Social Media Analytics Strategy: Using Data to Optimize Business Performance
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Berkeley, CA
Apress L. P.
2017
|
| Schlagworte: | |
| Online-Zugang: | HWR01 |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 online resource (302 pages) |
| ISBN: | 9781484231029 |
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| 245 | 1 | 0 | |a Social Media Analytics Strategy |b Using Data to Optimize Business Performance |
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| 505 | 8 | |a Intro -- Contents -- About the Author -- About the Technical Reviewer -- Acknowledgments -- Introduction -- Part I: Data -- Chapter 1: Social Media Data -- A Look into the Evolution of Data and the Digital Gap -- Social Media Data Sources: Offline and Online -- Defining Social Media Data -- Data Sources in Social Media Channels -- Estimated vs. Factual Data Sources -- Public and Private Data -- Data Gathering in Social Media Analytics -- Social Media Network Support of Data Collection -- API: Application Programming Interface -- Web Crawling or Scraping -- Key Takeaways -- Chapter 2: From Data to Insights -- The Key Is to Be Actionable -- An Example of a Single Metric Giving Actionable Insight -- An Example of a Metric Leading to New Questions -- Focus on Being Objective Even When Everyone Else Is Not -- Creating a Plan to Shape Data into Insights -- The Planning Stage: Projecting Possible Insights -- A Very Simple Example: The Analysis of a Social Media Post -- A Glimpse into the Analysis: The Process of Comparison -- Objectives: Keep Them Simple -- Preparing for Anything with a Template Setup -- Notes on Choosing a Good Analytics Tool -- Data Aggregation, Calculations, and Display -- Aggregating Data: Avoiding Common Mistakes -- A Sample Case -- Indexes: There Is Usually a Bigger Story -- Data Display: Keep It Simple and Easy to Understand -- A Simple Example: Changing from Line to Column -- Social Media and Big Data -- Potential Challenges -- The Fragmented Landscape: How to Unify Social Data? -- Who Can Pursue a Big Data Unification Approach? -- Potential Gains -- Marketing: The Eternal Goal of Sending Only Truly Relevant Content to the Right People -- Reference: What Do People Think About ... Everything? -- Community Growth: "Power to the People" -- Our Personal AI -- Let's Think Big, But Not Too Big-Not Yet -- Key Takeaways | |
| 505 | 8 | |a Chapter 3: Luis Madureira -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Question 6 -- Question 7 -- Part II: Defining Analytics in Social Media and Types of Analytics Tools -- Chapter 4: Analytics in Social Media -- Types of Analytics in Social Media: Analytics, Listening, Advertising Analytics, Analytics from CMS and CRM -- Analytics or Channel Analytics -- Social Media Listening: Keyword and Mention-Based Analysis -- Demographics -- Interests and Sentiment -- Advertising Analytics: Focus on Conversions and ROI of Paid Social Media Campaigns -- Conversions: The Key to Digital and Social Advertising -- CMS Analytics: Measuring the Performance of the Content Management Team -- CRM Analytics: Customer Support and Sales via Social Media -- A Final Note -- Key Takeaways -- Chapter 5: Dedicated vs. Hybrid Tools -- Common to All Tools -- Dedicated Tools -- The Advantages of Dedicated Tools -- The Disadvantages of Dedicated Tools -- Hybrid Tools -- Dedicated Tools with Hybrid Features -- The Advantages of Hybrid Tools -- The Disadvantages of Hybrid Tools -- Data Integration Tools -- The Advantages of Data Integration Tools -- The Disadvantages of Data Integration Tools -- The Best Setup: Focus on Our Objective -- Trials of Different Tools Before Choosing the Best: Heaven or Hell? -- Services: When Processes Are Done on Our Behalf -- Key Takeaways -- Chapter 6: Alexander and Frederik Peiniger -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part III: Differences of Social Media Networks -- Chapter 7: Social Network Landscape -- Concept and UX on Social Networks -- Features and Their Strategic Value -- Interactivity: How Social Is the Network? -- The Content Flow on Social Networks -- The Power of Copy -- Interaction Patterns Between Users: Can Networks Put Us in a Sharing Mood? | |
| 505 | 8 | |a How Friendly Is a Network to Brands? -- Social Media as a Two-way Channel -- Goals or Trends? What Is the Best for Brands? -- Key Takeaways -- Chapter 8: Tam Su -- Question I -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Question 6 -- Part IV: The Analytics Process -- Chapter 9: The Analytics Process -- Analysis Is Comparison -- Insight: A Broad and Open Term -- Investigation Beyond Social Analytics -- Shaping a Method: The End Game for an Analyst -- The Analysis Cycle: Time Periods as the First Key to Comparison -- Finding a Good Cycle: Considering Community Activity, Resources, and Attention Span for Reports -- Community Activity: Following the Dynamics of a Brand on Social Media -- Resources: Can the Team Deliver a Quality Analysis in Time? -- Attention Span: How Often Do People Want to See Reports? -- Dynamic Cycles: Keep at Least One Anchor Down -- Short Periods: Ongoing KPIs, Buzz, and Crisis Management -- Long Periods: Goals and Greater Optimization -- Going from One Cycle to the Next -- The Analyst Mindset: Making the Right Questions and Running the Right Experiments -- The Instinctive Analyst: Share the Joy -- Find the Joy -- Get the Context: What Is Not Evident at First Glance? -- Understand the Audience -- Keep the Analyst Flame Alive: It Feels a Bit Like Sherlock Holmes' Intuition -- Key Takeaways -- Chapter 10: Armando Terribili -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part V: Metrics, Dashboards, and Reports -- Chapter 11: Metrics -- Metrics Bring New Light to Events -- Metrics Help Us Remember Available Data -- A Deck of Metrics -- Default and Custom Metrics -- Private-Level Data -- Public-Level Data -- Metric Categories: Divide and Conquer -- Graph Types: Data Is There, But Does It Look Good? -- Example 1: A Simple Change in Chart Type | |
