KulizaNever in the history of commerce has sucha deluge of data been vaunted beforean information-hungry, and social-savvy...
error) {alert(‘Error occured’);} else {alert(‘Cook was successful! Action ID: ‘ + response.id);}});}function postCook(){ F...
KulizaWalmart Labs, Shopycat, andBig CommerceIn a bid to strengthen its commercial offerings,Walmart acquired Kosmix and i...
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Thinking Big Data

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This article by Siddharth Balaravi, Co-founder of GetJugaad, was published in issue 06 of the Social Technology Quarterly.
Summary: Businesses are leveraging big data and analyzing it to gain a stronger competitive position. This article looks at the significance of data and how it is used to conduct experiments to develop the next generation of products and services.

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Thinking Big Data

  1. 1. KulizaNever in the history of commerce has sucha deluge of data been vaunted beforean information-hungry, and social-savvyaudience. Only a decade ago, CERN, aEuropean research organization, set up oneof the world’s largest databases with over11.5 billion web pages. Today, the averagesupermarket has access to shopping data:stores that are at least twice as big, if notbigger in size.When consumers use their credit cards atrestaurants, clothing stores, or other retailbusinesses, those purchase choices arerecorded and processed. Within the hour,businesses have the ability to unearthunderlying consumption patterns that canbe produced in real-time. In a matter of fewhours, not only does the user behaviour trendbecome more evident, but also the correlationbetween people, events, locations, andpreferences emerge from silhouettes toreveal a fairly clear picture of how marketingcampaigns are performing. The availabilityof such large amounts of actionable data istransforming the communications landscapeand is also having a sibylline effect on thefabric of social commerce.What is Big Data?Wikipedia defines Big Data as “Datasetswhose size is beyond the ability of typicaldatabase software tools to capture, store,manage, and analyze.” 2.5 quintillion bytesis the amount of data created every day.Although, this proliferation of data is anevidence of an increasingly prying world, itis possible for Big Data to positively impactsocial commerce. While most research intoBig Data so far has focussed on addressingquestions related to its volume, this articleposits the case of the impact of Big Dataon businesses with a special emphasison social commerce. The article alsoexamines the potential value that Big Datacan create for organizations, and illustrateand quantify that value.CommerceThinking BigDataBusinesses are leveraging big data and analyzing it togain a stronger competitive position.This article looksat the significance of data and how it is used to conductexperiments to develop the next generation of productsand services.by Siddharth Balaravi
  2. 2. error) {alert(‘Error occured’);} else {alert(‘Cook was successful! Action ID: ‘ + response.id);}});}function postCook(){ FB.api(‘/me/[YOUR_APP_NAMESPACE]:cook’,‘posrecipe: ‘http://fbwerks.com:8000/zhen/cookie.html’ },function(response) {if (!response || response.error) {alert(‘Error occured’);} else {alert(‘Cook was successful! Action ID+ response.id);}});}function postCook(){ FB.api(‘/me/[YOUR_APP_NAMESPACE]:cook’,‘post’,{ recipe: ‘http://fbwerks.com:8000/zhen/cookie.html’ },function(response)(!response || response.error) {alert(‘Error occured’);} else {alert(‘Cook was successful! Action ID: ‘ + response.id);}});}function postCook(){ FB.api(‘/me/[YOUR_APNAMESPACE]:cook’,‘post’,{ recipe: ‘http://fbwerks.com:8000/zhen/cookie.html’ },function(response) {if (!response || response.error) {alert(‘Error occured’);} else {alert(‘Cowas successful! 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Action ID:response.id);}});}function postCook(){ FB.api(‘/me/[YOUR_APP_NAMESPACE]:cook’,‘post’,{ recipe: ‘http://fbwerks.com:8000/zhen/cookie.html’ },function(response)(!response || response.error) {alert(‘Error occured’);} else {alert(‘Cook was successful! Action ID: ‘ + response.id);}});}function postCook(){ FB.api(‘/me/[YOUR_APNAMESPACE]:cook’,‘post’,{ recipe: ‘http://fbwerks.com:8000/zhen/cookie.html’ },function(response) {if (!response || response.error) {alert(‘Error occured’);} else {alert(‘CoIn the old days most dataproblems could be solvedas computing speed caughtup. Now, there’s this delugeof new kinds of data which isgrowing faster than Moore’slaw. We’ve basically brokenwhat Moore’s law can copewith,and so we need a bunchofnewtechnologiestogetonthe right side of that again…
