Making Predictive Analytics Productive: Are You Learning from Social Data?
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Thanks to improved measurement tools, it is now standard among social strategists to present hard data on ROI and build strategies backed by statistics and charts - a far cry from the early years of social media. But while this data makes for great PowerPoints, concerns remain that numbers don't tell the whole story. What does "reach" really mean? Can influencers really be ranked on a single numerical spectrum? Enter predictive analytics: Advocates suggest that simply pulling numbers from Big Data tools isn't enough - you need to match the data to the story that you are trying to tell, and liberate information from what Wes Nichols calls "swim lanes". Each piece of an organization has a different picture of the data, and only combined do they provide meaningful lessons. This webinar is designed as a heart-to-heart conversation about the right and wrong ways to make use of predictive analytics.
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Making Predictive Analytics Productive: Are You Learning from Social Data?
- 1. Making Predictive Analytics Productive: Are You Learning from Social Data? #SMTLive
- 3. Our Speakers Kaiser Fung is a recognized expert in marketing analytics, a well-known speaker, and blogger. He is Vice President of Business Intelligence and Analytics at Vimeo. Previously, he led the analytics team at Sirius XM Radio. He is the creator of the acclaimed Junk Charts blog (http://junkcharts.typepad.com), which pioneered the critical examination of data and graphics in the mass media; and the author of two popular books on statistical thinking, including the recent release Numbersense: How to Use Big Data to Your Advantage. Mike Liddell General Manager, Digital Before coming to NGP VAN, Mike started working on state legislative and congressional campaigns to later become the Director of Online Communications for the 2004 Democratic National Convention. He then put in two tours of duty as the Director of Online Communications for the Democratic Senatorial Campaign Committee (DSCC). Most recently, he served in the Obama Administration, where he led the award-winning redesign of Treasury.gov. @mliddell Eric Siegel, Ph.D., founder of Predictive Analytics World and Text Analytics World, and Executive Editor of the Predictive Analytics Times, makes the how and why of predictive analytics understandable and captivating. In addition to being the author ofPredictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, Eric is a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field. @predictanalytic Paul Dunay, moderator, is an award-winning B2B marketing expert with more than 20 years’ success in generating demand and creating buzz for leading technology, consumer products, financial services and professional services organizations. @PaulDunay #SMTLive
- 4. How Predictive Analytics Leverages Social Media Social Media Today November 2013 Eric Siegel, Ph.D. Founder, Predictive Analytics World Author, Predictive Analytics Predictive Analytics World
- 8. The Social Effect Predictive Analytics World
- 9. The Social Effect Predictive Analytics World
- 11. Major N. American Telecom 700% more likely to cancel if someone in your network does Optus (Australian telecom) Doubled churn model performance with social data Predictive Analytics World
- 12. Amazon product reviews Research model IDs 83%. "Trees died for this book?" Predictive Analytics World
- 13. Editing requests Polite editors achieve high status; once elevated, become less polite Predictive Analytics World
- 15. Friendships LinkedIn: this is "the most important data product we built." Predictive Analytics World
- 16. Degree of influence Predictive Analytics World
- 17. Publicity tweet 55% increase in web page views publicizing Video Music Awards Predictive Analytics World
- 20. To Learn More: The Predictive Analytics Guide www.pawcon.com/guide Predictive Analytics World
- 21. On Accuracy Kaiser Fung Numbersense | Junk Charts
- 24. ViewThrough Data A user viewed a display ad
- 25. ViewThrough Data A server sent an ad to a browser
- 28. FB Likes Data New user converts
- 29. FB Likes Data New user converts Loyal user re-affirms Response to offer Purchased
- 31. Mike Liddell, General Manager - Digital
- 32. The Mustache
- 33. Social Analytics + Politics Singular Focus Social data including relationships Analytics should have a seat at the table
- 34. Join us on Thursday for… 11/7 Social Media Hacks and Hijacks: The Best Tips and Tricks to Maximize Your Social ROI http://socialmediatoday.com/hacks-and-hijacks-webinar
Editor's Notes
- The way we go about our lead generation campaigns is we base them on a Unified strategy- we determine the goals of the client and these can be refined once we discuss a little more but then we also factor in the purpose of the potential leads who are seeking information. People are coming to Social Media Today to get information and make their business better. They are looking for a solution. Jive can be that solutionWe can guarantee the Social Media Today leads are better qualified because of the quality of the content, and the unique vision that understands what business you are in and what you are trying to achieve. We are not trying to simply deliver leads, we are trying to cultivate relationships and connect you to real customers.