| 505 | 8 | |a Example 2: Adding an Extra Dimension to a New Chart Type -- Default and Custom Metrics Capabilities -- Default Metrics -- Custom Metrics Capabilities -- An Interesting and Simple Example -- Another Interesting Example -- A Third and Final Example (for now) -- Custom Metrics In Paid vs. Organic Analyses -- Paid vs. Organic Tables -- The Use of Machine Learning -- Interactions vs. Paid Posts Graphs -- Linear View of Paid vs. Organic Posts and Interactions -- Metrics and Strategy: Selecting the Best Metrics for the Job -- Focus on Being Actionable, at Some Point -- Dealing with Straightforward Questions -- Content Ranking Tables -- Interactions by Content Type -- Types of Interaction -- Interactions Distribution by Post Type -- Dealing with Complex or Subjective Questions -- Step One: A Simple Example -- Step Two: Building a Story -- Estimated Metrics: Avoiding Bad Decisions -- What Are Estimated Metrics Exactly? -- Given By the Social Networks -- Calculated by Third-Party Technology -- Making Good Use of Estimated Metrics -- Metrics and Tactics -- Key Takeaways -- Chapter 12: Dashboards -- Dashboard Purpose -- Defining Dashboard Objectives -- A Quick Example -- Dashboard Suggestion -- Content Table -- Audience Change by Weekday -- Interactions vs. Posts -- Interactions Distribution -- A Final Layout for the Dashboard -- Default vs. Custom Dashboards -- Default Dashboards: More Than a First Step -- Custom Dashboards: Building the Ideal Setup -- Key Points to Shaping an Ideal Dashboard -- Linearity and Order of Metrics -- Order of Metrics -- Metric Positioning and Correlation -- A Simple Example: From a Long Period into Weekdays and Hours -- Interlude: The Revealing Case of the Busy Nightclub Manager -- A Second Simple Example: Positioning Toward Content Overview -- Metric and Dashboard Layout -- Metric and Dashboard Graphic Design | |
| 505 | 8 | |a Data Integration Dashboards -- Social Media Command Centers -- The Essence of a Good Dashboard -- "Don't get too good." -- So... The Essence... -- Key Takeaways -- Chapter 13: Reports -- Elements of Reporting -- Good Qualities for Each Element of Reporting -- Elements in Chain -- A Case of an Unstructured Approach to Reporting -- Reporting Approaches -- A Note on Reporting Formats -- Visual Resources Available on Pinterest -- Highlights -- Full KPIs -- Goal Oriented -- 360 Overview -- Storytelling -- A Simple Example of a Storytelling Report -- Animation and Effects in Reporting -- Images, Graphs, Numbers, or Text? -- Stakeholders and Feedback -- Defining Stakeholders: What Matters To Each One? And Who Matters Most To The Project? -- Reporting with Teams -- Education -- Clear Tasks -- Honest Deadlines -- Feedback Sessions -- The Report as a Key to Success -- Key Takeaways -- Chapter 14: Milan Veverka -- Question 1 -- Question 1 (interlude) -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part VI: Strategy and Tactics -- Chapter 15: Strategy -- Strategy in Social Analytics -- Strategic Planning in Social Media Analytics -- Data Availability and Data Sources -- Knowledge Beyond Social Media -- Tools and Technology Preparation -- Team Preparation -- Goals and Objectives -- Reporting Cycles and Timelines -- Contingency Plans -- Application of a Social Media Analytics Strategy -- Strategy and Tactics -- Evaluation of a Strategic Analytics Cycle -- Detecting a Hidden Strategy -- Building a Good Social Analytics Strategy -- Key Takeaways -- Chapter 16: Tactics -- Tactics for Analytics Strategies -- Correlation -- Posts, User Posts, and User Questions -- Questions and Mentions with a Per-User View -- Total Followers and Follower Change -- Total Interactions, Average Interactions, and Post Frequency | |
| 505 | 8 | |a Post Types, Interactions, and Types of Interactions by Post Type | |
| 650 | 4 | |a Big data | |
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| contents | Intro -- Contents -- About the Author -- About the Technical Reviewer -- Acknowledgments -- Introduction -- Part I: Data -- Chapter 1: Social Media Data -- A Look into the Evolution of Data and the Digital Gap -- Social Media Data Sources: Offline and Online -- Defining Social Media Data -- Data Sources in Social Media Channels -- Estimated vs. Factual Data Sources -- Public and Private Data -- Data Gathering in Social Media Analytics -- Social Media Network Support of Data Collection -- API: Application Programming Interface -- Web Crawling or Scraping -- Key Takeaways -- Chapter 2: From Data to Insights -- The Key Is to Be Actionable -- An Example of a Single Metric Giving Actionable Insight -- An Example of a Metric Leading to New Questions -- Focus on Being Objective Even When Everyone Else Is Not -- Creating a Plan to Shape Data into Insights -- The Planning Stage: Projecting Possible Insights -- A Very Simple Example: The Analysis of a Social Media Post -- A Glimpse into the Analysis: The Process of Comparison -- Objectives: Keep Them Simple -- Preparing for Anything with a Template Setup -- Notes on Choosing a Good Analytics Tool -- Data Aggregation, Calculations, and Display -- Aggregating Data: Avoiding Common Mistakes -- A Sample Case -- Indexes: There Is Usually a Bigger Story -- Data Display: Keep It Simple and Easy to Understand -- A Simple Example: Changing from Line to Column -- Social Media and Big Data -- Potential Challenges -- The Fragmented Landscape: How to Unify Social Data? -- Who Can Pursue a Big Data Unification Approach? -- Potential Gains -- Marketing: The Eternal Goal of Sending Only Truly Relevant Content to the Right People -- Reference: What Do People Think About ... Everything? -- Community Growth: "Power to the People" -- Our Personal AI -- Let's Think Big, But Not Too Big-Not Yet -- Key Takeaways Chapter 3: Luis Madureira -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Question 6 -- Question 7 -- Part II: Defining Analytics in Social Media and Types of Analytics Tools -- Chapter 4: Analytics in Social Media -- Types of Analytics in Social Media: Analytics, Listening, Advertising Analytics, Analytics from CMS and CRM -- Analytics or Channel Analytics -- Social Media Listening: Keyword and Mention-Based Analysis -- Demographics -- Interests and Sentiment -- Advertising Analytics: Focus on Conversions and ROI of Paid Social Media Campaigns -- Conversions: The Key to Digital and Social Advertising -- CMS Analytics: Measuring the Performance of the Content Management Team -- CRM Analytics: Customer Support