The document discusses the role of big data in marketing, emphasizing its importance in both B2B and B2C contexts. It highlights the significance of real-time engagement in social media campaigns and provides examples, such as Oreo's successful Super Bowl response, showcasing how brands can capitalize on immediate consumer interactions. The narrative further explores tools and technologies enabling big data analytics and encourages businesses to adopt these strategies for enhanced customer connection and brand management.

1. Big Data in Marketing
April 2013

2. tip-off

3. INTRODUCTION
• Doug Denton
• Level Seven
• Interactive marketing for 6 years
• eCommerce brought me to marketing
• Technical education and background
• Practice Lead – Big Data
NOW YOU KNOW WHERE I AM COMING FROM

4. AGENDA
• Define Big Data
• Open vs closed loop in social media marketing
• Demonstrate simple example of closing the loop
• Consider a couple of example cases
• Look at the technologies that enable the capabilities
• Talk about smart ways to move forward
B2B & B2C UTILIZE THE SAME PRINCIPALS

5. BIG DATA
• Data that IT historically ignores
• Too fast, too different, too much to handle
• Represents 80% of all data
• Revolutionary tools now available
• Very different approach to data processing
• Very different way of thinking about data
• A VERY BIG DEAL
YOU WERE BLIND, BUT NOW YOU SEE

6. THE OPEN LOOP
• Social media campaign
• Participants are engaged and are spreading the word
• Building good “buzz” – message is viral
• Conversion rate is low
• Typical “brand building” scenario
LOTS OF BANG, NOT SO MUCH BANK

7. CLOSING THE LOOP
• Allow the viral nature continue
• Identify active (and positive) participants
• Engage and reward desired behavior (1 to 1)
• Drive a second wave of buzz using response to reward
• “Constructive interference” gives buzz a double-peak
• Reward has conversion with measurable value
MAKE THE INTERACTION PERSONAL

8. the mechanics

9. MAKE THE CONNECTIONS
• Monitor social channels for mentions of campaign,
products, and brand
• Confirm positive sentiment
• Reward individuals for their participation in real time
• Track and measure conversion
IMMEDIATE POSITIVE REINFORCEMENT

10. NOW YOU TRY IT!
• Step 1: In Twitter, follow @L7BigData
• Step 2: Tweet using hashtag #L7Rocks
• Options to engage you:
• Direct message to your account
• Tweet @you
• Retweet you
• Favorite your tweet
• Advertise to you (promote tweets)
THAT IS HOW IT WORKS

11. WHAT JUST HAPPENED?
• Custom application monitoring Twitter for #L7Rocks
• You Tweeted and were detected via direct Twitter API
• @L7BigData favorited your tweet
• You following @L7BigData -> Direct Message response
• Otherwise Tweet @you
• The exchange is logged for future use
THAT IS HOW IT WORKS

12. Oreo Super Bowl win

13. OREO AT THE SUPER BOWL
• “Whisper Fight” commercial ran during first half
• 55,000 tweets in 10 minutes (110/second)
• 20,000 Instagram followers in 2 minutes
• Cost: $$$ millions $$$
• Traditional advertising was a success
THEN THE LIGHTS WENT OUT!

14. PREPARATION WAS KEY
• Oreo brand team is social media sophisticated
• Creative, technical, management all in a war room
• Ready to respond to an opportunity to amplify impact
• Ready to compete (Audi, Tide, Walgreens, et al)
• Within minutes: “Power out? No problem. You can still
dunk in the dark.”
FORTUNE FAVORS THE PREPARED MIND – LOUIS PASTEUR

15. DUNKING IN THE DARK
• 15,000 Twitter retweets
• 8,000 Twitter follows
• 6,200 Twitter favorites
• 5,500 Facebook shares
• 19,000 Facebook likes
• 14,000 Instagram follows
MULTIPLIED VALUE OF ADVERTISING INVESTMENT

16. WHAT WAS MISSING?
• Engaging directly with the participants in real time
• Highlighting involvement of participants (retweets, likes)
• Collecting participants for future campaigns
• One-to-one incentives to monetize the buzz
BIG DATA IN MOTION & SOCIAL MEDIA FEEDS

17. customer service

18. REGIONAL UTILITIES
• Monitor for mentions of problems like service outages
• Limit social media feeds to geography of interest
• Analyze message sentiment
• Select appropriate response
• Engage in a conversation
PERSONAL ATTENTION WINS CUSTOMER LOYALTY

19. UTILITY EXAMPLE
• Power goes out in Mentor
• Wife (Barb) calls me at office in Independence
• I tweet to see what others are saying about a power
outage in Mentor
• Barb posts about the outage in Facebook
• I Twitter search for #power #outage #firstenergy
CLEAR CONCERN ABOUT FIRST ENERGY SERVICE

20. UTILITY EXAMPLE (2)
• Twitter Ad from First Energy shows up at the top of my
search results
• Lots of tweets about the outage are in my search
results (but none from First Energy)
• I get a Direct Message from First Energy with a link to
report or get information regarding an outage
• I click the link
FIRST ENERGY FOUND ME IN THE CHANNEL OF CHOICE

21. UTILITY EXAMPLE (3)
• Link takes me to a website where
• I see a dashboard of reported outages
• I can login using Google, Facebook or Twitter credentials
• I can register for updates regarding future outages
• I can download a mobile application for FE customers
• I see that Barb just registered against our account, too
FULLY CONNECTED

22. customer sentiment

23. WHAT IS IT?
• Identify and extract subjective information
• Text analytics, natural language processing,
computational linguistics
• Determine the attitude of the writer
• Classify the polarity of the text (pos, neg, neutral)
HUMANS DISAGREE 21% OF THE TIME!

24. HOW DO I DO IT?
• Mine message boards and social media networks
• Find mentions of brand, products, campaigns
• Determine positive, negative, neutral attitudes
• Compare to competition, historical trends
BIG DATA MAKES THIS POSSIBLE

25. WHAT CAN IT TELL ME?
BRAND HEALTH, BRAND DIFFERENTIATION

26. making it work

27. GETTING THE DATA
• Social media channels – direct connections (APIs)
• Social media channels – GNIP (www.gnip.com)
• Blogs and boards – Boardreader
(www.boardreader.com)
MASSIVE AMOUNTS OF DATA, CAN BE REAL-TIME

28. PROCESSING THE DATA
• Massive amounts of loosely-structured data
• Big Data tools (Hadoop, Map-Reduce, Hive, JACL, etc)
• Enterprise tools (IBM BigInsights)
• BI tools (Cognos, SAS, SPSS)
• Massive amounts of data in motion
• IBM Streams
• StreamSQL
BIG DATA MAKES THIS POSSIBLE

29. closing thoughts

30. MOVING FORWARD
• Tools are ready for market
• Now is the time to take initial steps
• Proofs of concept, prototypes
• Quick wins
• Gain understanding
• Define your strategy
• Create a roadmap for adoption
TOOLS ARE READY – NEED TO UNDERSTAND THE VALUE

31. questions?

32. thank you