmediabudget

scenarios.


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>ThinkVinefoodservices


Inthiscasestudy,thecompanyachievedgreatermediaefficienciesandROIandalsoquan1fiedthehaloeffectofcrossbrandmarke1ng.Morespecifically,morethan$0millionofmediaspendwas

oversaturatedduetoamismatchbetweenthetargetconsumersmediaconsump1onhabitsandthe

deployedmarke1ngtac1cs.


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15/24

>Theidealmediadashboard

Channel Investment ROMI Return

BrandequityBaseline

($00) n/a $40

OfflineTV,print,outdoor,etc

$7 330% $30

DirectDirectmail,email,etc

$ 400% $5

OnlineSearch,display,social,etc

$2 110% $25



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>ROMIascompe33veadvantage


74%ofmarketersdo

notengageinany

formofmedia

a-ribu1onasidefrom

thelastclickleaving

26%ofmarketerswithaseriouscompe11ve

advantageastheir

mediainvestmentis

likelytogeneratea

muchhigherROMI.


17/24

Closer

Paidsearch

Displayadviews

TV/print

responses

>Fullpurchasepathtracking


Influencer Influencer $

Displayadclicks

Onlinesales

Affiliateclicks

Socialreferrals

Offlinesales

Organic

search

Social

buzz

Retail

visits

Life3me

profit

Organicsearch

Emails,directmail

Directsitevisits

Introducer


18/24

>Custommodelsmosteffec3ve


56%ofmarketers

considerauniqueor

custom(weighted)

mediaa-ribu1on

approachthatdoes

notuseastandardoutofthebox

methodologyas

mosteffec1ve.


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Touchpoint1

>Analy3cstopickthebestmodel


Touchpoint2

Touchpoint

TouchpointN

CloserInfluencer Influencer $Introducer

Touchpoint1

Touchpoint2

Touchpoint

TouchpointN

Touch

point1

Touch

point2

Touch

point

Touch

pointN


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>A5ribu3onmodelscompared


COSTPERCONVERSION

Lastclick

a-ribu1on

Custom(weighted)a-ribu1on


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>Mediaa5ribu3on


Aussiepurchase

pathtrackingand

mediaa-ribu1on

modellinginclose

coopera1onwith

Amnesiadesigned

toop1misethe

overallAussie

budgetmixacross

paidandearned

mediaresul1nginanoverallproject

ROIof90%.


22/24

>Mediaa5ribu3on


Suncorppurchase

pathtrackingand

mediaa-ribu1on

modellinginorder

toop1misethe

overallSuncorp

insurancebudget

mixacrosspaid

andearnedmedia

resul1nginan

overallprojectROIof2,078%.


23/24


[email protected]

Learnmore

blog.datalicious.com

Followustwi5er.com/datalicious


24/24

Smartdatadrivenmarke3ng


201305 datalicious data driven media planning v1

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