and Sales via Social Media -- A Final Note -- Key Takeaways -- Chapter 5: Dedicated vs. Hybrid Tools -- Common to All Tools -- Dedicated Tools -- The Advantages of Dedicated Tools -- The Disadvantages of Dedicated Tools -- Hybrid Tools -- Dedicated Tools with Hybrid Features -- The Advantages of Hybrid Tools -- The Disadvantages of Hybrid Tools -- Data Integration Tools -- The Advantages of Data Integration Tools -- The Disadvantages of Data Integration Tools -- The Best Setup: Focus on Our Objective -- Trials of Different Tools Before Choosing the Best: Heaven or Hell? -- Services: When Processes Are Done on Our Behalf -- Key Takeaways -- Chapter 6: Alexander and Frederik Peiniger -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part III: Differences of Social Media Networks -- Chapter 7: Social Network Landscape -- Concept and UX on Social Networks -- Features and Their Strategic Value -- Interactivity: How Social Is the Network? -- The Content Flow on Social Networks -- The Power of Copy -- Interaction Patterns Between Users: Can Networks Put Us in a Sharing Mood? How Friendly Is a Network to Brands? -- Social Media as a Two-way Channel -- Goals or Trends? What Is the Best for Brands? -- Key Takeaways -- Chapter 8: Tam Su -- Question I -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Question 6 -- Part IV: The Analytics Process -- Chapter 9: The Analytics Process -- Analysis Is Comparison -- Insight: A Broad and Open Term -- Investigation Beyond Social Analytics -- Shaping a Method: The End Game for an Analyst -- The Analysis Cycle: Time Periods as the First Key to Comparison -- Finding a Good Cycle: Considering Community Activity, Resources, and Attention Span for Reports -- Community Activity: Following the Dynamics of a Brand on Social Media -- Resources: Can the Team Deliver a Quality Analysis in Time? -- Attention Span: How Often Do People Want to See Reports? -- Dynamic Cycles: Keep at Least One Anchor Down -- Short Periods: Ongoing KPIs, Buzz, and Crisis Management -- Long Periods: Goals and Greater Optimization -- Going from One Cycle to the Next -- The Analyst Mindset: Making the Right Questions and Running the Right Experiments -- The Instinctive Analyst: Share the Joy -- Find the Joy -- Get the Context: What Is Not Evident at First Glance? -- Understand the Audience -- Keep the Analyst Flame Alive: It Feels a Bit Like Sherlock Holmes' Intuition -- Key Takeaways -- Chapter 10: Armando Terribili -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part V: Metrics, Dashboards, and Reports -- Chapter 11: Metrics -- Metrics Bring New Light to Events -- Metrics Help Us Remember Available Data -- A Deck of Metrics -- Default and Custom Metrics -- Private-Level Data -- Public-Level Data -- Metric Categories: Divide and Conquer -- Graph Types: Data Is There, But Does It Look Good? -- Example 1: A Simple Change in Chart Type Example 2: Adding an Extra Dimension to a New Chart Type -- Default and Custom Metrics Capabilities -- Default Metrics -- Custom Metrics Capabilities -- An Interesting and Simple Example -- Another Interesting Example -- A Third and Final Example (for now) -- Custom Metrics In Paid vs. Organic Analyses -- Paid vs. Organic Tables -- The Use of Machine Learning -- Interactions vs. Paid Posts Graphs -- Linear View of Paid vs. Organic Posts and Interactions -- Metrics and Strategy: Selecting the Best Metrics for the Job -- Focus on Being Actionable, at Some Point -- Dealing with Straightforward Questions -- Content Ranking Tables -- Interactions by Content Type -- Types of Interaction -- Interactions Distribution by Post Type -- Dealing with Complex or Subjective Questions -- Step One: A Simple Example -- Step Two: Building a Story -- Estimated Metrics: Avoiding Bad Decisions -- What Are Estimated Metrics Exactly? -- Given By the Social Networks -- Calculated by Third-Party Technology -- Making Good Use of Estimated Metrics -- Metrics and Tactics -- Key Takeaways -- Chapter 12: Dashboards -- Dashboard Purpose -- Defining Dashboard Objectives -- A Quick Example -- Dashboard Suggestion -- Content Table -- Audience Change by Weekday -- Interactions vs. Posts -- Interactions Distribution -- A Final Layout for the Dashboard -- Default vs. Custom Dashboards -- Default Dashboards: More Than a First Step -- Custom Dashboards: Building the Ideal Setup -- Key Points to Shaping an Ideal Dashboard -- Linearity and Order of Metrics -- Order of Metrics -- Metric Positioning and Correlation -- A Simple Example: From a Long Period into Weekdays and Hours -- Interlude: The Revealing Case of the Busy Nightclub Manager -- A Second Simple Example: Positioning Toward Content Overview -- Metric and Dashboard Layout -- Metric and Dashboard Graphic Design Data Integration Dashboards -- Social Media Command Centers -- The Essence of a Good Dashboard -- "Don't get too good." -- So... The Essence... -- Key Takeaways -- Chapter 13: Reports -- Elements of Reporting -- Good Qualities for Each Element of Reporting -- Elements in Chain -- A Case of an Unstructured Approach to Reporting -- Reporting Approaches -- A Note on Reporting Formats -- Visual Resources Available on Pinterest -- Highlights -- Full KPIs -- Goal Oriented -- 360 Overview -- Storytelling -- A Simple Example of a Storytelling Report -- Animation and Effects in Reporting -- Images, Graphs, Numbers, or Text? -- Stakeholders and Feedback -- Defining Stakeholders: What Matters To Each One? And Who Matters Most To The Project? -- Reporting with Teams -- Education -- Clear Tasks -- Honest Deadlines -- Feedback Sessions -- The Report as a Key to Success -- Key Takeaways -- Chapter 14: Milan Veverka -- Question 1 -- Question 1 (interlude) -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part VI: Strategy and Tactics -- Chapter 15: Strategy -- Strategy in Social Analytics -- Strategic Planning in Social Media Analytics -- Data Availability and Data Sources -- Knowledge Beyond Social Media -- Tools and Technology Preparation -- Team Preparation -- Goals and Objectives -- Reporting Cycles and Timelines -- Contingency Plans -- Application of a Social Media Analytics Strategy -- Strategy and Tactics -- Evaluation of a Strategic Analytics Cycle -- Detecting a Hidden Strategy -- Building a Good Social Analytics Strategy -- Key Takeaways -- Chapter 16: Tactics -- Tactics for Analytics Strategies -- Correlation -- Posts, User Posts, and User Questions -- Questions and Mentions with a Per-User View -- Total Followers and Follower Change -- Total Interactions, Average Interactions, and Post Frequency Post Types, Interactions, and Types of Interactions by Post Type |
