Commetric: The Challenge of Social Data

BEST PRACTICE WORKSHOP # 1

© Commetric Ltd. 2012

The challenge of social media data

30th. October 2012

2

WELCOME

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

WORKSHOP AGENDA

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

TOPICS

THE SOCIAL DATA CHALLENGE


Chris Shaw

20mins

6

SOUND FAMILIAR?

YAMMER, in particular how do people use it? And for

what? - How do we embed sharing into the culture of a

company?

Focusing mostly on

influencers on Twitter: how

to track discussions and

comparing experience with

different online tools.

Social Listening - getting

actionable data (the data vs

analysis)Social Measurement - speaking one language in the company

How to implem

ent

social media

insights company

wide

Social media ROI focusing

on business metrics

it would be good to understand how to optimise SEO through social data findings.

KOFs social media influencers Consumer activism: how to become more pro-active

social media monitoring and proactive engagement.

7

YOU’RE NOT ALONEQ. What is preventing your organisation/clients from harnessing social data as effectively?

8

• 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)

WHY IT IS EXTREMELY DIFFICULTMega trend: Avinash Kaushik, industry guru talks about the ‘fragmentation of data capture’.

9

Q. What have been the primary positive impacts of social media data within your organization?

BUT WHY IT IS IMPORTANT

10

FUNDING LOOKING MORE LIKELYQ. Where does digital business rank on your strategic agenda in 2013?

Comms KPIs

Business KPIs 11

CURRENT PAIN POINT PARADIGM

Accurate

Earned

Quantitative

Qualitative

Unstructured data

StructuredData

CRMData

Sales Data

Owned

Indicative

Latinlanguages

Chineselanguages

ClosedNetworks

OpenNetworks

Pictures / Videos

Text / Tweets

SingleCampaign

Continuous Programme

ExecutiveReport

Single FormatPlatform

Self ServiceDashboard

Multi FormatPlatform

11

Comms KPIs

BusinessKPIs

STAKEHOLDERKPIsDATA

COMPATABILITY

CRMData

Sales Data

ClosedNetworks

OpenNetworks

DATAACCESS

Pictures / Videos

Text / Tweets

MEDIAFORMATS

Single FormatPlatform

Multi FormatPlatform

MEASUREMENTPLATFORMS

Latinlanguages

Chineselanguages

LANGUAGECHARACTERISTICS

Quantitative

QualitativeANALYSIS

METHODOLOGIES

Accurate

Indicative

DATA OUTPUTINTEGRITY

SingleCampaign

Continuous Programme

PERFORMANCEBENCHMARKS

ExecutiveReport

Self ServiceDashboard

REPORTINGFORMATS

Earned

Owned

MEDIACHARACTERISTICS

Unstructured data

StructuredData

CONNECTINGDATA SILOS

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

ONE APPROACH: TECHNOLOGY + PEOPLE

13

MULTI-DISCIPLINED TEAM

17 Languages

1. KPIs & scorecards

2. Influencer insights

3. Impact insights

14

SOCIAL DATA FRAMEWORKS

The key is to develop KPIs that align to the business objective yet deliver relevant insights to key stakeholders

SOCIAL DATA SCORECARDS

Business objective

Paid Earned Owned

Editorially Controlled

Socially Generated

KPIs for key Stakeholders

Paid Owned

Challenge is to combine data types and analysis methodologies to deliver accurate KPIs

KPI DATA FRAMEWORK

EditoriallyControlled

HARVESTING QUANT FILTERS QUAL FILTERSSocially

GeneratedVerification &

AnalysisUnstructured Data

Structured Data

Combining quant & qual methodologies, editorially controlled & socially generated media formats into stakeholder KPI scorecards

KPI SCORECARD OUTPUT

Total Buzz vs. Buzz by NetworkBuzz by geog marketOwned vs. shared coverageSentiment (indicative) by network

Discovered messages by brand (post / ref content)Coverage drivers by peakSentiment by brand/competitor

