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DATA FORWARD ADVANCING BUSINESS AND MARKETING GOALS THROUGH - PowerPoint PPT Presentation

DATA FORWARD ADVANCING BUSINESS AND MARKETING GOALS THROUGH ANALYTICS TOPICS FOR DISCUSSION EVOLVING DATA & ANALYTICS LANDSCAPE TRENDS IN COMMUNICATIONS ANALYTICS CAPITALIZING ON DATA TRENDS TO DRIVE VALUE EVOLVING DATA &


  1. DATA FORWARD ADVANCING BUSINESS AND MARKETING GOALS THROUGH ANALYTICS

  2. TOPICS FOR DISCUSSION EVOLVING DATA & ANALYTICS LANDSCAPE TRENDS IN COMMUNICATIONS ANALYTICS CAPITALIZING ON DATA TRENDS TO DRIVE VALUE

  3. EVOLVING DATA & ANALYTICS LANDSCALE

  4. Analytics is a strategic enabler, central to delivering customer experience, ANALYTICS IS A identifying, understanding and growing customers, and measuring and optimizing marketing performance LEADING AREA FOR INVESTMENT In the next three years, marketing departments will dedicate 22% of their budgets to analytics (229% est. Increase in analytics spending) yet most companies still use less than one-third of their data to drive business decisions. http://adage.com/article/digitalnext/speaking-language-marketing-product-teams-collaborate-analytics/310469/

  5. BALANCING VOLUME AND VALUE IS CRITICAL

  6. 5 % WE SEE WELL INTO THE CUSTOMER’S FUTURE AND CAN RESPOND IN RELEVANT AND MEANINGFUL WAYS IN REAL- TIME 42 % REAL-TIME OUR ANALYTICS GIVE US A CLEAR VIEW OF PAST PERFORMANCE BUT DO LITTLE TO LIGHT THE 23 % ROAD AHEAD ANALYTICS REMAINS A PREDICTIVE IN BROAD TRENDS 20 % BUT STRUGGLE TO PREDICT AND CHALLENGE FOR MOST DELIVER ACTIONABLE INSIGHTS IN THE NEXT THREE YEARS, FOR AN INDIVIDUAL CUSTOMER MARKETING DEPARTMENTS WILL OF ACCOUNT 12 % DEDICATE 22% OF THEIR BUDGETS WE CAN PREDICT WHAT THE NEXT BEST ACTION IS, BUT TO ANALYTICS BEYOND THAT IS A MORE MURKY PICTURE ANALYTICS? WHAT ANALYTICS Source: CMO Council Paper – Predicting Paths to Revenue

  7. Keep Data Investments and Value in Balance TALENT 15% GAPS LIMIT THE EXTENT of CMOs agree they have the right talent to fully leverage TO WHICH COMPANIES marketing analytics – relatively unchanged since 2014 CAN FULLY LEVERAGE DATA Source: The CMO Survey, 2017

  8. TRENDS IN COMMUNI CATIONS ANALYTICS

  9. Keep Data Investments and Value in Balance INSIGHTS & IMPACT ARE INCREASINGLY IMPORTANT Source: AMEC World Media Intelligence and Insights Study, 2016

  10. EVOLVING EXPECTATIONS FOR COMMUNICATIONS ANALYSIS INCREASING DEMAND FOR INTEGRATED AND CUSTOM SOLUTIONS TO PROVIDE MORE COMPREHENSIVE INSIGHTS S TAT I C R E P O R T I N G DY N A M I C A N A LY S I S SINGLE-SOURCE DATA MULTI-MEDIA DATA CONVERSATION VOLUME TOPIC AND EMOTION SIGNALS TOP STORIES EARNED AUDIENCE INSIGHTS AUTOMATED SEGMENT INFLUENCER IDENTIFICATION TARGETING CROSS CHANNEL DATA ANALYSIS, REPORTING AND DATA ANALYSIS ENGINEERING AND INFRASTRUCTURE

  11. CAPITALIZNG ON DATA TRENDS TO DRIVE VALUE

  12. INSIGHTS & PLANNING MARKET INTELLIGENCE, SETTING DIRECTION STRATEGIC DEFINE DATA & ANALYTICS ANALYTICS PRIORITIES PERFORMANCE ACTIVATION ANALYTICS ANALYTICS IMPACT EFFICIENCY EVALUATING OVERALL IMPACT OPTIMIZING PROGRAMS AGAINST PERFORMANCE GOALS AND OUTREACH ACTIVITIES