| ctrlnum | (ZDB-30-PQE)EBC6363080 (ZDB-30-PAD)EBC6363080 (ZDB-89-EBL)EBL6363080 (OCoLC)1012939258 (DE-599)BVBBV047693920 |
| dewey-full | 005.7 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.7 |
| dewey-search | 005.7 |
| dewey-sort | 15.7 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| format | Electronic eBook |
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P.</subfield><subfield code="c">2017</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©2017</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (302 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Intro -- Contents -- About the Author -- About the Technical Reviewer -- Acknowledgments -- Introduction -- Part I: Data -- Chapter 1: Social Media Data -- A Look into the Evolution of Data and the Digital Gap -- Social Media Data Sources: Offline and Online -- Defining Social Media Data -- Data Sources in Social Media Channels -- Estimated vs. Factual Data Sources -- Public and Private Data -- Data Gathering in Social Media Analytics -- Social Media Network Support of Data Collection -- API: Application Programming Interface -- Web Crawling or Scraping -- Key Takeaways -- Chapter 2: From Data to Insights -- The Key Is to Be Actionable -- An Example of a Single Metric Giving Actionable Insight -- An Example of a Metric Leading to New Questions -- Focus on Being Objective Even When Everyone Else Is Not -- Creating a Plan to Shape Data into Insights -- The Planning Stage: Projecting Possible Insights -- A Very Simple Example: The Analysis of a Social Media Post -- A Glimpse into the Analysis: The Process of Comparison -- Objectives: Keep Them Simple -- Preparing for Anything with a Template Setup -- Notes on Choosing a Good Analytics Tool -- Data Aggregation, Calculations, and Display -- Aggregating Data: Avoiding Common Mistakes -- A Sample Case -- Indexes: There Is Usually a Bigger Story -- Data Display: Keep It Simple and Easy to Understand -- A Simple Example: Changing from Line to Column -- Social Media and Big Data -- Potential Challenges -- The Fragmented Landscape: How to Unify Social Data? -- Who Can Pursue a Big Data Unification Approach? -- Potential Gains -- Marketing: The Eternal Goal of Sending Only Truly Relevant Content to the Right People -- Reference: What Do People Think About ... Everything? -- Community Growth: "Power to the People" -- Our Personal AI -- Let's Think Big, But Not Too Big-Not Yet -- Key Takeaways</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Chapter 3: Luis Madureira -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Question 6 -- Question 7 -- Part II: Defining Analytics in Social Media and Types of Analytics Tools -- Chapter 4: Analytics in Social Media -- Types of Analytics in Social Media: Analytics, Listening, Advertising Analytics, Analytics from CMS and CRM -- Analytics or Channel Analytics -- Social Media Listening: Keyword and Mention-Based Analysis -- Demographics -- Interests and Sentiment -- Advertising Analytics: Focus on Conversions and ROI of Paid Social Media Campaigns -- Conversions: The Key to Digital and Social Advertising -- CMS Analytics: Measuring the Performance of the Content Management Team -- CRM Analytics: Customer Support and Sales via Social Media -- A Final Note -- Key Takeaways -- Chapter 5: Dedicated vs. Hybrid Tools -- Common to All Tools -- Dedicated Tools -- The Advantages of Dedicated Tools -- The Disadvantages of Dedicated Tools -- Hybrid Tools -- Dedicated Tools with Hybrid Features -- The Advantages of Hybrid Tools -- The Disadvantages of Hybrid Tools -- Data Integration Tools -- The Advantages of Data Integration Tools -- The Disadvantages of Data Integration Tools -- The Best Setup: Focus on Our Objective -- Trials of Different Tools Before Choosing the Best: Heaven or Hell? -- Services: When Processes Are Done on Our Behalf -- Key Takeaways -- Chapter 6: Alexander and Frederik Peiniger -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part III: Differences of Social Media Networks -- Chapter 7: Social Network Landscape -- Concept and UX on Social Networks -- Features and Their Strategic Value -- Interactivity: How Social Is the Network? -- The Content Flow on Social Networks -- The Power of Copy -- Interaction Patterns Between Users: Can Networks Put Us in a Sharing Mood?</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">How Friendly Is a Network to Brands? -- Social Media as a Two-way Channel -- Goals or Trends? What Is the Best for Brands? -- Key Takeaways -- Chapter 8: Tam Su -- Question I -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Question 6 -- Part IV: The Analytics Process -- Chapter 9: The Analytics Process -- Analysis Is Comparison -- Insight: A Broad and Open Term -- Investigation Beyond Social Analytics -- Shaping a Method: The End Game for an Analyst -- The Analysis Cycle: Time Periods as the First Key to Comparison -- Finding a Good Cycle: Considering Community Activity, Resources, and Attention Span for Reports -- Community Activity: Following the Dynamics of a Brand on Social Media -- Resources: Can the Team Deliver a Quality Analysis in Time? -- Attention Span: How Often Do People Want to See Reports? -- Dynamic Cycles: Keep at Least One Anchor Down -- Short Periods: Ongoing KPIs, Buzz, and Crisis Management -- Long Periods: Goals and Greater Optimization -- Going from One Cycle to the Next -- The Analyst Mindset: Making the Right Questions and Running the Right Experiments -- The Instinctive Analyst: Share the Joy -- Find the Joy -- Get the Context: What Is Not Evident at First Glance? -- Understand the Audience -- Keep the Analyst Flame Alive: It Feels a Bit Like Sherlock Holmes' Intuition -- Key Takeaways -- Chapter 10: Armando Terribili -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part V: Metrics, Dashboards, and Reports -- Chapter 11: Metrics -- Metrics Bring New Light to