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A Different Perspective on
Business with Social Data
From Social Media to Decision
Tzar C. Umang
Tzar Enterprises – 23o9.tech
Why Social Media?
• Most of our customers are in Social Media
• Considering Philippines as Social Media Capital of the World
• In FB Alone we have: 28M + users where it has an acceleration of 5 user
registrations per minute, and 52% are females
• Customers freely interact, express their love and hate in social media
• It is organic interaction in virtual space means higher probability of
conversion
• By Demographics
• Location
• Gender
• Interest and etc.
Intelligence in Business
• What data tells you, is your current Story and possible
Future Story
Story
Intelligent
Operation
Flexibility and
Adaptability
Recommendation
Goals
Current Brand
Status
Competitive
Standing
Customer
Scenarios
Production
Scenarios
How do we work with Social Data?
Social Voices
Listening
Structure
Analytics
Strategize
Social Voices
• Sources:
• Pages and Personal Account – “talking about this”
• Post, Shares and Twits, Comments and Replies, Likes as based on Sentiment Icons
• State of Virality and Visibility of your content
• Social Enabled Feedback form on your Website
Listening
• A way to collect Social Voices using
• Hashtags i.e. #PogiNation
• Keywords i.e. Astig Ka, Brand Name
• Methods
• Scheming, where you get data from each social media accounts you have,
whether manually or by downloading a CSV or Excel file from it
• Crawling, where bots, cron-job or API Based Searching and Storing process is
done.
Listening Demo
Structure Data
Sentiment
Demographics
And other Social Activities
Sample Structured Data
Analytics
• Methods
• Pattern Analytics – Sorting out facts via activity patterns
• Predictive Analytics – Sorting out facts based on standard predictable effect
caused by an activity
• Stream Analytics – use of video, images or any flowing progressive data that
we get from vector dispersion, Brownian movement on pixel level and etc.
• Formal Concept Analysis – formalization of concepts derived from a dataset, it
could be based on activity, numerical representation of interactions and
Data Analytics
Data
Warehousing
Data Insight Data Foresight
Data Gathering
Cleansing
Standardization
Treatment using
Statistical Models
Identification for
Indicators
Present State
Overview
Data Treatment with
Predictive Analytic
Models
Probability and
Predictive Analytics
Pattern Analysis
Formal Concept
Analysis
Use Case
• A movie with a Target
• XX M Pesos for the 1st week
• Identify top Cities to show the
movie to secure its success on
the first day
• Make sure that we show more
than 1 week
What movie?
Hint: It is the first movie
where the environment is
purely shot in green screen
ala 300
Strategy
• Focused on Social Activity
• Demographic Vs. Interaction
• Location Vs. Age
• Location Vs. Gender
• Location Vs. Sentiment
• Sentiment is very sensitive with materials, to sustain positive interaction, our team gives
weekly recommendation on media releases based on Social Activity
Strategy
• Derived from that:
• Cinema for Premiere
• Top 10 First Day Showing Locations
• Top 10 2nd week Showing Locations
• After Compliance
• Targeted XX M Pesos + on the first week
• Sustained the movie to be present on the cinemas for more than 3 weeks
• Pushing them to create the next movie which is Kubot
Thankyou for
listening!!!
TzarC. Umang
tzarumang@gmail.com

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A Different Perspective on Business with Social Data

  • 1. A Different Perspective on Business with Social Data From Social Media to Decision Tzar C. Umang Tzar Enterprises – 23o9.tech
  • 2.
  • 3.
  • 4. Why Social Media? • Most of our customers are in Social Media • Considering Philippines as Social Media Capital of the World • In FB Alone we have: 28M + users where it has an acceleration of 5 user registrations per minute, and 52% are females • Customers freely interact, express their love and hate in social media • It is organic interaction in virtual space means higher probability of conversion • By Demographics • Location • Gender • Interest and etc.
  • 5.
  • 6. Intelligence in Business • What data tells you, is your current Story and possible Future Story Story Intelligent Operation Flexibility and Adaptability Recommendation Goals Current Brand Status Competitive Standing Customer Scenarios Production Scenarios
  • 7. How do we work with Social Data? Social Voices Listening Structure Analytics Strategize
  • 8. Social Voices • Sources: • Pages and Personal Account – “talking about this” • Post, Shares and Twits, Comments and Replies, Likes as based on Sentiment Icons • State of Virality and Visibility of your content • Social Enabled Feedback form on your Website
  • 9. Listening • A way to collect Social Voices using • Hashtags i.e. #PogiNation • Keywords i.e. Astig Ka, Brand Name • Methods • Scheming, where you get data from each social media accounts you have, whether manually or by downloading a CSV or Excel file from it • Crawling, where bots, cron-job or API Based Searching and Storing process is done.
  • 13. Analytics • Methods • Pattern Analytics – Sorting out facts via activity patterns • Predictive Analytics – Sorting out facts based on standard predictable effect caused by an activity • Stream Analytics – use of video, images or any flowing progressive data that we get from vector dispersion, Brownian movement on pixel level and etc. • Formal Concept Analysis – formalization of concepts derived from a dataset, it could be based on activity, numerical representation of interactions and
  • 14. Data Analytics Data Warehousing Data Insight Data Foresight Data Gathering Cleansing Standardization Treatment using Statistical Models Identification for Indicators Present State Overview Data Treatment with Predictive Analytic Models Probability and Predictive Analytics Pattern Analysis Formal Concept Analysis
  • 15. Use Case • A movie with a Target • XX M Pesos for the 1st week • Identify top Cities to show the movie to secure its success on the first day • Make sure that we show more than 1 week What movie? Hint: It is the first movie where the environment is purely shot in green screen ala 300
  • 16. Strategy • Focused on Social Activity • Demographic Vs. Interaction • Location Vs. Age • Location Vs. Gender • Location Vs. Sentiment • Sentiment is very sensitive with materials, to sustain positive interaction, our team gives weekly recommendation on media releases based on Social Activity
  • 17. Strategy • Derived from that: • Cinema for Premiere • Top 10 First Day Showing Locations • Top 10 2nd week Showing Locations • After Compliance • Targeted XX M Pesos + on the first week • Sustained the movie to be present on the cinemas for more than 3 weeks • Pushing them to create the next movie which is Kubot
  • 18.
  • 19.