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Optimizing Your Media Plan for the Bought-Owned-Earned World
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Optimizing Your Media Plan for the Bought-Owned-Earned World

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In the third installment of the Copernicus Marketing Planning 3.0 webcast series, Copernicus’ Rolf Olsen explained a critical element of marketing mix optimization: understanding how different media …

In the third installment of the Copernicus Marketing Planning 3.0 webcast series, Copernicus’ Rolf Olsen explained a critical element of marketing mix optimization: understanding how different media channels work together, build off each other, and directly or indirectly contribute to sales.

In this webcast, Rolf demonstrated how to evaluate the effects of different media on each other and apply these insights to media decisions. He offered techniques for disentangling the true impact of all bought, owned, and earned media channel and a how-to on simulating different media scenarios to forecast ROI and sales

He will use case examples to demonstrate how a deeper understanding of the synergistic performance of all channels can substantially improve your ability to do marketing mix optimization work and improve current and future media plans.

Published in: Business

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  • 1. Optimizing Your Media Plan for theBought/Owned/Earned Marketing LandscapeRolf Olsen, VP, Director of MarketingAnalyticsTuesday,June 25,20131
  • 2. WELCOME TO PART 3!2 weeks, 5 webcasts, improved marketing effectiveness2
  • 3. 3SERIES SCHEDULE1. Transformational Marketing Mix Optimization Using a Virtual MarketplaceDate: Tuesday, June 18Time: 1 pm EDTPresenter: Jeffrey Maloy, SVP and CMO2. Using a Virtual Marketplace to Evaluate Your Marketing StrategyDate: Wednesday, June 19Time: 1 PM EDTPresenter: Eric Paquette, Senior Vice President3. Optimizing Your Media Plan for the Bought-Owned-Earned Marketing LandscapeDate: Tuesday, June 25Time: 1 pm EDTPresenter: Rolf Olsen, Vice President, Director, Marketing Analytics4. Leveraging Marketing Investments with Marketing Mix ModelingDate: Wednesday, June 26Time: 1 pm EDTPresenter: Irina Pessin, Managing Partner, Data2Decisions US5. Marketing Analytics: 5 Things Every CMO Should KnowDate: Thursday, June 27Time: 1 pm EDTPresenter: Peter Krieg, President and CEO
  • 4. MY BACKGROUND Leading our new MarketingAnalyticspractice for Copernicus– 8+ year (and counting) tenure withAegis Media– Worked with clients across all majorindustry verticals– Prior to transferring from the UK, I leadand developed the Social Analyticspractice for Aegis in the UK My focus– Helping our clients navigate theincreasing complex media landscape,creating analytical solutions, whichhelp our clients maximize the impact oftheir marketing campaignsROLF OLSEN, VP, DIRECTOR OF MARKETINGANALYTICS4
  • 5. THE STARTING POINTTHE INDUSTRY HAS FRAGMENTED5
  • 6. THE NEED FOR INNOVATION IN MARKETING ANALYTICS6B/O/E = ANALYTICAL COMPLEXITY
  • 7. STARTING FROM A DIFFERENT PLACERETHINK THE OBJECTIVE7
  • 8. ACCESSING THE LANDSCAPE Agent Based Models (ABM) VECMs / VARs (Non-LinearEconometrics) Bayesian Probability Machine learning algorithms Monte Carlo simulations Neural NetsCOMPUTATIONAL MODEL TECHNIQUES8
  • 9. COMPUTATIONAL MODELINGCREATING THE RIGHT APPLICATION9
  • 10. DEVELOPING THE RIGHT FOCUSBOE• Evaluate allBought,Owned &Earnedchannels withthe samecurrencyGameTheory• How to gainmarket sharefrom thecompetitionSegments• Evaluate thecontributionfromsegments anddefine themost impactfultargetingstrategyMessaging• Identify mostefficientproduct andattributemessagestrategySimulationEngines• Test theunknown,validate plansandassumptions• Maximizemediaperformance10ADDRESSING THE KEY CHALLENGES
  • 11. ADDRESSING THE BIG MARKETING CHALLENGEEFFECTIVE B/O/E MARKETING PLANNING11
  • 12. TAKING THE EXTRA STEPITS NOT ABOUT STATIC OUTPUTS12
  • 13. CASE STUDYBRINGING THE APPROACH TO LIFE13
  • 14. ANALYSIS OBJECTIVESContribution from advertising across B/O/E for productportfolioAccount for synergistic role of media across B/O/E touchpoints (i.e.: How does TV influence Display performance?)How can we best optimize within digital to deliverincremental sales lift?Quantify the potential impact of performance optimizationsTACTICAL PAID OPTIMIZATIONS14
