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The Future of Social Intelligence and Sentiment Analysis

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Presentation at 3m Hosted Conference Board by Converseon/Revealed Context

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The Future of Social Intelligence and Sentiment Analysis

  1. 1. © 2014 Converseon Inc. Proprietary and Confidential Social Listening & Intelligence The Next Generation June 21, 2016
  2. 2. © 2014 Converseon Inc. Proprietary and Confidential Today’s speakers 2 ROB KEY Founder & CEO of Converseon @robkey JOEL RUBINSON Former Chief Research Office at The Advertising Research Foundation Senior Strategist and Advisor with Converseon @joelrubinson Over a decade of social intelligence and consulting leadership. Starts where listening platforms stop. “Top score consulting/research (5 out of 5), data processing and sentiment analysis (Forrester Wave Q1 2014 Enterprise Social Listening) Forrester Research Top Innovator (ConveyAPI technology) in Social Data Mining “for its ability to provide near human level precision at the speed and scale that only software can provide.” Dataweek
  3. 3. © 2014 Converseon Inc. Proprietary and Confidential “Though social and digital media are rapidly transforming marketing and new tools emerge daily, in most firms the organization of the function hasn't changed in 40 years. How should marketers revamp…to meet the new realities?” The Ultimate Marketing Machine by Marc de Swaan Arons, Frank van den Driest, Keith Weed Source: Harvard Business Review Publication Date: Jul 01, 2014. Social is a game changer
  4. 4. © 2014 Converseon Inc. Proprietary and Confidential AOL “Buying at Speed” findings across 20+ product categories: • We live in an always connected world where we browse daily…engaging in shopping behaviors without shopping purpose • When we ARE shopping, up to 80% of purchases (depends on category) involve digital, lean-forward behaviors A push-pull media world McKinsey Consumer Decision Journey AOL: Buying at speed: how technology empowers the always on shopper. Jan, 2014
  5. 5. © 2014 Converseon Inc. Proprietary and Confidential Consumers become social…with brands Marketers begin social marketing and social business programs Marketing research becomes “intrigued” Social media moves from curiosity to quantified impact 5 The journey marketers and researchers have been on embrace social data How can we engage in the conversation? What insights can we gain from social media conversation Are the data trustworthy? Does social media have quantitative value What can we learn about user interests? How can we drive sales? Curiosity Core
  6. 6. © 2014 Converseon Inc. Proprietary and Confidential Today We’re at a Tipping Point. …Into your framework for brand success …into your brand research data strategies ….to reinvent brand tracking …into your research modalities ….More and more leading brands are getting serious about integrating digital, especially social data – and capturing voice of customer in new ways
  7. 7. © 2014 Converseon Inc. Proprietary and Confidential 7 But there’s been a problem: too much social data has been a “coin flip.” Greater insights must begin with better data
  8. 8. © 2014 Converseon Inc. Proprietary and Confidential A case in point..
  9. 9. © 2014 Converseon Inc. Proprietary and Confidential The Dirty Secrets of Social Listening (to date) 9 “Far from being unfixable, however, miscalculations in social-media analyses can already be fixed using methods developed to fix similar problems in studies in epidemiology, statistics and machine learning.” - ComputerWorld
  10. 10. © 2014 Converseon Inc. Proprietary and Confidential Reasons: There’s never been more noise and less signal • How does Sprint analyze what is being said about their company? • They can’t just search for the word “sprint” • It’s too common a word
  11. 11. © 2014 Converseon Inc. Proprietary and Confidential 11 Reasons: Booleans Ineffective ("enterprise 2.0" OR "Social Biz" OR "social business" OR "#SocBiz" OR "#SocialBiz" OR "#socialbusiness" OR SocBiz OR SocialBiz OR socialbusiness OR "enterprise social business" OR "enterprise social network" OR "enterprise social grid" OR "social CRM" OR "social BPM") AND ("activity stream" OR "activity streams" OR "application development" OR "best practices" OR "business model" OR "business models" OR "content management" OR "crowd sourcing" OR "customer service" OR "disruptive technologies" OR "disruptive technology" OR "human resources" OR "information technology" OR "next generation social" OR "open social" OR "organizational culture" OR "predictive analytics" OR "product lifecycle management" OR "social analytics" OR "social mail" OR "social portal" OR "social portals" OR "social commerce" OR "customer experience management" OR "innovation management" OR "social app" OR "social application" OR "social applications" OR "social apps" OR "social business app" OR "social business application" OR "social business applications" OR "social business apps" OR "social collaboration" OR "social computing" OR "social learning" OR "social media" OR "social network" OR "social networks" OR "social platform" OR "social platforms" OR "social software" OR "social softwares" OR "social technologies" OR "social technology" OR "soft ware" OR "tool kit" OR "unified telephony" OR "analytics" OR "app" OR "application" OR "applications" OR "apps" OR "benefit" OR "benefits" OR "blog" OR "blogs" OR "bookmark" OR "bookmarks" OR "BPM" OR "collaboration" OR "collaborative" OR "commerce" OR "communication" OR "communities" OR "community" OR "compliance" OR "innovation" OR "connection" OR "connections" OR "CRM" OR "crowdsourcing" OR "engagement" OR "ERM" OR "information" OR "intelligence" OR "intelligent" OR "interaction" OR "interactive" OR "internet" OR "interoperability" OR "learning" OR "mail" OR "marketing" OR "mobile" OR "network" OR "nimble" OR "optimization" OR "optimized" OR "organization" OR "organizational" OR "organizations" OR "platform" OR "platforms" OR "portal" OR "portals" OR "productive" OR "productivity" OR "risk" OR "risks" OR "sales" OR "software" OR "softwares" OR "technologies" OR "technology" OR "tool" OR "toolkit" OR "tools" OR "transparency" OR "transparent" OR "value" OR "voIP" OR "wiki" OR "collective intelligence" OR "customer self service" OR "social grid" OR "content" OR "social content" OR "insights" OR "social selling" OR "social communications" OR "collaborative communications" OR "human capital management" OR "business process management" OR "enterprise resource management" OR "enterprise resource planning") 15% Relevancy
  12. 12. © 2014 Converseon Inc. Proprietary and Confidential • Is this tweet positive or negative? • It depends on whether you work for Verizon or Sprint • Often, your viewpoint is what makes something positive or negative, but most text analytics systems are not up to the challenge • “UberEats just launched in Ottawa but doesn't deliver to my house…I'm moving.” Every Signal, Target and Entity Must Be Captured and Analyzed Reasons: Listening Tools Have Lacked Context and POV
  13. 13. © 2014 Converseon Inc. Proprietary and Confidential The same words mean different things • An “unpredictable” movie is good, but “unpredictable” braking, not so much • We like “small” cell phones but not “small” hotel rooms Much conversation is implicit • “I spent my entire lunch hour yesterday trying to exchange my American Airline ticket Reasons: Poor Precision
  14. 14. © 2014 Converseon Inc. Proprietary and Confidential 14 It’s Simple Math 60% (precision) x 15% Relevancy X Low “Recall” = Problems
  15. 15. © 2014 Converseon Inc. Proprietary and Confidential 15 The New Era 2016: A New Era
  16. 16. © 2014 Converseon Inc. Proprietary and Confidential 16 New Deep/Machine Learning Approaches Unlocking Insights Knowledge -based Resources Machine Learning System Test Data Training Data/Libr aries Semi Supervision: Keeps “humans in the loop” for continuous training Customizable: Trains to domain and brands (“small” may be good for selling smartphones, bad for hotel rooms) Accurate: Close approximation of human performance at scale (humans that agree with each other) – generally 90-95% Scalable: Now allows the accuracy of human coding at large scale and speed Vertical and Brand/Domain Specific Custom Classifiers: Enables unlimited number of custom classifiers (intent, purchase phase, etc.) Vertical and brand specific High Relevancy and Recall: Isolates key data sets rapidly and at most detailed level. Data approach as represented by Converseon’s ConveyAPI technology
  17. 17. © 2014 Converseon Inc. Proprietary and Confidential • Relevance feedback allows you to be in control • 85% accurate with less than one hour’s work vs 15% by boolean No More Booleans: Machine Learning Captures Patterns That Go Beyond Keyword Specifics
  18. 18. © 2014 Converseon Inc. Proprietary and Confidential • It had a slightly buttery off-note • I disliked the aftertaste • The taste was decidedly foul • I would never eat this again • The taste of it turned my stomach • This the worst tasting #@&*% ever New Metrics: Intensity
  19. 19. © 2014 Converseon Inc. Proprietary and Confidential New Metrics: Emotions Plutchik Wheel of Emotion Converseon analyzes emotion in social conversation
  20. 20. © 2014 Converseon Inc. Proprietary and Confidential High Recall: Entity (Facet) Level Analysis 20
  21. 21. © 2014 Converseon Inc. Proprietary and Confidential 21 High Recall, Precision, Relevancy Example negative 4% neutral 15% positive 81% Cool Whip Sentiment: Convey negative 3% neutral 84% positive 13% Cool Whip Sentiment: Industry Standard Industry standard sentiment analysis for Cool Whip over-indexes neutral, failing to represent true consumer opinions of the brand and identify brand advocates: Industry Standard Convey Sentiment Precision 38% 83% Relevancy 46% 91%
  22. 22. © 2014 Converseon Inc. Proprietary and Confidential 22 New Metrics: Emotion and Intensity Analysis Example Emotion analysis reveals the insight that Thanksgiving is when consumers turn to social media to share their feelings about Cool Whip, associating it directly with the joy of Thanksgiving dinner with family N/A Low Intensity Medium Intensity High Intensity joy 10% 45% 28% 14% disgust 0% 1% 1% 0% anticipation 0% 1% 0% 0% anger 0% 0.1% 0.3% 0.1% sadness 0% 0.1% 0.1% 0% trust 0% 0% 0% 0% surprise 0% 0% 0% 0% fear 0% 0% 0% 0% 0 200 400 600 Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Monthly Expressions of Joy in Mentions about eating Cool Whip 20142015 Emotion and Intensity in Messages about Eating Cool Whip “I'm so excited for thanksgiving just for pumpkin pie. With a giant tub of cool whip. And some apple cider. Maybe with a side of turkey.” Source: Converseon analysis of public online records, November 2015.
