Ravi VatrapuDirector, Centre for Business Data Analytics (bda.cbs.dk)

Professor, Department of IT ManagementCopenhagen Business School, Denmark

Email: vatrapu@cbs.dkWeb: http://www.cbs.dk/en/staff/rvitm

Centre: http://bda.cbs.dk

Transforming Big Data Sets into Business Assets

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• Phenomena• Internet, Social Media & Society• Challenges & Opportunties: In-House Data + Big Data• Business Value: Big Data Sets à Business Assets

• Centre for Business Data Analytics (bda.cbs.dk)• Meaningful Facts• Actionable Insights• Valuable Outcomes• Sustainable Impacts

• Case Projects• Predictive Models• Prescriptive Analytics• Visual Analytics

• Our Product and Service Portfolio

Outline

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About Me: Global Nomad

Vizag,India Blacksburg,USA

Honolulu,USACopenhagen,Denmark

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Part I:Phenomena

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Internet, Social Media & Society

https://en.wikipedia.org/wiki/On_the_Internet,_nobody_knows_you're_a_dogRamu:“OntheFacebook,everybodyknowsIamadog"

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Challenges: How to Combine House Data with Big Data

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Opportunities: Business Value = In-House Data + Big Data

Porta,M.,House,B.,Buckley,L.&Blitz,A.(2008)

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Business Value = In-House Data + Big Data

Wollan,R.,Smith,N.&Zhou,C(2011)SonyPS4Controller:“Share”Button

ImagefromKotaku

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Big Data Sets à Business AssetsCase: Product: Baby-Monitors

MasterThesis:AdeleIndianeGurrich Kristensen&StineSofieBragdø

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Part II: CSSL ApproachSet-Theoretical Big Social Data Analytics

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CentreforBusinessDataAnalytics(cbsBDA)locatedattheDept.ofITManagement,CopenhagenBusinessSchool.cbsBDA conductstransdisciplinarybasicresearchonsocio-technicalinteractions withspecificapplicationstomanagersincompanies,teachersinschoolsandresidentsincities.

1Director&Professor2AssistantProfessors10PhDStudents4ResearchAssociates+11FacultyCollaboratorsatCBS,KUandbeyond

(IEEEEDOC2014)

cbsBDA (bda.cbs.dk)

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cbsBDA’s Naïve Model for Applied Research

• Symptoms

• Diagnosis

• Therapy• Prescription• Proscription

• Prognosis• Positive/Negative

MARCELLUS:

SomethingisrotteninthestateofDenmark

http://shakespeare.mit.edu/hamlet/full.html

https://en.wikipedia.org/wiki/File:Helsing%C3%B8r_Elsinore_from_sea_01.jpg

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Class of Problems: Social Associations (Organisations)

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SocialData

Interactions Conversations

Actors ArtifactsActivitiesActions Topics EmotionsPronounsKeywords

Source:RaviVatrapu

Conceptual Model of Social Data

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Analytical Framework for Set-Theoretical CSS

McDonaldsDKActors:266,000Noma Actors:4,567McDonaldsDK&Noma Actors:203

CROSS-WALL ANALYSIS:MCDONALDS DKVS.NOMA

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• Whatkindsofsocialtextdothese203 actorscreate,circulate,andinteractwith?

• What,ifany,isthecross-culturalvariationofactorsassociatingwithbothfastfoodandfinedining?

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Part III: Case Projects

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Case Project #1: Loyalty Club Programs

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• Datasets• CRM

• Interviews

• Facebook

Case Project #1: Loyalty Club Programs

© Temperaturenpådanskeloyalitetsklubberanno2015-II 20

BigSocialDataAnalytics

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Foragivensocialmediaaction,wewanttoanalyse andmodel:

• UserCharacteristics• Emotion• Personality

• User/ConsumerCharacteristics• ConsumerDecision-MakingStage

• Organisational Consequences• BrandSentiment

• SocialMediaConsequences• SocialEngagementPotential

Beyond Social Media-->Towards Social Business

BeyondSocialMedia-->TowardsSocialBusiness“Heres anidea.Ifyouliketheirfoodeatthere.Ifyoudont liketheirfoodeatsomewhereelseormakeyourownmeal.

