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Commetric: The Challenge of Social Data

commetric
26. Nov 2012
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Commetric: The Challenge of Social Data

  1. BEST PRACTICE WORKSHOP # 1 The challenge of social media data 30th. October 2012 © Commetric Ltd. 2012
  2. WELCOME 2
  3. WORKSHOP AGENDA Start: 09.00am  The social data challenge – Chris Shaw, CEO Commetric  Data smart social enterprise – Maz Nadjm, Founder SoMazi  Break out challenge – 3 Teams  Summary & close Close: 11.00am 3
  4. TOPICS 1. Gathering data: – What to look for, what to ignore and how to get intelligence, not just information, from social technology 2. Internal stakeholders: – How to build bridges within your organization with social insights 3. Social impact: – How to report social media impact to elevate your profile with key decisions makers 4
  5. THE SOCIAL DATA CHALLENGE Chris Shaw 20mins © Commetric Ltd. 2012
  6. SOUND FAMILIAR? Social Measurement - speaking one language in the company it would be good to understand how to optimise SEO through social data findings. 6
  7. YOU’RE NOT ALONE Q. What is preventing your organisation/clients from harnessing social data as effectively? 7
  8. WHY IT IS EXTREMELY DIFFICULT Mega trend: Avinash Kaushik, industry guru talks about the ‘fragmentation of data capture’. • Different apps give rise to different metrics making holistic view challenging – New behaviours such as Pinterest ‘pins’ – Acceleration of new functions on social networks to retain traffic, notably Facebook • Organizations simultaneously under investing – 63% of organizations have1-2 people tasked with social data & measurement (Altimeter) 8
  9. BUT WHY IT IS IMPORTANT Q. What have been the primary positive impacts of social media data within your organization? 9
  10. FUNDING LOOKING MORE LIKELY Q. Where does digital business rank on your strategic agenda in 2013? 10
  11. CURRENT PAIN POINT PARADIGM Comms CRM Comms Structured Self ServiceEarned KPIs Data KPIs Dashboard Data Open Single Networks Campaign Text / Tweets Accurate Single Format Qualitative Platform Chinese Latin languages languages Multi Format Platform Quantitative Pictures Indicative / Videos Closed Continuous Networks Programme Executive Unstructure Sales Business Owned Report Business d data Data KPIs KPIs 11 11
  12. ONE APPROACH: TECHNOLOGY + PEOPLE We combine advanced text processing and visualization technologies to optimize human analysis.  Harvesting multiple media types for 360° perspective  Accurate Natural Language Processing (NLP) for speed  Statistical tools combining text with business performance data  Visualizations to reveal new connections in data 12
  13. MULTI-DISCIPLINED TEAM 17 Languages 13
  14. SOCIAL DATA FRAMEWORKS 1. KPIs & scorecards 2. Influencer insights 3. Impact insights 14
  15. SOCIAL DATA SCORECARDS The key is to develop KPIs that align to the business objective yet deliver relevant insights to key stakeholders Business objective Paid Earned Owned Editorially Socially Controlled Generated KPIs for key Stakeholders
  16. KPI DATA FRAMEWORK Challenge is to combine data types and analysis methodologies to deliver accurate KPIs HARVESTING QUANT FILTERS QUAL FILTERS Editorially Socially Unstructured Data Verification & ControlledGenerated Analysis Structured Data
  17. KPI SCORECARD OUTPUT Combining quant & qual methodologies, editorially controlled & socially generated media formats into stakeholder KPI scorecards Quant Total Buzz vs. Buzz by Network Buzz by geog market Owned vs. shared coverage Sentiment (indicative) by network Qual Discovered messages by brand (post / ref content) Coverage drivers by peak Sentiment by brand/competitor
  18. SOCIAL INFLUENCE DATA FRAMEWORK Deliver auto rankings of indicative influence. Will improve but currently requires qualitative enrichment QUANTITATIVE FILTERS QUALITIATIVE FILTERS Inputs Auto Rankings Relevancy x Consistency - Overall activity  - Posts / topic  - No. followers  - Topic authority  - Re-tweet ratios  - FB ave. likes /post  - FB ave. comments  / post
  19. SOCIAL INFLUENCE DATA OUTPUT Our objective is to identify ‘consistently passionate influencers and map ‘gatekeepers’ to wider networks ARAB SPRING – YEMEN
  20. SOCIAL DATA / BUSINESS DATA What are the data types that can be used to discover the business impact of social media SOCIAL DATA BUSINESS DATA  On topic activity  CRM behaviour – Posts (volumes trends / time) – FAQ visits – Multipliers (contagion/ formats) – Online questions – Quality (likes/dislikes; sentiment) – Call centre ($$)  Sales behaviour – search/research – Micro site visits – Promotion click thru – Purchases ($$)  Investor behaviour – Buy / Sell –Associated impact ($$$)
  21. ONE APPROACH TO BUSINESS IMPACT Combines media data (unstructured) with business data (structured) ; discovers correlations between rising media topics and changes in business data HARVESTING QUANT PROCESSING QUAL FILTERS Editorially NLP/Semantic engine, Verification & Controlled modeling Analysis
