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

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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 &


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DATA FORWARD

ADVANCING BUSINESS AND MARKETING GOALS THROUGH ANALYTICS

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SLIDE 2

TOPICS FOR DISCUSSION

EVOLVING DATA & ANALYTICS LANDSCAPE TRENDS IN COMMUNICATIONS ANALYTICS CAPITALIZING ON DATA TRENDS TO DRIVE VALUE

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SLIDE 3

EVOLVING DATA & ANALYTICS LANDSCALE

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SLIDE 4 http://adage.com/article/digitalnext/speaking-language-marketing-product-teams-collaborate-analytics/310469/

ANALYTICS IS A

LEADING AREA FOR INVESTMENT

Analytics is a strategic enabler, central to delivering customer experience, identifying, understanding and growing customers, and measuring and optimizing marketing performance

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

  • f their data to drive business decisions.
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SLIDE 5

VOLUME AND VALUE IS CRITICAL

BALANCING

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REAL-TIME

IN THE NEXT THREE YEARS, MARKETING DEPARTMENTS WILL DEDICATE 22% OF THEIR BUDGETS TO ANALYTICS

Source: CMO Council Paper – Predicting Paths to Revenue

WE SEE WELL INTO THE CUSTOMER’S FUTURE AND CAN RESPOND IN RELEVANT AND MEANINGFUL WAYS IN REAL- TIME OUR ANALYTICS GIVE US A CLEAR VIEW OF PAST PERFORMANCE BUT DO LITTLE TO LIGHT THE ROAD AHEAD PREDICTIVE IN BROAD TRENDS BUT STRUGGLE TO PREDICT AND DELIVER ACTIONABLE INSIGHTS FOR AN INDIVIDUAL CUSTOMER OF ACCOUNT WE CAN PREDICT WHAT THE NEXT BEST ACTION IS, BUT BEYOND THAT IS A MORE MURKY PICTURE ANALYTICS? WHAT ANALYTICS

42% 23% 20% 12% 5%

ANALYTICS REMAINS A CHALLENGE FOR MOST

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SLIDE 7

Keep Data Investments and Value in Balance

GAPS LIMIT THE EXTENT TO WHICH COMPANIES CAN FULLY LEVERAGE DATA

TALENT 15%

  • f CMOs agree they have the
right talent to fully leverage marketing analytics – relatively unchanged since 2014 Source: The CMO Survey, 2017
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SLIDE 8

TRENDS IN COMMUNI CATIONS ANALYTICS

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Keep Data Investments and Value in Balance ARE INCREASINGLY IMPORTANT

INSIGHTS & IMPACT

Source: AMEC World Media Intelligence and Insights Study, 2016
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TOP STORIES EARNED AUDIENCE INSIGHTS CONVERSATION VOLUME TOPIC AND EMOTION SIGNALS INFLUENCER IDENTIFICATION AUTOMATED SEGMENT TARGETING REPORTING AND DATA ANALYSIS CROSS CHANNEL DATA ANALYSIS, ENGINEERING AND INFRASTRUCTURE SINGLE-SOURCE DATA MULTI-MEDIA DATA

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

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SLIDE 11

CAPITALIZNG ON DATA TRENDS TO DRIVE VALUE

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STRATEGIC ANALYTICS ACTIVATION ANALYTICS PERFORMANCE ANALYTICS

MARKET INTELLIGENCE, SETTING DIRECTION

IMPACT INSIGHTS & PLANNING EFFICIENCY

OPTIMIZING PROGRAMS AND OUTREACH ACTIVITIES EVALUATING OVERALL IMPACT AGAINST PERFORMANCE GOALS

DEFINE DATA &

ANALYTICS PRIORITIES

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SLIDE 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? 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? WHAT RESPONSES WOULD MANAGEMENT LIKE TO PROMPT WITH COMMUNICATIONS? WHAT BARRIERS HAVE HINDERED MEETING OF OBJECTIVES IN THE PAST? WHAT MARKET FORCES ARE WORKING FOR OR AGAINST US?

& CRITICAL QUESTIONS

ALIGN ON GOALS

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SLIDE 14

TEAMING TO MEET BROADER RANGE OF DATA NEEDS

TALENT STRUCTURE

DATA MODELERRS

provide statistical knowledge

DATA ENGINEERS

manage the hardware, software and data processing needs

DATA STRATEGISTS

prioritize the problems and determine data relevance

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DATA OPPORTUNITY THOUGHT-STARTERS

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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

DATA AGGREGATION/ HARMONIZATIO N Artificial Intelligence Machine Learning NLP MODELING

Audience Influencer Channel Content Impact Storytelling

ENHANCED SOLUTIONS ADVANCED METHODS

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+ Comprehensive tracking to understand brand’s social traction and positioning vs. competitors + Topic and phrases analyses to understand how consumers, influencers, and press are talking about each topic + Audience-influence tracking to pinpoint major and minor voices around particular subtopics for additional outreach targeting 10,000+ conversations per day from social, forums, blogs, news

  • utlets, TV, and radio

Data is automatically mapped and analyzed to recognize key conversations

KEY ACTIONS/INSIGHTS

Outputs arm the team with strategic communications recommendations

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SLIDE 18

WHO INFLUENCES WHOM

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INFLUENCERS

INDUSTRY INSIDERS INFLUENCE THE PRESS WHILE THE PRESS INFLUENCES CONSUMERS

INDUSTRY INSIDERS PRESS CONSUMERS

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LEARNING

Articles scored across emotion, language and societal tones Scoring provides insight into content positioning opportunities

IBM WATSON MACHINE LEARNING

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OUTLET STRATEGY

Client

PUBLISHER OR WEBSITE RANKING

Data Supplier

PRIMARY MENTION

Data Analysis

BRAND OCCURENCE EMOTION

Artificial Intelligence IBM Watson

DESIRES IMPRESSIONS

Data Supplier

VIEWABILITY

Algorithm

RELEVANCE

HOW PERTINENT IS THE ARTICLE?

TONE

HOW APPROPRIATE IN STYLE HAS THE ARTICLE BEEN WRITTEN?

VISIBILITY

HOW MANY PEOPLE HAVE THE POTENTIAL TO SEE THE ARTICLE?

Panel-based click-tracking

AUDIENCE FIT

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TV, SEARCH, AND TWITTER IMPACT

1000 2000 3000 4000 5000 6000 7000 8000 9000 1000 2000 3000 4000 5000 6000 7000 8000 Impressions Negative Conversation Negative Conversation TV Impression Effect Twitter Impression Effect Paid Search Impression Effect = Media optimized = Media not optimized
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OPEN UP NEW DATA SOURCES

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REVIEW DATA

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+ 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

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SEARCH DATA

WHAT WE ANSWERED:

+ How can we detect customer service or operational issues at a zip code, district and area level? + What are the communications implications of the data?

HOW WE ANSWERED IT:

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QUESTIONS/THANK YOU