Quant

Qual

Growth of influence technologies that use social graph technology to track contagion and (quality) of opinions

SOCIAL INFLUENCE DATA

SOCIAL INFLUENCE TOOLS

SOCIAL INFLUENCE DATA

Decoding these tools: Process billions of ‘structured’ data

items– Status changes, updates, re-tweets,

Process millions of ‘unstructured’ posts using statistical NLP to determine topics

Integrate into a social graph to discover/track change s in ‘connections’

Index over last 3mths

SOCIAL INFLUENCE TOOLS

Growth of influence technologies that use social graph technology to track contagion and (quality) of opinions

Relevancy x Consistency

Deliver auto rankings of indicative influence. Will improve but currently requires qualitative enrichment

SOCIAL INFLUENCE DATA FRAMEWORK

Inputs

QUANTITATIVE FILTERS QUALITIATIVE FILTERS

Auto Rankings

- Overall activity- Posts / topic- No. followers- Topic authority- Re-tweet ratios- FB ave. likes /post- FB ave. comments / post

ARAB SPRING – YEMEN

Our objective is to identify ‘consistently passionate influencers and map ‘gatekeepers’ to wider networks

SOCIAL INFLUENCE DATA OUTPUT

What are the data types that can be used to discover the business impact of social media

SOCIAL DATA / BUSINESS DATA

SOCIAL DATA BUSINESS DATA On topic activity

– Posts (volumes trends / time)– Multipliers (contagion/ formats)– Quality (likes/dislikes; sentiment)

CRM behaviour– FAQ visits– Online questions– Call centre ($$)

Sales behaviour– search/research– Micro site visits– Promotion click thru– Purchases ($$)

Investor behaviour– Buy / Sell – Associated impact ($$$)

Combines media data (unstructured) with business data (structured) ; discovers correlations between rising media topics and changes in business data

ONE APPROACH TO BUSINESS IMPACT

EditoriallyControlled

HARVESTING QUANT PROCESSINGVerification &

AnalysisNLP/Semantic engine,

modeling

QUAL FILTERS

PEPSI: CARCINOGEN REPORT 5TH MARCH

Double-HELIX REPORTS: PEP - 31 bps/$306m

VERIFY HISTORICAL IMPACT

ALERT IMPACT / TRACK CONTAGION

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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

BUILDING THE SOCIAL ENTERPRISE


Maz Nadjm, Founder SoMazi

40mins

GROUP EXERCISE


One team per table

30mins

31

GROUP CHALLENGE OBJECTIVE

• 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

• 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

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SOCIAL NETWORK METRICS (sample)

1. Number of followers2. Number of following3. Overall number of tweets4. 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 members3. Wall activity: number of wall posts for specific time period; frequency of wall posts – open groups only4. Wall activity: is it only group owner posting, or are members posting as well – open groups onlySingle post level (all metrics below apply to open groups only):1. Number of likes2. Number of shares3. Number of comments4. Number of different users commenting5. Number of comments per commentator6. 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 friends2. Number of subscribers3. Active since4. Average number of status updates per day/week5. Average number of comments per status updates6. 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/week8. Number of pages liked9. Number of groups joined10. Other applicable data – if necessary (number of photos uploaded, which apps the user is using)

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LinkedIn1. Number of Connections2. Number of Companies in work experience3. Number of Universities/Academic Institutions in education/training4. Number of groups/professional communities joined5. Number of status updates/shares

YouTubeChannel level:1. Number of subscribers2. Number of videos uploaded3. Average frequency of uploading (videos per week/month4. Average number of views per video5. Average number of comments per videoVideo level:1. Number of views2. Number of likes3. Number of dislikes4. Number of comments5. Number of video responses

Single status update/content share level:1. Number of likes2. Number of shares3. Number of comments4. Number of different users commenting5. Number of comments per commentator6. 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)

SOCIAL NETWORK METRICS (sample)

APPENDIX


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