  22. PEPSI: CARCINOGEN REPORT 5TH MARCH
  23. Double-HELIX REPORTS: PEP - 31 bps/$306m
  24. VERIFY HISTORICAL IMPACT
  25. ALERT IMPACT / TRACK CONTAGION
  26. SOCIAL DATA GUIDING PRINCIPALS # 1. Use the broadest set of data for true perspective # 2. Combine methodologies, then be consistent # 3. Think scalable processes, not just big data # 4. Align to business objective, deliver KPIs for key stakeholders # 5. Know the difference between indicative and qualified outputs 28
  27. BUILDING THE SOCIAL ENTERPRISE Maz Nadjm, Founder SoMazi 40mins © Commetric Ltd. 2012
  28. GROUP EXERCISE One team per table 30mins © Commetric Ltd. 2012
  29. GROUP CHALLENGE OBJECTIVE • Your team is leading the social strategy of an important new car launch across five European markets. – Launched date: 1st. April 2013 – Social seeding campaign starting January 2013 led by celebrity Cristiano Ronaldo – Full national and network campaign from launch • A key task is to create a set of Key Performance Indicators to measure the campaign success in earned social media • To help with budget and buy-in, you are meeting important internal stakeholders. Tomorrow you will be presenting the campaign KPIs to the Marketing function 31
  30. GROUP CHALLENGE OBJECTIVE • Your team is leading the social strategy of an important new car launch across five European markets. – Launched date: 1st. April 2013 – Social seeding campaign starting January 2013 led by celebrity Cristiano Ronaldo – Full national and network campaign from launch • A key task is to create a set of Key Performance Indicators to measure the campaign success in earned social media • To help with budget and buy-in, you are meeting important internal stakeholders. Tomorrow you will be presenting the campaign KPIs to the Marketing function 32
  31. GROUP CHALLENGE OBJECTIVE • Your team is leading the social strategy of an important new car launch across five European markets. – Launched date: 1st. April 2013 – Social seeding campaign starting January 2013 led by celebrity Cristiano Ronaldo – Full national and network campaign from launch • A key task is to create a set of Key Performance Indicators to measure the campaign success in earned social media • To help with budget and buy-in, you are meeting important internal stakeholders. Tomorrow you will be presenting the campaign KPIs to the Marketing function 33
  32. SOCIAL NETWORK METRICS (sample) 1. Number of followers 2. Number of following 3. Overall number of tweets 4. Average tweeting frequency (tweets/day based on last week/month) 5. Share of on-topic tweets (ratio of tweets on monitored topic vs. overall number of tweets for the study period – if applicable) 6. Average number of retweets (measures how engaged this users’ followers are) 7. Number of retweets for most retweeted posting (measures whether one hit-tweet was an outlier) 8. Share of posts with link to content (measures how much the user tends to tweet interesting content, vs. creating own tweets) 9. Share of tweets with @reference (measures how much the user is prone to conversations/interactions) Facebook Groups: Group level (Manual / not auto) 1. Closed vs. Open 2. Number of members 3. Wall activity: number of wall posts for specific time period; frequency of wall posts – open groups only 4. Wall activity: is it only group owner posting, or are members posting as well – open groups only Single post level (all metrics below apply to open groups only): 1. Number of likes 2. Number of shares 3. Number of comments 4. Number of different users commenting 5. Number of comments per commentator 6. Additional layer of information - comments can be liked too, so where applicable, most liked comments/commentators per group could be identified (currently purely manual unfortunately) Facebook / Google + Personal Profiles: (Public profiles only) Personal user profiles level 1. Number of friends 2. Number of subscribers 3. Active since 4. Average number of status updates per day/week 5. Average number of comments per status updates 6. Number of different users commenting on past X number of status updates (measures if the user interacts only with a small group of more loyal friends, or many people engage with him/her) 7. Average number of other shares (links, photos, apps, locations etc) per day/week 8. Number of pages liked 9. Number of groups joined 10. Other applicable data – if necessary (number of photos uploaded, which apps the user is using) 34
