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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/

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Data Driven Digital Marketing

  • 1. Digital Marketing Webinar Data Driven Digital Marketing Apr 2, 2014 | Manish Vij (Founder, SVUG) www.digitalvidya.com
  • 2. Data Driven Digital Marketing April 4, 2014
  • 3. 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?
  • 4. 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
  • 5. Look Alike Modeling People who click on an Ad PrecisionMatch 3rd Party Data Set Converting Audiences People who look like Converting Audiences
  • 6. CASE STUDY – LOOK-ALIKE MODELLING AUDIENCE DATA EXTENSION – POLITICAL PARTY
  • 7. Data Seen on Platform • Overall trend of the Party’s website users as seen on DMP from 14-Jan onwards
  • 8. Data Seen on Platform • Multiple attributes (e.g. PageType) captured for analysis
  • 9. 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
  • 10. 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
  • 11. Look Alike Model 13.6M new potential recipients at 82% Accuracy! *Based on sample size of just about 77k from the Party’s website
  • 12. www.digitalvidya.com Found It Useful? Join upcoming Digital Marketing Webinar live! http://www.digitalvidya.com/webinars/