  • 15. 1. B/O/E NETWORK ANALYSISUNCOVERING CHANNEL SYNERGIESNon-Linear econometric models, utilizing VECMs or VARs create a structuralshift from traditional econometrics by using multiple dependants vs. just one.15
  • 16. ADDRESSING THE ROLE OF OWNED & EARNEDACCESS THE BEST DESTINATION16
  • 17. UNCOVERING THE DRIVERS OF EARNEDFUEL ECOSYSTEM PLANNING17
  • 18. 2. FLIGHTING ANALYSISOPTIMIZE THE FLIGHTING AND SYNERGYCHALLENGE•Should weleverageContinuous vs.Pulsing flightingstrategies?•How do we bestmaximize theeffectiveness ofDisplay and TV?•Can we provideinsight oneffectivenessdecay?INSIGHT•Contribution fromDisplayimpressionsindicate poorsales contributionfor both Brand X &Y•Network analysishighlights the two-way impact of TV& Display onchannelperformance•As seen with inthis category,creative/mediawear out occurswithin threemonthsACTION•Adjusting thedisplay flightingstrategy to astaggered 1-2-3burst (high to low),with a one weekbreak, willmaximize theresponse curvefunction fordisplay•Flighting strategywill also help tomaximize theperformance of acreative within thethree month cycle•Optimize displayflighting strategyto maximizesynergisticrelationshipbetween TV andDisplayIMPACT•The estimateimpact from thedisplay pulsingstrategy is$4,816,675•Direct contributionfrom DisplayImpressionsincreases from 0.3to 0.8% for bothBrand X & Y•Maximizing thisDisplay flightingstrategy with TVhas the potentialto deliverincremental salesof $17,103 forBrand X &$146,928 forBrand Y, bymaximizing theimpact for Displayduring TV flighting18
  • 19. 012345671 2 3 4 5 6 7 8 9 10 11 12 13Response CurvesObserved Response Predicted Response0123456705,00010,00015,00020,00025,00030,00035,0001 2 3 4 5 6 7 8 9 10 11 12 13Current FlightingCurrent Flighting Observed Response0.83%Contributionfrom DisplayImpressionsZero-SumDifference0.3% & 0.2%Contributionfrom DisplayImpressions05,00010,00015,00020,00025,0001 2 3 4 5 6 7 8 9 10 11 12 13Impression FlightingCurrent Flighting Proposed Flighting0123456705,00010,00015,00020,00025,00030,00035,0001 2 3 4 5 6 7 8 9 10 11 12 13Proposed FlightingProposed Flighting Predicted ResponseBrand X – 55,509 Incremental Units at a value of $2,357,562Brand Y – 46,089 Incremental Units at a value of $2,459,113FLIGHTING OPTIMIZATION IMPACT“ZERO SUM BUDGET CONSTRAINTS”19
  • 20. 3. SCENARIO PLANNER• Having completed the Networkanalysis, we now want to leveragethe model outputs within thescenario planner for testing possibleoptimization scenariosOverview• Test the impact of inter-channeloptimizations• i.e. within digital as in this case• Quantify the performance impact ofoptimizations with incremental salesAnalysis ObjectiveOPTIMIZING DISPLAY PERFORMANCE20
  • 21. SCENARIO PLANNER IN ACTIONOPTIMIZE WITHIN DISPLAYCHALLENGE• How do webest optimizewithin digitalto deliverincrementalvolume orROI?INSIGHT• The scenarioplannerfacilitates theability tooptimizeDisplayperformance,using themodeledDisplay cuts• This allows usto highlightgood andpoorlyperformingsite buckets• USH cutsindicatestrongperformanceACTION• Using the sitebucketcontributiongrid as astarting point,we created anumber ofscenariooptimizations,while notmoving morethan 10%within bucketsIMPACT• The estimateimpact fromthe proposedoptimizationsis $2,224,805• 70% Brand X• 30% Brand Y21
  • 22. “ZERO SUM” PERFORMANCE OPTIMIZATIONFLIGHTINGANALYSIS• PerformanceSummary• Brand X• 55,509 Inc Units• $2,357,562 Salescont.• Brand Y• 46,089 Inc Units• $2,459,113Salescont.DIGITALOPTIMIZATION• PerformanceSummary• Totalimpact• $2,224,805• Brand X• $1,557,363 Salescont.• Brand Y• $667,441 Salescont.TV/DISPLAYSYNERGY• PerformanceSummary• Totalimpact• $164,031• Brand X• $17,103 Salescont.• Brand Y• $146,928 Salescont.OPPORTUNITY SUMMARYTOTAL POTENTIAL OPTIMIZATION IMPACT = $7,205,51122
  • 23. THANK YOU FOR YOUR TIME TODAY!QUESTIONS?23
  • 24. For a PDF of this presentation and our advertorialon using big data for marketing planning.Email ami.bowen@copernicusmarketing.com24
  • 25. LeveragingMarketing InvestmentsWithMarketing Mix ModelingIrina Pessin, Data2Decisions USJune 26, 2013Data2DecisionsIrina PessinManaging Partner, Data2Decisions US+1 347 406 0247Irina.Pessin@d2dlimited.com
  • 26. (917) 326-7451rolf.olsen@copernicusmarketing.comgoo.gl/eydHgRolf OlsenVice President, Director, MarketingAnalytics

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