Non-technical description of the role that Big Data can play in interactive marketing. Examples given for retail and utility industries and a brief description of customer sentiment. There is also audience participation that shows automated response to a Twitter posting.
3. INTRODUCTION
â˘âŻ Doug Denton
â˘âŻ Level Seven
â˘âŻ Interactive marketing for 6 years
â˘âŻ eCommerce brought me to marketing
â˘âŻ Technical education and background
â˘âŻ Practice Lead â Big Data
NOW YOU KNOW WHERE I AM COMING FROM
4. AGENDA
â˘âŻ DeďŹne Big Data
â˘âŻ Open vs closed loop in social media marketing
â˘âŻ Demonstrate simple example of closing the loop
â˘âŻ Consider a couple of example cases
â˘âŻ Look at the technologies that enable the capabilities
â˘âŻ Talk about smart ways to move forward
B2B & B2C UTILIZE THE SAME PRINCIPALS
5. BIG DATA
â˘âŻ Data that IT historically ignores
â˘âŻ Too fast, too diďŹerent, too much to handle
â˘âŻ Represents 80% of all data
â˘âŻ Revolutionary tools now available
â˘âŻ Very diďŹerent approach to data processing
â˘âŻ Very diďŹerent way of thinking about data
â˘âŻ A VERY BIG DEAL
YOU WERE BLIND, BUT NOW YOU SEE
6. THE OPEN LOOP
â˘âŻ Social media campaign
â˘âŻ Participants are engaged and are spreading the word
â˘âŻ Building good âbuzzâ â message is viral
â˘âŻ Conversion rate is low
â˘âŻ Typical âbrand buildingâ scenario
LOTS OF BANG, NOT SO MUCH BANK
7. CLOSING THE LOOP
â˘âŻ Allow the viral nature continue
â˘âŻ Identify active (and positive) participants
â˘âŻ Engage and reward desired behavior (1 to 1)
â˘âŻ Drive a second wave of buzz using response to reward
â˘âŻ âConstructive interferenceâ gives buzz a double-peak
â˘âŻ Reward has conversion with measurable value
MAKE THE INTERACTION PERSONAL
9. MAKE THE CONNECTIONS
â˘âŻ Monitor social channels for mentions of campaign,
products, and brand
â˘âŻ Confirm positive sentiment
â˘âŻ Reward individuals for their participation in real time
â˘âŻ Track and measure conversion
IMMEDIATE POSITIVE REINFORCEMENT
10. NOW YOU TRY IT!
â˘âŻ Step 1: In Twitter, follow @L7BigData
â˘âŻ Step 2: Tweet using hashtag #L7Rocks
â˘âŻ Options to engage you:
â˘âŻ Direct message to your account
â˘âŻ Tweet @you
â˘âŻ Retweet you
â˘âŻ Favorite your tweet
â˘âŻ Advertise to you (promote tweets)
THAT IS HOW IT WORKS
11. WHAT JUST HAPPENED?
â˘âŻ Custom application monitoring Twitter for #L7Rocks
â˘âŻ You Tweeted and were detected via direct Twitter API
â˘âŻ @L7BigData favorited your tweet
â˘âŻ You following @L7BigData -> Direct Message response
â˘âŻ Otherwise Tweet @you
â˘âŻ The exchange is logged for future use
THAT IS HOW IT WORKS
13. OREO AT THE SUPER BOWL
â˘âŻ âWhisper Fightâ commercial ran during first half
â˘âŻ 55,000 tweets in 10 minutes (110/second)
â˘âŻ 20,000 Instagram followers in 2 minutes
â˘âŻ Cost: $$$ millions $$$
â˘âŻ Traditional advertising was a success
THEN THE LIGHTS WENT OUT!