  33. SOCIAL NETWORK METRICS (sample) Single status update/content share level: 1. Number of likes 2. Number of shares 3. Number of comments 4. Number of different users commenting 5. Number of comments per commentator 6. Is the post sponsored– now that you can pay to promote your own posts this is a metric we should bear in mind, because it may explain higher values in the above quant metrics (conditional upon weather Facebook identifies posts as sponsored!) 7. Number of likes by the user to the comments received by friends (to explain whose comments is the user preferring/supporting) LinkedIn 1. Number of Connections 2. Number of Companies in work experience 3. Number of Universities/Academic Institutions in education/training 4. Number of groups/professional communities joined 5. Number of status updates/shares YouTube Channel level: 1. Number of subscribers 2. Number of videos uploaded 3. Average frequency of uploading (videos per week/month 4. Average number of views per video 5. Average number of comments per video Video level: 1. Number of views 2. Number of likes 3. Number of dislikes 4. Number of comments 5. Number of video responses 35
  34. APPENDIX © Commetric Ltd. 2012
  35. GROUP CHALLENGE OBJECTIVE • Your team is leading the social strategy of an important new car launch across five European markets. – Launched date: 1st. April 2013 – Social seeding campaign starting January 2013 led by celebrity Cristiano Ronaldo – Full national and network campaign from launch • A key task is to create a set of Key Performance Indicators to measure the campaign success in earned social media • To help with budget and buy-in, you are meeting important internal stakeholders. Tomorrow you will be presenting the campaign KPIs to the Marketing function 37

Hinweis der Redaktion

  1. Collective fear in businesses that they have not got a handle on social Multiple formats Too dynamic to measure Too voluminous to find relevancy RESULT: REPUTATION EXPOSURE / BUSINESS RISK
  2. Econsultancy and AdobeIt is based on a survey of 650 marketing professionals.Technical issues:social data is stored in disparate tools (31%) social analytics are separate from multichannel analytics and business intelligence (31%)However agencies: Were more likely to point to a lack of budget or buy-in from the top of the organisation (40%) Lack of joined-up thinking (40%).Collective fear in businesses that they have not got a handle on social Multiple formats Too dynamic to measure Too voluminous to find relevancy RESULT: REPUTATION EXPOSURE / BUSINESS RISK
  3. Fragmentation of data capture; AvinashKaushik Digital Evangelist for Google, Author of Web Analytics 2.0http://www.kaushik.net/avinash/best-social-media-metrics-conversation-amplification-applause-economic-value/Different apps give rise to different metrics; making holistic view challengingNew behaviours such as ‘pins’ in Pintrest“I feel we’re all data chemists at this point, trying to put a bunch of stuff into our beakers to see if it works” Ken Burbary, Chief Digital Officer at Campbell EwaldOrganizations move slowly: 63% of Alimteter survey reported 1-2 people tasked with social media measurement
  4. Primary drivers are ‘customer insight’ – 84%However further inspection shows financial drivers make up most of the others – showing real focus in on ROIAli Ardalan, Intel‘why do you do an ROI analysis? To justify why you should do this project vs another, Why you need more funding. You need to know the results, are you wasting money?’ Could you have done the same thing with 20% less money?’Big Issue:Underlying expectation that AvinashKaushik talks about; Social media data should be a trackable as Web Analytics that have been so effective at optimizing online experiences, driver new dynamic models in advertising. But are they?The underlying tension here is the assumption that we can understand what people are thinking, wanting by the structured data elements in social data – such as ‘status’ updates, ‘likes/dislikes’, retweets and followers on twitter.As we shall see – these are ‘indicators’ and very valuable ones; however understanding what people are ‘saying’ and therefore thinking is more difficult and requires technologies that relay on processing ‘unstructured’ data – not ‘structured’
  5. Mckinsey study:1,469 CEOs / C-suite April 2012 65% say dig data / analytics a top or top three corporate priority 68% say same about digital marketing & social tools 50% say current spending too small to deliver on aspirations of business transformationBudgets are expanding: 25% responded saying they spend at least 3% of total cost base on digital initativesBut lack of agreement between C-Suite:40% CEO expect investment at least 3%20% of CFOs agreed at this level, most say less!12% CIOs agree on this level, most say more!
  6. Why is social media data difficult?In our dealings with clients, and I am sure this will be backed up by Maz later; there is currently what I call a new pain point paradigm – cheesy – but you are at the vortex of many elements that current are not ‘connecting’ – making your job very painful.Here are some of them – which I am sure you will be familiarBasically – there is no single remedy.Yet.But massive investments by Oracle, Salesforce and IBM point the way a tech architecture that will break down many of these data issues, and provide a single solution – or part…we are not there yet.