Events -- Metrics Help Us Remember Available Data -- A Deck of Metrics -- Default and Custom Metrics -- Private-Level Data -- Public-Level Data -- Metric Categories: Divide and Conquer -- Graph Types: Data Is There, But Does It Look Good? -- Example 1: A Simple Change in Chart Type</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Example 2: Adding an Extra Dimension to a New Chart Type -- Default and Custom Metrics Capabilities -- Default Metrics -- Custom Metrics Capabilities -- An Interesting and Simple Example -- Another Interesting Example -- A Third and Final Example (for now) -- Custom Metrics In Paid vs. Organic Analyses -- Paid vs. Organic Tables -- The Use of Machine Learning -- Interactions vs. Paid Posts Graphs -- Linear View of Paid vs. Organic Posts and Interactions -- Metrics and Strategy: Selecting the Best Metrics for the Job -- Focus on Being Actionable, at Some Point -- Dealing with Straightforward Questions -- Content Ranking Tables -- Interactions by Content Type -- Types of Interaction -- Interactions Distribution by Post Type -- Dealing with Complex or Subjective Questions -- Step One: A Simple Example -- Step Two: Building a Story -- Estimated Metrics: Avoiding Bad Decisions -- What Are Estimated Metrics Exactly? -- Given By the Social Networks -- Calculated by Third-Party Technology -- Making Good Use of Estimated Metrics -- Metrics and Tactics -- Key Takeaways -- Chapter 12: Dashboards -- Dashboard Purpose -- Defining Dashboard Objectives -- A Quick Example -- Dashboard Suggestion -- Content Table -- Audience Change by Weekday -- Interactions vs. Posts -- Interactions Distribution -- A Final Layout for the Dashboard -- Default vs. Custom Dashboards -- Default Dashboards: More Than a First Step -- Custom Dashboards: Building the Ideal Setup -- Key Points to Shaping an Ideal Dashboard -- Linearity and Order of Metrics -- Order of Metrics -- Metric Positioning and Correlation -- A Simple Example: From a Long Period into Weekdays and Hours -- Interlude: The Revealing Case of the Busy Nightclub Manager -- A Second Simple Example: Positioning Toward Content Overview -- Metric and Dashboard Layout -- Metric and Dashboard Graphic Design</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Data Integration Dashboards -- Social Media Command Centers -- The Essence of a Good Dashboard -- "Don't get too good." -- So... The Essence... -- Key Takeaways -- Chapter 13: Reports -- Elements of Reporting -- Good Qualities for Each Element of Reporting -- Elements in Chain -- A Case of an Unstructured Approach to Reporting -- Reporting Approaches -- A Note on Reporting Formats -- Visual Resources Available on Pinterest -- Highlights -- Full KPIs -- Goal Oriented -- 360 Overview -- Storytelling -- A Simple Example of a Storytelling Report -- Animation and Effects in Reporting -- Images, Graphs, Numbers, or Text? -- Stakeholders and Feedback -- Defining Stakeholders: What Matters To Each One? And Who Matters Most To The Project? -- Reporting with Teams -- Education -- Clear Tasks -- Honest Deadlines -- Feedback Sessions -- The Report as a Key to Success -- Key Takeaways -- Chapter 14: Milan Veverka -- Question 1 -- Question 1 (interlude) -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part VI: Strategy and Tactics -- Chapter 15: Strategy -- Strategy in Social Analytics -- Strategic Planning in Social Media Analytics -- Data Availability and Data Sources -- Knowledge Beyond Social Media -- Tools and Technology Preparation -- Team Preparation -- Goals and Objectives -- Reporting Cycles and Timelines -- Contingency Plans -- Application of a Social Media Analytics Strategy -- Strategy and Tactics -- Evaluation of a Strategic Analytics Cycle -- Detecting a Hidden Strategy -- Building a Good Social Analytics Strategy -- Key Takeaways -- Chapter 16: Tactics -- Tactics for Analytics Strategies -- Correlation -- Posts, User Posts, and User Questions -- Questions and Mentions with a Per-User View -- Total Followers and Follower Change -- Total Interactions, Average Interactions, and Post Frequency</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Post Types, Interactions, and Types of Interactions by Post Type</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Big data</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="a">Gonçalves, Alex</subfield><subfield code="t">Social Media Analytics Strategy</subfield><subfield code="d">Berkeley, CA : Apress L. 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| id | DE-604.BV047693920 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T18:57:27Z |
| indexdate | 2024-07-10T09:19:21Z |
| institution | BVB |
| isbn | 9781484231029 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033077914 |
| oclc_num | 1012939258 |
| open_access_boolean | |
| owner | DE-2070s |
| owner_facet | DE-2070s |
| physical | 1 online resource (302 pages) |
| psigel | ZDB-30-PQE ZDB-30-PQE HWR_PDA_PQE |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | Apress L. P. |
| record_format | marc |
| spelling | Gonçalves, Alex Verfasser aut Social Media Analytics Strategy Using Data to Optimize Business Performance Berkeley, CA Apress L. P. 2017 ©2017 1 online resource (302 pages) txt rdacontent c rdamedia cr rdacarrier Description based on publisher supplied metadata and other sources Intro -- Contents -- About the Author -- About the Technical Reviewer -- Acknowledgments -- Introduction -- Part I: Data -- Chapter 1: Social Media Data -- A Look into the Evolution of Data and the Digital Gap -- Social Media Data Sources: Offline and Online -- Defining Social Media Data -- Data Sources in Social Media Channels -- Estimated vs. Factual Data Sources -- Public and Private Data -- Data Gathering in Social Media Analytics -- Social Media Network Support of Data Collection -- API: Application Programming Interface -- Web Crawling or Scraping -- Key Takeaways -- Chapter 2: From Data to Insights -- The Key Is to Be Actionable -- An Example of a Single Metric Giving Actionable Insight -- An Example of a Metric Leading to New Questions -- Focus on Being Objective Even When Everyone Else Is Not -- Creating a Plan to Shape Data into Insights -- The Planning Stage: Projecting Possible Insights -- A Very Simple Example: The Analysis of a