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While most organizations embrace the idea of Big data, they are yet to figure out how to solve the implications brought about by the big data explosion from social media. In this presentation we highlighted some of the key challenges that organizations face while implementing big data
The social media partner of
6 & 7 December, 2013
For more details visit:
According to McKinsey Global Institute
USE CASES OF BIG DATA
Three types of big data use cases that most often result in improved business outcomes.
HOW CAN BIG DATA HELP?
The following are the key areas where big data can help in marketing
• Implement more targeted marketing campaigns for specific geographies or
• Track and respond to promotions in real time to ensure the most profitable
• Identify which promotion strategy will yield the best results in a specific chain
or cluster of stores
• Determine which new product options are the most profitable and least risky
to pursue Better assess product price elasticity before implementing price
• Perform predictive analytics across all areas of the business to improve
• Process larger volumes of data faster, including batch data provided by
Case study: American Express airline loyalty scheme
American Express partnered with an airline to create an
air miles loyalty scheme. The scheme was to give
customers points that could eventually be used to purchase
flights, each time they used their American Express card.
Innovative air miles customer loyalty schemes such as this
require the intricate management of a lot of consumer
information from many sources, so must be robust, secure,
well supported and well maintained.
American Express uses big data to make the airline
loyalty scheme one of the most successful scheme.
One of the reasons this particular loyalty scheme is so successful is that
both American Express and its airline partner recognize their clients as
unique consumers with the help of big data
SOCIAL MEDIA DATA SUPPLEMENTS EXISTING DATA SOURCES
FOR NEW MARKETING CAPABILITIES
Analyze social media and consumer information data sources to gain customer insights and take informed sales, marketing or
SOCIAL MEDIA BIG DATA
400 Million Tweets sent per day
2.5 billion content items shared on Facebook
2.7 billion Likes
300 million photos uploaded
500+ TB data ingested
100+ PB disk space in a single HDFS cluster
105 TB data scanned via Hive (30 min)
Facebook stats as of 2012
CHALLENGES WITH SOCIAL MEDIA BIG DATA
• One of the biggest challenge with so much data on social
media is; deriving a meaningful contextual information.
• Social media data is unstructured. Unlike other customer
data from retail, banking etc. which is structured, data on
social media is unstructured.
Most organizations want to capture contextual conversations and other
widely available sources of unstructured data from social media, blog
commentaries and other sources in real time, and put them side by side with
structured data in their information ecosystem for a much clearer picture of
what is going on
Making sense out of the
unstructured data from
social media biggest
THE BIGGEST CHALLENGE
• Such unstructured data from social media has to be
approached in a non traditional manner
• Mastering the science of understanding the exploding
big data from social media will definitely be a game
LET BIG DATA DO
Slide No. 13