level seven - big data in interactive marketing

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Big Data in Marketing April 2013

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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.

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Page 1: Level Seven - Big data in interactive marketing

Big Data in Marketing April 2013

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tip-off

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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

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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

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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

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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

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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

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the mechanics

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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

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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

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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

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Oreo Super Bowl win

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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!

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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

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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

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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

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customer service

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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

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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

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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

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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

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customer sentiment

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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!

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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

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WHAT CAN IT TELL ME?

BRAND HEALTH, BRAND DIFFERENTIATION

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making it work

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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

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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

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closing thoughts

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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

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questions?

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thank you