Social Media Post -- A Glimpse into the Analysis: The Process of Comparison -- Objectives: Keep Them Simple -- Preparing for Anything with a Template Setup -- Notes on Choosing a Good Analytics Tool -- Data Aggregation, Calculations, and Display -- Aggregating Data: Avoiding Common Mistakes -- A Sample Case -- Indexes: There Is Usually a Bigger Story -- Data Display: Keep It Simple and Easy to Understand -- A Simple Example: Changing from Line to Column -- Social Media and Big Data -- Potential Challenges -- The Fragmented Landscape: How to Unify Social Data? -- Who Can Pursue a Big Data Unification Approach? -- Potential Gains -- Marketing: The Eternal Goal of Sending Only Truly Relevant Content to the Right People -- Reference: What Do People Think About ... Everything? -- Community Growth: "Power to the People" -- Our Personal AI -- Let's Think Big, But Not Too Big-Not Yet -- Key Takeaways Chapter 3: Luis Madureira -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Question 6 -- Question 7 -- Part II: Defining Analytics in Social Media and Types of Analytics Tools -- Chapter 4: Analytics in Social Media -- Types of Analytics in Social Media: Analytics, Listening, Advertising Analytics, Analytics from CMS and CRM -- Analytics or Channel Analytics -- Social Media Listening: Keyword and Mention-Based Analysis -- Demographics -- Interests and Sentiment -- Advertising Analytics: Focus on Conversions and ROI of Paid Social Media Campaigns -- Conversions: The Key to Digital and Social Advertising -- CMS Analytics: Measuring the Performance of the Content Management Team -- CRM Analytics: Customer Support and Sales via Social Media -- A Final Note -- Key Takeaways -- Chapter 5: Dedicated vs. Hybrid Tools -- Common to All Tools -- Dedicated Tools -- The Advantages of Dedicated Tools -- The Disadvantages of Dedicated Tools -- Hybrid Tools -- Dedicated Tools with Hybrid Features -- The Advantages of Hybrid Tools -- The Disadvantages of Hybrid Tools -- Data Integration Tools -- The Advantages of Data Integration Tools -- The Disadvantages of Data Integration Tools -- The Best Setup: Focus on Our Objective -- Trials of Different Tools Before Choosing the Best: Heaven or Hell? -- Services: When Processes Are Done on Our Behalf -- Key Takeaways -- Chapter 6: Alexander and Frederik Peiniger -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part III: Differences of Social Media Networks -- Chapter 7: Social Network Landscape -- Concept and UX on Social Networks -- Features and Their Strategic Value -- Interactivity: How Social Is the Network? -- The Content Flow on Social Networks -- The Power of Copy -- Interaction Patterns Between Users: Can Networks Put Us in a Sharing Mood? How Friendly Is a Network to Brands? -- Social Media as a Two-way Channel -- Goals or Trends? What Is the Best for Brands? -- Key Takeaways -- Chapter 8: Tam Su -- Question I -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Question 6 -- Part IV: The Analytics Process -- Chapter 9: The Analytics Process -- Analysis Is Comparison -- Insight: A Broad and Open Term -- Investigation Beyond Social Analytics -- Shaping a Method: The End Game for an Analyst -- The Analysis Cycle: Time Periods as the First Key to Comparison -- Finding a Good Cycle: Considering Community Activity, Resources, and Attention Span for Reports -- Community Activity: Following the Dynamics of a Brand on Social Media -- Resources: Can the Team Deliver a Quality Analysis in Time? -- Attention Span: How Often Do People Want to See Reports? -- Dynamic Cycles: Keep at Least One Anchor Down -- Short Periods: Ongoing KPIs, Buzz, and Crisis Management -- Long Periods: Goals and Greater Optimization -- Going from One Cycle to the Next -- The Analyst Mindset: Making the Right Questions and Running the Right Experiments -- The Instinctive Analyst: Share the Joy -- Find the Joy -- Get the Context: What Is Not Evident at First Glance? -- Understand the Audience -- Keep the Analyst Flame Alive: It Feels a Bit Like Sherlock Holmes' Intuition -- Key Takeaways -- Chapter 10: Armando Terribili -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part V: Metrics, Dashboards, and Reports -- Chapter 11: Metrics -- Metrics Bring New Light to Events -- Metrics Help Us Remember Available Data -- A Deck of Metrics -- Default and Custom Metrics -- Private-Level Data -- Public-Level Data -- Metric Categories: Divide and Conquer -- Graph Types: Data Is There, But Does It Look Good? -- Example 1: A Simple Change in Chart Type Example 2: Adding an Extra Dimension to a New Chart Type -- Default and Custom Metrics Capabilities -- Default Metrics -- Custom Metrics Capabilities -- An Interesting and Simple Example -- Another Interesting Example -- A Third and Final Example (for now) -- Custom Metrics In Paid vs. Organic Analyses -- Paid vs. Organic Tables -- The Use of Machine Learning -- Interactions vs. Paid Posts Graphs -- Linear View of Paid vs. Organic Posts and Interactions -- Metrics and Strategy: Selecting the Best Metrics for the Job -- Focus on Being Actionable, at Some Point -- Dealing with Straightforward Questions -- Content Ranking Tables -- Interactions by Content Type -- Types of Interaction -- Interactions Distribution by Post Type -- Dealing with Complex or Subjective Questions -- Step One: A Simple Example -- Step Two: Building a Story -- Estimated Metrics: Avoiding Bad Decisions -- What Are Estimated Metrics Exactly? -- Given By the Social Networks -- Calculated by Third-Party Technology -- Making Good Use of Estimated Metrics -- Metrics and Tactics -- Key Takeaways -- Chapter 12: Dashboards -- Dashboard Purpose -- Defining Dashboard Objectives -- A Quick Example -- Dashboard Suggestion -- Content Table -- Audience Change by Weekday -- Interactions vs. Posts -- Interactions Distribution -- A Final Layout for the Dashboard -- Default vs. Custom Dashboards -- Default Dashboards: More Than a First Step -- Custom Dashboards: Building the Ideal Setup -- Key Points to Shaping an Ideal Dashboard -- Linearity and Order of Metrics -- Order of Metrics -- Metric Positioning and Correlation -- A Simple Example: From a Long Period into Weekdays and Hours -- Interlude: The Revealing Case of the Busy Nightclub Manager -- A Second Simple Example: