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Data Driven Digital Marketing
 

Data Driven Digital Marketing

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Care about learning Data Driven Digital Marketing? You will find this deck presented by Manish Vij (Founder, SVUG) during Digital Marketing Webinar for Digital Vidya. Interested in attending similar ...

Care about learning Data Driven Digital Marketing? You will find this deck presented by Manish Vij (Founder, SVUG) during Digital Marketing Webinar for Digital Vidya. Interested in attending similar Webinar Live? Register Now at http://www.digitalvidya.com/webinars/

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    Data Driven Digital Marketing Data Driven Digital Marketing Presentation Transcript

    • Digital Marketing Webinar Data Driven Digital Marketing Apr 2, 2014 | Manish Vij (Founder, SVUG) www.digitalvidya.com
    • Data Driven Digital Marketing April 4, 2014
    • AGENDA 1. What is data driven digital marketing? 2. How can an organization use 1st/3rd party data to fine- tune their digital marketing campaigns? 3. How can data driven digital campaigns impact an organization’s revenue goals? 4. What are the latest trends in data-driven marketing- navigating the complex world of Big Data? 5. What are the best practices for targeting and retargeting ads and fine-tuning segmentation strategies? 6. How to be cognizant of the latest privacy regulations?
    • Data Targeted Advertising ONLINE AUDIENCE Data Aggregation Data Point 1 Data Point 2 Data Point 3 Data Point 4 Data Management Platform (DMP) Data Analysis Trait 1 Trait 2 Trait 3 Trait 4 cookies classified into Segments classified as Intent Interest Descriptors available via connected to Multiple browsing behavior data points captured from various sources Data collected and analyzed to allow effective classification of audience cookies Cookies assigned to various usable segments, e.g. New readers, Auto Interest/Intent etc. RTB inventory used to run campaigns against relevant audience segments available via DSPs
    • Look Alike Modeling People who click on an Ad PrecisionMatch 3rd Party Data Set Converting Audiences People who look like Converting Audiences
    • CASE STUDY – LOOK-ALIKE MODELLING AUDIENCE DATA EXTENSION – POLITICAL PARTY
    • Data Seen on Platform • Overall trend of the Party’s website users as seen on DMP from 14-Jan onwards
    • Data Seen on Platform • Multiple attributes (e.g. PageType) captured for analysis
    • Sample Audience Profile • Based on analysis of the sample group, following are their interests/profile – – Microblogging users (e.g. Twitter) – Social Media users and followers – Financial Enthusiasts – Brand followers on blogging sites – Technology savvy (smartphones, tablets etc.) – Value seekers (e.g. Couponing Website visitors) – News Shows Enthusiasts – Travel Intenders – Online Shoppers – … • A number of these profiles would be receptive to the Party’s core messages of growth and anti-corruption
    • Power of Look Alike Modeling • The visitors that come to the Party’s website are a relatively small %age of the overall internet user population • While retargeting of these users can continuously engage them, look alike modeling can find other similar users at scale that have not visited the Party’s websites • Targeting these users should increase effectiveness of the Party’s campaigns since these users have similar issues and profiles as the Party’s site’s current visitors
    • Look Alike Model 13.6M new potential recipients at 82% Accuracy! *Based on sample size of just about 77k from the Party’s website
    • www.digitalvidya.com Found It Useful? Join upcoming Digital Marketing Webinar live! http://www.digitalvidya.com/webinars/