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Equifax Marketing Analytics Map For MMM & MTA

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How to take action on marketing analytics and where to start? There are many different options and dependencies. This 'map' aims to provide a basic overview of how at least Marketing Mix Modeling (MMM) and Multi-Touch Attribution (MTA) hang together and interact. Please visit https://prezi.com/view/rld4D75G0UT6EXmFHv8g/ for the original Prezi version.

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Equifax Marketing Analytics Map For MMM & MTA

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Importance of Coordinated Segmentation & Targeting Marketing Analytics Increase Return on Marketing Investment Increase Revenue & Reduce Costs Optimize Marketing Mix Promotion Optimize Media Media Mix Modeling (MMM) 1-4x Year Macro/Channel/Campaign-Level Measure Media Impact on Sales/Revenue Measure Brand Impact Justify Brand Investment Keep Brand in Consideration Set Maintain Brand Awareness >>> Protect Revenue Insert Brand into Consideration Set Increase Brand Awareness >>> Increase Revenue Aide Intent >>> Increase Revenue Measure Impact of External Factors Determine Uncontrollable Factors Reduce Waste >>> Reduce Costs Determine Controllable Factors Provide Focus for Resources Measure Seasonality Impact Determine Sub-Optimal Time Reduce Waste >>> Reduce Costs Determine Optimal Time Provide Focus for Resources Measure Halos Online to Offline e.g. Display Driving Offline Sales Offline to Online e.g. TV Driving Online Sales Channel Halos e.g. TV Driving Paid Search Campaign Halos e.g. Campaign A Driving B Sales Product Halos e.g. Product Category A Driving B Sales Measure Timing, Recency & Frequency Month/Week/Day-Part Ad Exposure Time Decay Diminishing Returns of Ad Exposure Determine Response Curves Determine Optimal Mix Compare to Current Budget Allocation Increase Spend >>> Increase Revenue Reduce Spend/Waste >>> Reduce Costs Improve Targeting Improve Response/Conversion Rates >>> Increase Revenue Targeting-Level Publisher Content State/Region/City Geo-Demographics Enable Test & Learn Program Test New Hypothesis Success Repeat >>> Increase Revenue Fail Next Hypothesis Determine Optimal Timing & Frequency Month/Week/Day-Part Frequency Controlled via Budget Forecast Sales/Revenue Manage Expectations Provide Focus for Resources Business Case for Budget Increase >>> Increase Revenue Granularity-Level Channel Channel A vs B e.g. TV vs Radio Campaign Campaign A vs B e.g. Black Friday vs Christmas Product Category Category A vs B e.g. SUV vs. German Luxury Price/Offer Offer A vs B e.g. Extras vs. Service Segment Segment A vs B e.g. Republicans vs Democrats State/Region/City Geo-Demographics Area A vs B e.g. Miami vs New York Upper Funnel: Awareness/Intent Traditional Media Paid Media Broadcast TV Targeting-Level Publisher Content State/Region/City Geo-Demographics Broadcast Radio Targeting-Level Publisher Content State/Region/City Geo-Demographics Out-of-Home Targeting-Level State/Region Cinema Targeting-Level Content State/Region/City Geo-Demographics Newspapers Targeting-Level Publisher Content Magazines Targeting-Level Publisher Content Earned Media PR Targeting-Level Publisher Word-of-Mouth Owned Media Direct Media Paid Media Mail Drop Targeting-Level ZIP Code Geo-Demographics Earned Media Digital Media Paid Media Addressable TV Targeting-Level Publisher Content Household/IP Address ZIP Code Geo-Demographics Video/Display Targeting-Level Publisher Content Context Person/Device/Cookie Household ZIP Code Geo-Demographics Behaviour PII/Custom Paid Search Generic Targeting-Level State/Region/City Keyword Paid Social Targeting-Level Publisher Content Person/Device/Cookie Household ZIP Code Geo-Demographics Behaviour PII/Custom Earned Media Organic Search Targeting-Level Keyword Referrals Social Media Word-of-Mouth Owned Media Blog Targeting-Level Keyword Social Media Profiles Targeting-Level Keyword Lower Funnel: Desire/Action Traditional Media Paid Media Earned Media Owned Media Catalogue Targeting-Level ZIP Code Geo-Demographics Point-of-Sale Targeting-Level ZIP Code Geo-Demographics Direct Media Paid Media Direct Mail Targeting-Level