- http://www.marketingprofs.com/charts/2013/11340/digital-marketers-on-twitter-share-retweet?adref=nl080613Quote on lower person reading article.Social Media Today’s number’s are growing exponentially lately, which is great for Jive because as we develop new content we ccanWE are unique in our reach
- We’d love to propose a content hub as a way to organize this lead generation campaign for Jive. The content hub can be specific to each of the verticals you are looking to focus on or can be more general to incorporate all three verticals and maybe more as the campaign grows. We envision leveraging existing Jive eBooks, whitepapers, and webinars to begin lead generation immediately (in the next few slides, I’ll show you how Oracle does this)
- BOOK:Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Diewww.thepredictionbook.comCONFERENCE:Predictive Analytics WorldSan Francisco, Chicago, Boston, Washington DC, Toronto, Berlin, and Londonwww.predictiveanalyticsworld.comONLINE PORTAL AND NEWS SITE:Predictive Analytics Timeswww.predictiveanalyticstimes.comCONFERENCE:Text Analytics WorldSan Francisco and Bostonwww.textanalyticsworld.comOnline training:“Predictive Analytics Applied" - View it on-demandwww.businessprediction.com
- Also applies to fraud detection. If your contacts commit fraud, so might you.In fact, one fraud scheme can't be detected without social data. A group of criminals open financial accounts that improve their respective credit ratings by transferring funds among themselves. Since the money transfers take place only between these accounts, the fraudsters need not spend any real money in conducting these transactions; they play their own little zero-sum game. Once each account has built up its own supposedly legitimate record, they strike, taking out loans, grabbing the money, and running. These schemes can be detected only by way of social data to reveal that the network of transactors is a closed group.
- If your friend's defect, you're much more likely to as well.Friends stick to the same cell phone company. If you switch wireless carriers, your contacts are in turn up to seven times more likely to follow suit.“Birds of a feather use the same phone service provider”http://blog.summation.net/2009/11/birds-of-a-feather-use-the-same-phone-service-provider.html“The Social Effect: Predicting Telecom Customer Churn with Call Data”http://www.predictiveanalyticsworld.com/sanfrancisco/2010/agenda.php#day1-12
- Hebrew University identified 83 percent of sarcastic Amazon product reviews (e.g., "Trees died for this book?").
- “Polite Wikipedia editors are more likely to achieve high status through elections, but, once elevated, they become less polite.”A Computational Approach to Politeness with Application to Social Factors, byDanescu-Niculescu-Mizil et al:http://arxiv.org/abs/1306.6078http://www.mpi-sws.org/~cristian/Politeness.htmlSee also, determination of controversial Wikipedia articles:http://arxiv.org/abs/1305.5566
- PayPal identifies from written feedback customers who intend to leave (aka churn or defect) with 85 percent accuracy.www.textanalyticsworld.com/newyork/2011/agenda/full-agenda#day1-gold
- Microsoft works to predict which people are influential in a social network
- See also, Predicting the Number of Likes on a Facebook Status With Statistical Keyword Analysis:http://minimaxir.com/2013/06/big-social-data/See also, "What Makes online Content Viral?" by Jonah Berger and Katherine L. Milkman, Journal of Marketing Research, American Marketing Association, ISSN: 0022-2437 (print), 1547-7193 (electronic)