  23. 23. © 2014 Converseon Inc. Proprietary and Confidential 23 Custom Classifiers Unlock New Insights Fact / Opinion Product Application Consumer Intent Brand Personality Unmet Needs Influencers Patient Journey Sentiment Adverse Events
  24. 24. © 2014 Converseon Inc. Proprietary and Confidential 5% 17% 11% 35% 17% 11% 12% 6% 0% 25% 50% 75% 100% Customer Journey Analysis Example Smartphone Category 11% 14% 13% 19% 54%35% 14% 22% 41% 14% 22% 42% 42% 27% 0% 25% 50% 75% 100% Fear Distraction Apprehension Pensiveness Acceptance Trust Serenity Surprise Interest Sadness Annoyance Disgust Anger Anticipation Joy Multiple Categories Emotions in the Purchase Funnel
  25. 25. © 2014 Converseon Inc. Proprietary and Confidential Network Analysis is Being Blended with Social Intelligence for More Advanced Influencer Analysis Twitter Network Betweenness Betweenness Centrality is a measure of ability to broker communication between individuals. Interacting with individuals who have high betweenness can expose your messages to more influencers. Legend • Arrow: Indicates that one influencer mentions another on Twitter. • Node Size: Nodes increase in size with higher numbers of overall Twitter followers. • Node Color: Indicates influencer’s centrality. High Centrality Intermediate Centrality Low Centrality © 25
  26. 26. © 2014 Converseon Inc. Proprietary and Confidential 26 New Metrics: Audience Analysis WOMEN make up 70% of Cool Whip Advocates 80% of Cool Whip Advocates are WHITE 0% 8% 73% 18% 1% 13-17 18-24 25-34 35-44 45+ White 79% Black 16% Hispanic 4% 73% of Advocates are aged 25-34 Food 58% Religion 58% Beverages 49% Humor 49% Nutrition 41% Parenting 39% Fitness 39% School Life 38% Health Care 38% Family 37% Cool Whip Advocates are interested in FOOD, FAMILY LIFE, and HEALTH @AshleyKfit Ashley Kaltwasser Athlete Top interests: Fitness, Multimedia, Travel @how2girl Courtney Sixx Model and step-mother Top interests: Fashion, Family, Charity @manwhohasitall Comedian and father Top interests: Parenting, Nutrition, Beauty Top Advocate Influencers are minor celebrities – comedian, model, athlete
  27. 27. © 2014 Converseon Inc. Proprietary and Confidential Multiple Peer Reviewed Studies Have Shown Predictive Capabilities of Convey-Powered Data 27 Professor Wendy Moe and David Schweidel, conducted analysis of social conversation versus offline brand tracking using Converseon data. . New WOMM Media Mixed Modeling Study (utilizing Converseon data) 95% precision + 85% Relevancy + High Recall
  28. 28. © 2014 Converseon Inc. Proprietary and Confidential Enabling Mainstreaming and Integration 28 Business Outcomes Brand Equity (Brand Preference & Advocacy) Sales / Share Outcomes Meaning & Engagement Meaning (Language, Attributes, Culture, Consumer Interest Profiles) Engagement Behaviors (Community Size & Behavior Toward Brand) Purchase Disposition (Path to purchase) Marketing Effectiveness Spending Impressions (Amplification via Paid, Owned vs. Earned) Return (Marketing Return on Investment) Social Inputs/ Classifiers: Brand Equity: Consumer preference + advocacy; Social NPS (actual advocating versus intent) Brand Meaning: language, topics, emotions, imagery, opinions, perceptions Engagement Behaviors: Interacting with brand beyond functional purpose. (likes, retweets, etc.) Purchase: Purchase funnel analysis; intent to buy
  29. 29. © 2014 Converseon Inc. Proprietary and Confidential …Across Organizations Product Launch, Unmet Needs, Segmentation, Outliers, etc Brand Tracking Innovation Customer Journey/Advocacy Advanced Enrichment
  30. 30. © 2014 Converseon Inc. Proprietary and Confidential 3. All the way to bright Measure and analyze social media to demonstrate its importance to the marketing organization  Contribution to sales  Predictive value  Listening for the unexpected  Segment conversations by customer groups  Seek single truth  Data not APP level! Use social media as a way of transforming brand tracking • Lighten the survey load by tracking brand beliefs via social • Be agile…as the marketplace changes, no need to fear trend disruption from adding attributes Turn social media into trustworthy information • Establish rigorous standards for determining conversation relevance and sentiment • Use the same data for modeling, KPIs, and brand tracking
  31. 31. © 2014 Converseon Inc. Proprietary and Confidential Thank You rkey@converseon.com @robkey 31

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