  3. 3. KulizaWalmart Labs, Shopycat, andBig CommerceIn a bid to strengthen its commercial offerings,Walmart acquired Kosmix and its SocialGenome in early 2011. The Social Genomeorganizes the Internet into topic pages allowingusers to explore the Web by topic. This platformthen works as a Big Data application that iscapable of aggregating in-store, online, andsocial data and analyzing them to power aplethora of social commerce applications.Walmart implemented this with Shopycat -a Facebook application that was designedto help shoppers identify better gifts forfriends and family. Shopycat takes a person’sinterests and Likes from Facebook andcombines this information with informationagainst a vast product catalogue to identifyinteresting gift options. For instance, if onehas a friend that is known to quote Barnabus“Barney” Stinson, a fictional character fromthe CBS television series How I Met YourMother, it is quite likely that Shopycat wouldsuggest one pick costumes from the StarWars films as an ideal gift for such a friend.During the month long marketing campaignthat Shopycat was tested, it performedan astonishing 42% goal conversion rate.About half of the users who used the appshared the promotion with their friends, andthe virality garnered an incremental 25% liftin conversions. Moreover, the cost of useracquisition was $2.67, far less than theallocated campaign targets. Such resultsmark the success of such a program. Clearly,in the world of Big Data, success lies inconnecting the dots in fundamentally newways that resonate with people, brands, andsocial commerce.Big data is here to stay as it offers a competitiveadvantage with a projected 60% increasein retailers’ operating margins. It providesstatistics and insights into user and purchasebehaviours which are key factors in influencingshopping behaviours. These datasets allowcompanies to test, experiment, analyze, andthereby help them implement appropriate socialtechnologies and social shopping platforms.References“Big Data.” Wikipedia: The FreeEncyclopedia.Wikipedia Inc,02 Sep 2012.“Case Study: Walmart.” ifeelgoods.ifeelgoods,n.d.Kirsner, Scott. “Richard Dale splits fromSigma to raise money for new VC firm, BigData Boston.” Boston.com. Boston Globe, 09Aug 2012.“What is Big Data.” IBM.IBM,n.d.“World Wide Web.” Wikipedia: The FreeEncyclopedia.Wikipedia Inc,07 Sep 2012.The Value of ExperimentationThe hype around Big Data stems from thefact that it eschews a fundamentally differenttype of decision-making: one that requiresa fundamentally different mindset to theanalyses of the data itself. Think of it as data-driven decision-making on steroids. However,far from the hype, foundational customization,constant experimentation, and breakthroughbusiness models will be the new telltale signsof competition as companies capture andanalyze vast volumes of data.Using carefully crafted controlled experiments,marketers have the ability to test theories,hypotheses, and analyze results of businessdecisions in near real time. These have astriking resemblance to decisions madein hindsight as well as when experiencingone of those “I Wish I Knew” moments.Thus, experimentation can help marketersdistinguish causation from correlation. Thisreduces the variability of outcomes whileimproving the overall probability that theperformance of the control variable increases–sales, sign-ups, or any other goal.Adaptive experimentation can take manyforms. Leading online and consumer goodscompanies are test continuously. In somecases, they divide a small, but statisticallysignificant portion of their web page viewsto conduct experiments that reveal factorsthat drive higher user engagement or greaterconversions. In the world of web analytics,and digital media, this sort of experimentationis commonly known as A/B testing or Splittesting. Similarly, companies selling physicalgoods also depend on experimentationto aid decisions, but Big Data can pushthis approach to a new level. For instance,McDonald’s has installed electronic devicesthat gather operational data in few of its retailoutlets. These devices track and store detailssuch as customer interactions, traffic instores, ordering patterns, billing information,time of the day, etc. Statisticians can then usethis data to model the correlation betweenvariations in menus, restaurant designs, andtraining, among other things on the overallproductivity and sales.

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