Ireallydont understandwhatthebigdealis.”

User Consumer

Organisation

SocialInfluence

TextClassification:Multi-DimensionalModels

BasicEmotions

0.00% 20.00% 40.00% 60.00% 80.00% 100.00%

BRmatascoop

ForbrugsforeningenIKEA

imercolOplus

Sportsmaster

BasicEmotions:Proportion

Joy% Sadness% Surprise% Fear% Disgust% Anger%

0 0.2 0.4 0.6 0.8 1

BRmatascoop

ForbrugsforeningenIKEA

imercolOplus

Sportsmaster

BasicEmotions:Intensity

JoyIntensity SadnessIntensity SurpriseIntensity

FearIntensity DisgustIntensity AngerIntensity

BrandParameters:HistoricalDevelopment:UserEmotionsvs.BrandSentiment:

PredictingNetPromotorScoreFromBigSocialData

R²=0.95813

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0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70NPS Poly.(NPS)

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Case Project #2: Market & User Segmentation

CROSS-WALL ANALYSIS:USER/CUSTOMER SEGMENTATION

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DK2011 US2008

ENGAGEMENT DIMENSIONS &USER SEGMENTS

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SOCIAL NETWORK DIALOG SPACE

Robertson,S.,Vatrapu,R.,&Medina,R.(2010).OfftheWallPoliticalDiscourse:FacebookUseinthe2008U.S.Presidential Election.InformationPolity,15(1-2),11-31.

BUSINESS VALUE:REAL PROMOTER SCOREProduct Advocates are champions for products in general.

Product Enthusiasts are the users that aspire for the product category.

Brand Loyalists are champions of a particular brand.

Brand Tourists are in the early stages of brand consideration.

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Case Project #3: Sales & Revenue Forecasters

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Business Value: Sales and Revenue Predictive Models

(IEEEEDOC2014)(ICCSS2015)

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Q1'10

Q2'10

Q3'10

Q4'10

Q1'11

Q2'11

Q3'11

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Q1'12

Q2'12

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Q1'13

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Q4'13

Q1'14

Q2'14

Q3'14

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Q1'15

H&Msales,billionSEKperQuarter

Sales PredictedSales

Company DataSource TimePeriod SizeofDatasetApple Twitter 2007® October12,

2014500million+tweetscontaining“iPhone”

H&M Facebook January01,2009®October12,2014

~15millionFacebookevents

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Case Project #4: Social Media Crises (“Shitstorms”)

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CSR Crises: Bangladesh Factory Accidents & Volkswagen

IEEEEDOC2015 IEEEBigData2015

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Business Impact: Social Media Crisis

(ACMCABS2014) (IEEEEDOC2015)(IEEEBigData2015)

DuringCrisis:05-19February,2014Artefacts:AllData:WallbeginningtolastcollectedtimeActors:AllFacebookusersonCopenhagenZooPageActions:LIKE

Activity:PositiveAssociationSociologicalImportanceOrganizationalRelevance

Interpretation:ComputationalSocialScience:SetTheoryLIKEswereawayofexpressingculturalsolidarityandin-groupsupporttoaDanishinstitutionperceivedtobeunderundeservedout-groupcriticism

LikesonZoo’sPosts&CommentsUniqueActorsonZoo’sFBWall

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Case Project #5: EU Immigration Crisis

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EU Immigration Crisis

BDACourseProject:Jensen,Brock,Hody,Christensen&AlHumaidan

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• Big Social Data• Complete Corpus for Facebook• Multi-Channel, Multi-Language & Multi-Domain

• Analytics Software• Social Data Analytic Tool (SODATO)• Social Set Visualiser (SOSEVI)• Multi-Dimensional Text Analytics (MUDITA)• Social Business Predictor (SB-PRE)• Social Business Integrator (SB-INT)

• Research & Consultancy Reports

• Analytics Time Horizons• Fixed• Incremental• Continuous

• Analytics Mode• Historic• Near Real-Time• Real-Time

• Projects• Research

• Research Projects• Industrial PhD Projects

• Consultancy• Real Promoter Score• Strategic Management

Our Product Portfolio

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Interested?Contact us!