  7. Best practice for EARNED media is to combine connect KPIs for Editorially Controlled & Socially Generatede.g. Opinions being gathered/refined/re-served in Editorial media vs. spontaneous or solicited opinions in social.KPIs need to connect to understand the relationship between the two formats
  8. How does Klout work:has raised about US$40-million in funding to date.Klout now processes more than 2.7 billion pieces of information a dayalgorithm takes into account 400 distinct signalsGoogle, by comparison, only uses 200From from Twitter, now comes from Facebook, Google+, LinkedIn, Foursquare and Wikipedia It promotes three specific measures, which the company calls “true reach,” “amplification,” and “network impactDoes it capture the distinctions of actual, real world influence?How we think it works:The content you link to, and where you link to it fromThe conversations you have with people and their topicHow your followers act on your content (primarily how they retweet/share your content)Technology:mining/processing structured data: Process billions of ‘status’ updates on Facebook, Linked In, Twitter– est. 6 billion per day Process billions changes to ‘connections’ / followers – e.g. Social Graph – est. 4 billion per day Processing unstructured data: From 100+ million pieces of unstructured content – such as tweets, FB comments, linked inWe derive hundreds of thousands of different topics that 14 million users are influentialonOn average 5 topics per user using NLP and semantic analysis NLP (statistical) tags 1 million topics / ontology Key thing:Combine changes in ‘status’ and ‘connections’ to ‘topics’ (as they are defined)3 months of mentions and retweets are analyzed, currently over 6 billionRecent comments from Joe Fernandez:We are constantly evolving the algorithm with an eye toward increasing the score’s accuracyWe define influence as the ability to drive action. A person’s ability to get their network to engage with them is much more telling than their follower count.Through Klout, brands provide special offers, called “Perks,” to influencers and pay a fee to make those offers. We are also considering other forms of revenue, but Perks makes up the lion’s share of our income.
  9. How does Klout work:has raised about US$40-million in funding to date.Klout now processes more than 2.7 billion pieces of information a dayalgorithm takes into account 400 distinct signalsGoogle, by comparison, only uses 200From from Twitter, now comes from Facebook, Google+, LinkedIn, Foursquare and Wikipedia It promotes three specific measures, which the company calls “true reach,” “amplification,” and “network impactDoes it capture the distinctions of actual, real world influence?How we think it works:The content you link to, and where you link to it fromThe conversations you have with people and their topicHow your followers act on your content (primarily how they retweet/share your content)Technology:mining/processing structured data: Process billions of ‘status’ updates on Facebook, Linked In, Twitter– est. 6 billion per day Process billions changes to ‘connections’ / followers – e.g. Social Graph – est. 4 billion per day Processing unstructured data: From 100+ million pieces of unstructured content – such as tweets, FB comments, linked inWe derive hundreds of thousands of different topics that 14 million users are influentialonOn average 5 topics per user using NLP and semantic analysis NLP (statistical) tags 1 million topics / ontology Key thing:Combine changes in ‘status’ and ‘connections’ to ‘topics’ (as they are defined)3 months of mentions and retweets are analyzed, currently over 6 billionRecent comments from Joe Fernandez:We are constantly evolving the algorithm with an eye toward increasing the score’s accuracyWe define influence as the ability to drive action. A person’s ability to get their network to engage with them is much more telling than their follower count.Through Klout, brands provide special offers, called “Perks,” to influencers and pay a fee to make those offers. We are also considering other forms of revenue, but Perks makes up the lion’s share of our income.
  10. How does Klout work:has raised about US$40-million in funding to date.Klout now processes more than 2.7 billion pieces of information a dayalgorithm takes into account 400 distinct signalsGoogle, by comparison, only uses 200From from Twitter, now comes from Facebook, Google+, LinkedIn, Foursquare and Wikipedia It promotes three specific measures, which the company calls “true reach,” “amplification,” and “network impactDoes it capture the distinctions of actual, real world influence?How we think it works:The content you link to, and where you link to it fromThe conversations you have with people and their topicHow your followers act on your content (primarily how they retweet/share your content)Technology:mining/processing structured data: Process billions of ‘status’ updates on Facebook, Linked In, Twitter– est. 6 billion per day Process billions changes to ‘connections’ / followers – e.g. Social Graph – est. 4 billion per day Processing unstructured data: From 100+ million pieces of unstructured content – such as tweets, FB comments, linked inWe derive hundreds of thousands of different topics that 14 million users are influentialonOn average 5 topics per user using NLP and semantic analysis NLP (statistical) tags 1 million topics / ontology Key thing:Combine changes in ‘status’ and ‘connections’ to ‘topics’ (as they are defined)3 months of mentions and retweets are analyzed, currently over 6 billionRecent comments from Joe Fernandez:We are constantly evolving the algorithm with an eye toward increasing the score’s accuracyWe define influence as the ability to drive action. A person’s ability to get their network to engage with them is much more telling than their follower count.Through Klout, brands provide special offers, called “Perks,” to influencers and pay a fee to make those offers. We are also considering other forms of revenue, but Perks makes up the lion’s share of our income.
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