14. PREPARATION WAS KEY
â˘âŻ Oreo brand team is social media sophisticated
â˘âŻ Creative, technical, management all in a war room
â˘âŻ Ready to respond to an opportunity to amplify impact
â˘âŻ Ready to compete (Audi, Tide, Walgreens, et al)
â˘âŻ Within minutes: âPower out? No problem. You can still
dunk in the dark.â
FORTUNE FAVORS THE PREPARED MIND â LOUIS PASTEUR
15. DUNKING IN THE DARK
â˘âŻ 15,000 Twitter retweets
â˘âŻ 8,000 Twitter follows
â˘âŻ 6,200 Twitter favorites
â˘âŻ 5,500 Facebook shares
â˘âŻ 19,000 Facebook likes
â˘âŻ 14,000 Instagram follows
MULTIPLIED VALUE OF ADVERTISING INVESTMENT
16. WHAT WAS MISSING?
â˘âŻ Engaging directly with the participants in real time
â˘âŻ Highlighting involvement of participants (retweets, likes)
â˘âŻ Collecting participants for future campaigns
â˘âŻ One-to-one incentives to monetize the buzz
BIG DATA IN MOTION & SOCIAL MEDIA FEEDS
18. REGIONAL UTILITIES
â˘âŻ Monitor for mentions of problems like service outages
â˘âŻ Limit social media feeds to geography of interest
â˘âŻ Analyze message sentiment
â˘âŻ Select appropriate response
â˘âŻ Engage in a conversation
PERSONAL ATTENTION WINS CUSTOMER LOYALTY
19. UTILITY EXAMPLE
â˘âŻ Power goes out in Mentor
â˘âŻ Wife (Barb) calls me at office in Independence
â˘âŻ I tweet to see what others are saying about a power
outage in Mentor
â˘âŻ Barb posts about the outage in Facebook
â˘âŻ I Twitter search for #power #outage #firstenergy
CLEAR CONCERN ABOUT FIRST ENERGY SERVICE
20. UTILITY EXAMPLE (2)
â˘âŻ Twitter Ad from First Energy shows up at the top of my
search results
â˘âŻ Lots of tweets about the outage are in my search
results (but none from First Energy)
â˘âŻ I get a Direct Message from First Energy with a link to
report or get information regarding an outage
â˘âŻ I click the link
FIRST ENERGY FOUND ME IN THE CHANNEL OF CHOICE
21. UTILITY EXAMPLE (3)
â˘âŻ Link takes me to a website where
â˘âŻ I see a dashboard of reported outages
â˘âŻ I can login using Google, Facebook or Twitter credentials
â˘âŻ I can register for updates regarding future outages
â˘âŻ I can download a mobile application for FE customers
â˘âŻ I see that Barb just registered against our account, too
FULLY CONNECTED
23. WHAT IS IT?
â˘âŻ Identify and extract subjective information
â˘âŻ Text analytics, natural language processing,
computational linguistics
â˘âŻ Determine the attitude of the writer
â˘âŻ Classify the polarity of the text (pos, neg, neutral)
HUMANS DISAGREE 21% OF THE TIME!
24. HOW DO I DO IT?
â˘âŻ Mine message boards and social media networks
â˘âŻ Find mentions of brand, products, campaigns
â˘âŻ Determine positive, negative, neutral attitudes
â˘âŻ Compare to competition, historical trends
BIG DATA MAKES THIS POSSIBLE
25. WHAT CAN IT TELL ME?
BRAND HEALTH, BRAND DIFFERENTIATION
27. GETTING THE DATA
â˘âŻ Social media channels â direct connections (APIs)
â˘âŻ Social media channels â GNIP (www.gnip.com)
â˘âŻ Blogs and boards â Boardreader
(www.boardreader.com)
MASSIVE AMOUNTS OF DATA, CAN BE REAL-TIME
28. PROCESSING THE DATA
â˘âŻ Massive amounts of loosely-structured data
â˘âŻ Big Data tools (Hadoop, Map-Reduce, Hive, JACL, etc)
â˘âŻ Enterprise tools (IBM BigInsights)
â˘âŻ BI tools (Cognos, SAS, SPSS)
â˘âŻ Massive amounts of data in motion
â˘âŻ IBM Streams
â˘âŻ StreamSQL
BIG DATA MAKES THIS POSSIBLE
30. MOVING FORWARD
â˘âŻ Tools are ready for market
â˘âŻ Now is the time to take initial steps
â˘âŻ Proofs of concept, prototypes
â˘âŻ Quick wins
â˘âŻ Gain understanding
â˘âŻ DeďŹne your strategy
â˘âŻ Create a roadmap for adoption
TOOLS ARE READY â NEED TO UNDERSTAND THE VALUE