Positioning Toward Content Overview -- Metric and Dashboard Layout -- Metric and Dashboard Graphic Design Data Integration Dashboards -- Social Media Command Centers -- The Essence of a Good Dashboard -- "Don't get too good." -- So... The Essence... -- Key Takeaways -- Chapter 13: Reports -- Elements of Reporting -- Good Qualities for Each Element of Reporting -- Elements in Chain -- A Case of an Unstructured Approach to Reporting -- Reporting Approaches -- A Note on Reporting Formats -- Visual Resources Available on Pinterest -- Highlights -- Full KPIs -- Goal Oriented -- 360 Overview -- Storytelling -- A Simple Example of a Storytelling Report -- Animation and Effects in Reporting -- Images, Graphs, Numbers, or Text? -- Stakeholders and Feedback -- Defining Stakeholders: What Matters To Each One? And Who Matters Most To The Project? -- Reporting with Teams -- Education -- Clear Tasks -- Honest Deadlines -- Feedback Sessions -- The Report as a Key to Success -- Key Takeaways -- Chapter 14: Milan Veverka -- Question 1 -- Question 1 (interlude) -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part VI: Strategy and Tactics -- Chapter 15: Strategy -- Strategy in Social Analytics -- Strategic Planning in Social Media Analytics -- Data Availability and Data Sources -- Knowledge Beyond Social Media -- Tools and Technology Preparation -- Team Preparation -- Goals and Objectives -- Reporting Cycles and Timelines -- Contingency Plans -- Application of a Social Media Analytics Strategy -- Strategy and Tactics -- Evaluation of a Strategic Analytics Cycle -- Detecting a Hidden Strategy -- Building a Good Social Analytics Strategy -- Key Takeaways -- Chapter 16: Tactics -- Tactics for Analytics Strategies -- Correlation -- Posts, User Posts, and User Questions -- Questions and Mentions with a Per-User View -- Total Followers and Follower Change -- Total Interactions, Average Interactions, and Post Frequency Post Types, Interactions, and Types of Interactions by Post Type Big data Erscheint auch als Druck-Ausgabe Gonçalves, Alex Social Media Analytics Strategy Berkeley, CA : Apress L. P.,c2017 9781484231012 |
| spellingShingle | Gonçalves, Alex Social Media Analytics Strategy Using Data to Optimize Business Performance Intro -- Contents -- About the Author -- About the Technical Reviewer -- Acknowledgments -- Introduction -- Part I: Data -- Chapter 1: Social Media Data -- A Look into the Evolution of Data and the Digital Gap -- Social Media Data Sources: Offline and Online -- Defining Social Media Data -- Data Sources in Social Media Channels -- Estimated vs. Factual Data Sources -- Public and Private Data -- Data Gathering in Social Media Analytics -- Social Media Network Support of Data Collection -- API: Application Programming Interface -- Web Crawling or Scraping -- Key Takeaways -- Chapter 2: From Data to Insights -- The Key Is to Be Actionable -- An Example of a Single Metric Giving Actionable Insight -- An Example of a Metric Leading to New Questions -- Focus on Being Objective Even When Everyone Else Is Not -- Creating a Plan to Shape Data into Insights -- The Planning Stage: Projecting Possible Insights -- A Very Simple Example: The Analysis of a Social Media Post -- A Glimpse into the Analysis: The Process of Comparison -- Objectives: Keep Them Simple -- Preparing for Anything with a Template Setup -- Notes on Choosing a Good Analytics Tool -- Data Aggregation, Calculations, and Display -- Aggregating Data: Avoiding Common Mistakes -- A Sample Case -- Indexes: There Is Usually a Bigger Story -- Data Display: Keep It Simple and Easy to Understand -- A Simple Example: Changing from Line to Column -- Social Media and Big Data -- Potential Challenges -- The Fragmented Landscape: How to Unify Social Data? -- Who Can Pursue a Big Data Unification Approach? -- Potential Gains -- Marketing: The Eternal Goal of Sending Only Truly Relevant Content to the Right People -- Reference: What Do People Think About ... Everything? -- Community Growth: "Power to the People" -- Our Personal AI -- Let's Think Big, But Not Too Big-Not Yet -- Key Takeaways Chapter 3: Luis Madureira -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Question 6 -- Question 7 -- Part II: Defining Analytics in Social Media and Types of Analytics Tools -- Chapter 4: Analytics in Social Media -- Types of Analytics in Social Media: Analytics, Listening, Advertising Analytics, Analytics from CMS and CRM -- Analytics or Channel Analytics -- Social Media Listening: Keyword and Mention-Based Analysis -- Demographics -- Interests and Sentiment -- Advertising Analytics: Focus on Conversions and ROI of Paid Social Media Campaigns -- Conversions: The Key to Digital and Social Advertising -- CMS Analytics: Measuring the Performance of the Content Management Team -- CRM Analytics: Customer Support and Sales via Social Media -- A Final Note -- Key Takeaways -- Chapter 5: Dedicated vs. Hybrid Tools -- Common to All Tools -- Dedicated Tools -- The Advantages of Dedicated Tools -- The Disadvantages of Dedicated Tools -- Hybrid Tools -- Dedicated Tools with Hybrid Features -- The Advantages of Hybrid Tools -- The Disadvantages of Hybrid Tools -- Data Integration Tools -- The Advantages of Data Integration Tools -- The Disadvantages of Data Integration Tools -- The Best Setup: Focus on Our Objective -- Trials of Different Tools Before Choosing the Best: Heaven or Hell? -- Services: When Processes Are Done on Our Behalf -- Key Takeaways -- Chapter 6: Alexander and Frederik Peiniger -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part III: Differences of Social Media Networks -- Chapter 7: Social Network Landscape -- Concept and UX on Social Networks -- Features and Their Strategic Value -- Interactivity: How Social Is the Network? -- The Content Flow on Social Networks -- The Power of Copy -- Interaction Patterns Between Users: Can Networks Put Us in a Sharing Mood? How Friendly Is a Network to Brands? -- Social Media as a Two-way Channel -- Goals or Trends? What Is the Best for Brands? -- Key Takeaways -- Chapter 8: Tam Su -- Question I -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Question 6 -- Part IV: The Analytics Process -- Chapter 9: The Analytics Process -- Analysis Is Comparison -- Insight: A Broad and Open Term -- Investigation Beyond Social Analytics -- Shaping a Method: The End Game for an Analyst -- The Analysis Cycle: Time Periods as the First Key to Comparison -- Finding a Good Cycle: Considering Community Activity, Resources, and Attention Span for Reports -- Community Activity: Following the Dynamics of a Brand on Social Media -- Resources: Can the Team Deliver a Quality Analysis in Time? -- Attention Span: How Often Do People Want to See Reports? -- Dynamic Cycles: Keep at Least One Anchor Down -- Short Periods: Ongoing KPIs, Buzz, and Crisis Management -- Long Periods: Goals and Greater Optimization -- Going from One Cycle to the Next -- The Analyst Mindset: Making the Right Questions and Running the Right Experiments -- The Instinctive Analyst: Share the Joy -- Find the Joy -- Get the Context: What Is Not Evident at First Glance? -- Understand the Audience -- Keep the Analyst Flame Alive: It Feels a Bit Like Sherlock Holmes' Intuition -- Key Takeaways -- Chapter 10: Armando Terribili -- Question 1 -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part V: Metrics, Dashboards, and Reports -- Chapter 11: Metrics -- Metrics Bring New Light to Events -- Metrics Help Us Remember Available Data -- A Deck of Metrics -- Default and Custom Metrics -- Private-Level Data -- Public-Level Data -- Metric Categories: Divide and Conquer -- Graph Types: Data Is There, But Does It Look Good? -- Example 1: A Simple Change in Chart Type Example 2: Adding an Extra Dimension to a New Chart Type -- Default and Custom Metrics Capabilities -- Default Metrics -- Custom Metrics Capabilities -- An Interesting and Simple Example -- Another Interesting Example -- A Third and Final Example (for now) -- Custom Metrics In Paid vs. Organic Analyses -- Paid vs. Organic Tables -- The Use of Machine Learning -- Interactions vs. Paid Posts Graphs -- Linear View of Paid vs. Organic Posts and Interactions -- Metrics and Strategy: Selecting the Best Metrics for the Job -- Focus on Being Actionable, at Some Point -- Dealing with Straightforward Questions -- Content Ranking Tables -- Interactions by Content Type -- Types of Interaction -- Interactions Distribution by Post Type -- Dealing with Complex or Subjective Questions -- Step One: A Simple Example -- Step Two: Building a Story -- Estimated Metrics: Avoiding Bad Decisions -- What Are Estimated Metrics Exactly? -- Given By the Social Networks -- Calculated by Third-Party Technology -- Making Good Use of Estimated Metrics -- Metrics and Tactics -- Key Takeaways -- Chapter 12: Dashboards -- Dashboard Purpose -- Defining Dashboard Objectives -- A Quick Example -- Dashboard Suggestion -- Content Table -- Audience Change by Weekday -- Interactions vs. Posts -- Interactions Distribution -- A Final Layout for the Dashboard -- Default vs. Custom Dashboards -- Default Dashboards: More Than a First Step -- Custom Dashboards: Building the Ideal Setup -- Key Points to Shaping an Ideal Dashboard -- Linearity and Order of Metrics -- Order of Metrics -- Metric Positioning and Correlation -- A Simple Example: From a Long Period into Weekdays and Hours -- Interlude: The Revealing Case of the Busy Nightclub Manager -- A Second Simple Example: Positioning Toward Content Overview -- Metric and Dashboard Layout -- Metric and Dashboard Graphic Design Data Integration Dashboards -- Social Media Command Centers -- The Essence of a Good Dashboard -- "Don't get too good." -- So... The Essence... -- Key Takeaways -- Chapter 13: Reports -- Elements of Reporting -- Good Qualities for Each Element of Reporting -- Elements in Chain -- A Case of an Unstructured Approach to Reporting -- Reporting Approaches -- A Note on Reporting Formats -- Visual Resources Available on Pinterest -- Highlights -- Full KPIs -- Goal Oriented -- 360 Overview -- Storytelling -- A Simple Example of a Storytelling Report -- Animation and Effects in Reporting -- Images, Graphs, Numbers, or Text? -- Stakeholders and Feedback -- Defining Stakeholders: What Matters To Each One? And Who Matters Most To The Project? -- Reporting with Teams -- Education -- Clear Tasks -- Honest Deadlines -- Feedback Sessions -- The Report as a Key to Success -- Key Takeaways -- Chapter 14: Milan Veverka -- Question 1 -- Question 1 (interlude) -- Question 2 -- Question 3 -- Question 4 -- Question 5 -- Part VI: Strategy and Tactics -- Chapter 15: Strategy -- Strategy in Social Analytics -- Strategic Planning in Social Media Analytics -- Data Availability and Data Sources -- Knowledge Beyond Social Media -- Tools and Technology Preparation -- Team Preparation -- Goals and Objectives -- Reporting Cycles and Timelines -- Contingency Plans -- Application of a Social Media Analytics Strategy -- Strategy and Tactics -- Evaluation of a Strategic Analytics Cycle -- Detecting a Hidden Strategy -- Building a Good Social Analytics Strategy -- Key Takeaways -- Chapter 16: Tactics -- Tactics for Analytics Strategies -- Correlation -- Posts, User Posts, and User Questions -- Questions and Mentions with a Per-User View -- Total Followers and Follower Change -- Total Interactions, Average Interactions, and Post Frequency Post Types, Interactions, and Types of Interactions by Post Type Big data |
| title | Social Media Analytics Strategy Using Data to Optimize Business Performance |
| title_auth | Social Media Analytics Strategy Using Data to Optimize Business Performance |
| title_exact_search | Social Media Analytics Strategy Using Data to Optimize Business Performance |
| title_exact_search_txtP | Social Media Analytics Strategy Using Data to Optimize Business Performance |
| title_full | Social Media Analytics Strategy Using Data to Optimize Business Performance |
| title_fullStr | Social Media Analytics Strategy Using Data to Optimize Business Performance |
| title_full_unstemmed | Social Media Analytics Strategy Using Data to Optimize Business Performance |
| title_short | Social Media Analytics Strategy |
| title_sort | social media analytics strategy using data to optimize business performance |
| title_sub | Using Data to Optimize Business Performance |
| topic | Big data |
| topic_facet | Big data |
| work_keys_str_mv | AT goncalvesalex socialmediaanalyticsstrategyusingdatatooptimizebusinessperformance |