Person Household ZIP Code Geo-Demographics PII/Custom Outbound Calls Targeting-Level Person Household ZIP Code Geo-Demographics PII/Custom Door-to-Door Targeting-Level Person Household ZIP Code Geo-Demographics PII/Custom Email Targeting-Level Publisher Content Person/Device/Cookie Household ZIP Code Geo-Demographics Behaviour PII/Custom Earned Media Owned Media Catalogue Targeting-Level ZIP Code Geo-Demographics Email Targeting-Level Person/Device/Cookie Household ZIP Code Geo-Demographics Behaviour PII/Custom Digital Media Paid Media Paid Search Branded Targeting-Level State/Region/City Keyword Display Re-Targeting Targeting-Level Person/Device/Cookie Behaviour Affiliates Targeting-Level Publisher Content Earned Media Direct-to-Site Owned Media Mobile App Targeting-Level Content Person/Device/Cookie Household ZIP Code Geo-Demographics Behaviour PII/Custom Website Targeting-Level Content Person/Device/Cookie Household ZIP Code Geo-Demographics Behaviour PII/Custom Multi-Touch Attribution (MTA) Daily/Weekly/Monthly Micro/Person/Event-Level Measure Media Impact on Sales/Revenue Modeling Approaches All Modeling Approaches Measure Halos Channel Halos e.g. Display Driving Paid Search Campaign Halos e.g. Campaign A Driving B Sales Product Halos e.g. Product A Driving B Sales Measure Timing, Recency & Frequency Month/Week/Day-Part Ad Exposure Time Decay Diminishing Returns of Ad Exposure Determine Response Curves Determine Optimal Mix Compare to Current Budget Allocation Increase Spend >>> Increase Revenue Reduce Spend/Waste >>> Reduce Costs Improve Targeting Improve Response/Conversion Rates >>> Increase Revenue Targeting-Level Person/Device/Cookie ZIP Code Geo-Demographics PII/Custom Household/IP Address ZIP Code Geo-Demographics Behaviour State/Region/City Keyword Enable Test & Learn Program Test New Hypothesis Success Repeat >>> Increase Revenue Fail Next Hypothesis Determine Optimal Timing & Frequency Month/Week/Day-Part Frequency Caps Forecast Sales/Revenue Manage Expectations Provide Focus for Resources Business Case for Budget Increase >>> Increase Revenue Granularity-Level Channel Channel A vs B e.g. Paid Search vs Display e.g. Branded vs Generic Paid Search Strategy Strategy A vs B e.g. Display Prospecting vs Re-Targeting Campaign Campaign A vs B e.g. Black Friday vs Christmas Publisher Publisher A vs B e.g. Fox News vs CNN e.g. Publisher Overlap Content Content A vs B e.g. Immigrants vs Renewable Energy Product Category Category A vs B e.g. SUV vs. German Luxury SKU SKU A vs B e.g. F150 vs. 911 GTS Price/Offer Offer A vs B e.g. Extras vs. Service Keyword Keyword A vs B e.g. F150 vs. GTS Creative Entire Creative Creative A vs B e.g. Price vs Car Creative Elements Element A vs B e.g. Image A vs B Segment PII/Custom Person/Device/Cookie A vs B e.g. Republicans vs Democrats ZIP Code Geo-Demographics ZIP Code A vs B e.g. Jacksonville vs Manhatten Hidden Markov Modeling (HMM) Considers Order of Events Report on Funnel Stages Awareness > Intent Intent > Desire Desire > Action Addresses Ad-Viewability By Design Reduce Spend/Waste >>> Reduce Costs Addresses Ad-Fraud By Design Reduce Spend/Waste >>> Reduce Costs Predict Likelihood to Buy Improve Targeting Improve Response/Conversion Rates >>> Increase Revenue Targeting-Level Person/Device/Cookie ZIP Code Geo-Demographics PII/Custom Household/IP Address ZIP Code Geo-Demographics Customer Journey Analytics Determine Negative User Experience Eliminate Negative User Experience Reduce Drop-Off Rates Reduce Waste >>> Reduce Costs Determine Positive User Experience Promote Positive User Experience Improve Response/Conversion Rates >>> Increase Revenue Determine Next Best Action Right Message/Channel/Time Improve Response/Conversion Rates >>> Increase Revenue User Identity Management With Include More Channels Cross-Device Offline Sales In-Store Outbound Calls Addressable TV Direct Mail […] Without Include Less Channels No Cross-Device No Offline Sales No In-Store No Outbound Calls No Addressable TV No Direct Mail […] Price Optimal Price Dynamic Price […] Product Bundles Features […] Place Website Mobile App Retail Outlet Call Center […] Physical Evidence People Process Partners

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