Managing digital media through Multi-touch Attribution - The Digital Benchmark - Berlin 2019

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Managing digital media through Multi-touch Attribution Chapter produced in collaboration with

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Conference

11:50 AM - 12:30 PM

Managing digital media through Multi-touch Attribution GUILHEM BODIN

enior Manager expert Media Converteo

SABINE DE COURCY

SIRISACK VIENGSAVANH

MATTHIEU BRET

Acquisition & Digital Trafic Manager Canal Plus

Data Media and Tools Manager

Head of Data and Omnichannel Analytics

BNP Paribas

Orange France

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GENERAL OVERVIEW

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WHAT IS ATTRIBUTION?

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What is Multi-touch Attribution ?

SABINE DE COURCY Responsible e-marketing

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What are the Multi-touch models ? Who are the market players ?

CANAL +

MATTHIEU BRET Head of Data and Omnichannel Analytics ORANGE

GUILHEM BODIN 5

How can attribution be used in 2019 ?

Senior Manager CONVERTEO

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INTRODUCTION TO Multi-touch Attribution

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WHAT IS ATTRIBUTION?

Attribution allows to reconcile adcentric and site-centric data by comparing data related to ad exposure and the action resulting from it. It mainly aims at improving reporting, analysis and budget optimization.

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WHAT IS MULTI-TOUCH ATTRIBUTION? Multi-touch attribution allows to analyze the performance of each interaction of the marketing channels used in a conversion, relying on media and site behavior-related data. It aims at obtaining a unified and comprehensive vision of the customer journey leading to conversion.

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WHAT ARE THE MULTI-TOUCH MODELS?

WEIGHTED MODELS

AD-HOC MODELS

ALGORITHMIC MODELS

LINEAR MODEL PROGRESSIVE MODEL DECLINING MODEL U-SHAPE MODEL

BASED ON BUSINESS PRIORITIZATION

BASED ON HISTORICAL DATA

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WHO ARE THE MARKET PLAYERS? TOOLS

FULL STACK

Enables connected tools sharing same data collection system to rebuild customer journeys Data is gathered in the cloud to create custom models displayed through data visualization tools

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HOW CAN ATTRIBUTION BE USED IN 2019? ADJUST MIX MEDIA AND EXPENDITURE

ASSESS CAMPAIGN OR MEDIUM REGARDING GLOBAL MARKETING STRATEGY

ENABLE CONTINUOUS IMPROVEMENT BASED ON TEST AND LEARN

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Cost

Data Collection

Models Limitations

ROUND TABLE Features Technological stack WIFI digitbench19

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THANK YOU!

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