  13. WHAT IS THE ORGANIZATION TRYING TO ACHIEVE? WHAT WILL HELP OR HINDER THE ORGANIZATION’S SUCCESS? HOW DOES MANAGEMENT THINK COMMUNICATIONS CAN HELP ACHIEVE BUSINESS GOALS? WHAT DOES SUCCESS LOOK LIKE? ALIGN WHAT IS THE OPTIMAL TIME-FRAME FOR ACHIEVING GOALS? WHO ARE OUR PRIORITY STAKEHOLDERS (INTERNAL AND EXTERNAL)? WHAT CHANNELS AND MESSAGES SHOULD BE PRIORITIZED TO REACH KEY STAKEHOLDERS? ON GOALS WHAT RESPONSES WOULD MANAGEMENT LIKE TO PROMPT WITH COMMUNICATIONS? WHAT BARRIERS HAVE HINDERED MEETING OF OBJECTIVES IN THE PAST? & CRITICAL WHAT MARKET FORCES ARE WORKING FOR OR AGAINST US? QUESTIONS

  14. DATA MODELERRS TALENT provide statistical knowledge DATA ENGINEERS STRUCTURE manage the hardware, software and data processing needs DATA STRATEGISTS TEAMING TO MEET prioritize the problems and BROADER RANGE determine data relevance OF DATA NEEDS

  15. DATA OPPORTUNITY THOUGHT-STARTERS

  16. Capabilities applied creatively to new, or as yet unsolved, communications challenges. Development of prototype new, customized solutions to meet unique analytics needs using advanced methods ENHANCED SOLUTIONS ADVANCED DATA METHODS Audience AGGREGATION/ HARMONIZATIO N Artificial Influencer Intelligence Channel Machine Learning Content NLP Impact MODELING Storytelling

  17. 10,000+ conversations per day from social, forums, blogs, news outlets, TV, and radio Data is automatically mapped and analyzed KEY ACTIONS/INSIGHTS to recognize key conversations + Comprehensive tracking to understand brand’s social traction and positioning vs. competitors Outputs arm + Topic and phrases analyses to understand how the team with strategic consumers, influencers, and press are talking about communications each topic recommendations + Audience-influence tracking to pinpoint major and minor voices around particular subtopics for additional outreach targeting 18

  18. WHO INFLUENCES WHOM CONSUMERS INFLUENCES CONSUMERS PRESS INFLUENCE THE PRESS WHILE THE PRESS INDUSTRY INDUSTRY INSIDERS INSIDERS INFLUENCERS 19

  19. LEARNING IBM WATSON MACHINE LEARNING Articles scored across emotion, language and societal tones Scoring provides insight into content positioning opportunities

  20. RELEVANCE PUBLISHER OR PRIMARY BRAND OUTLET WEBSITE RANKING MENTION OCCURENCE STRATEGY HOW PERTINENT IS THE ARTICLE? Data Supplier Client Data Analysis TONE EMOTION DESIRES HOW APPROPRIATE IN STYLE HAS THE Artificial Intelligence IBM Watson ARTICLE BEEN WRITTEN? VISIBILITY AUDIENCE FIT VIEWABILITY IMPRESSIONS HOW MANY PEOPLE HAVE Algorithm Data Supplier THE POTENTIAL TO SEE Panel-based click-tracking THE ARTICLE? 21

  21. TV, SEARCH, AND TWITTER IMPACT 8000 9000 8000 7000 Negative Conversation 7000 6000 Impressions 6000 5000 5000 4000 4000 3000 3000 2000 2000 1000 1000 0 0 = Media optimized = Media not optimized Negative Conversation TV Impression Effect Twitter Impression Effect Paid Search Impression Effect

  22. OPEN UP NEW DATA SOURCES | 23

  23. REVIEW DATA 24

  24. WHAT WE ANSWERED: SEARCH + How can we detect customer service or operational issues at a zip code, district and area level? DATA + What are the communications implications of the data? HOW WE ANSWERED IT: + Sourced search data from Google partnership + Identified search language that indicates an issue + Broken down to zip code level + Created indexed volume by zipcode + Created dashboard showing anomalies broken out by geography 25

  25. QUESTIONS/THANK YOU | 26

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