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Social Media Metrics

Boston, September 30-Oct 4, 2012

Blogs, Facebook, Twitter, Foursquare, consumer generated content, - it's enough to make you want to either jump in and play without regard to metrics (experimentation is good!) or simply stick to your knitting and do the best you can with the traditional media you have. Neither of these is optimal. With marketing dollars so tight, it is critical to determine the value of all these emerging media. From reach, frequency and awareness to sentiment analysis and influence graphing, this track is guaranteed to be the most tweeted.

Moderator: John Lovett, Senior Partner, Web Analytics Demystified Moderator: Krista Seiden, Product Marketing Manager, Google

Monday, October 1

Social Media Analysis: From Strategy to Best Practices

Bill Gassman, Research Director, Gartner, Inc.
Carol Rozwell, VP, Distinguished Analyst, Content, Collaboration and
Social Research Team, Gartner, Inc.
Bill examines social analytics and provides advice on how to make it work in your organization. What new data, metrics and analytic functions come with social analytics? What tools and techniques are available to measure the value of social media? How should an organization build a social analytics initiative? What is the true power of chocolate? The perfect session to get you socially and analytically oriented.

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Social Media Metrics Secrets

John Lovett, Senior Partner, Web Analytics Demystified
John is a renowned analytics expert who wrote the book on social media metrics. He shares his best insights on how to analyze and measure the effects of social media and gauge the success of your initiatives. Through case studies and a massive amount of common sense, John demonstrates how to manage social operations with process and technology by applying key performance indicators, and assessing the business value of social media. He also details his techniques for adopting a Social Analytics Framework for understanding evolving consumer behavior necessary to compete in a socially networked future.

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Unstructured Social Media Big Data Analytics: Quantifying Brand Activation and Loyalty

Kimberly Chulis, Co-Founder, Consumer Scientist and CEO, Core Analytics, LLC and Game Loyalty
Big brands want to turn raw social media comment, image and video data from LinkedIn, Facebook, YouTube, Twitter, Pinterest, etc. into valuable and useful business insights. Customer brand activation and loyalty efforts can be measured through advanced semantic and machine learning manipulation of raw, unstructured data. Kim uses healthcare and grocery brand examples to introduce a step-wise process for building a viable, valuable and trustworthy social media datamart.

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Tuesday, October 2

Building a Measurement Organization for the Big Data World

Susan Etlinger, Industry Analyst, Altimeter Group
Sir Tim Berners-Lee recently said, "Change is getting faster." As the customer journey continues to fragment, as data, screens, apps and platforms proliferate, the strain on organizations is starting to show. How can business respond to external signals when social data is locked within silos, interpreted in myriad ways and sometimes even conflicts with enterprise data? In this session, Susan discusses how high-performance companies are organizing for social data, how they are integrating it, what challenges and they're facing and how they are addressing the cultural impact of a faster, more fragmented, data-driven world. It's time to get your social business house in order. Here's how.

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The Community Manager's Best Friend: You and Twitter & Facebook Analytics

Tim Wilson, Director of Measurement and Analytics, Resource Interactive
Community Managers (virtually unheard of a few years ago) are now legion and need to a) determine if the work they are doing is working and, b) validate their existence. You can become an analytics hero armed with the right kind of Twitter and Facebook data. Tim offers up edifying Twitter case studies, an educational knowledge of Facebook Insights and presents a process for working with a community manager to drive an iterative test-and-learn process. All these will help when you discover the Facebook party line doesn't always square with Facebook reality and some retweets are more equal than others.

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