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Measuring social media success
With marketing dollars so tight, it is critical to determine the value of all emerging media. From reach, frequency and awareness to sentiment analysis and influence graphing, this track is loaded with shortcuts, tips and tricks for getting a handle on the conversation in the marketplace. This track is guaranteed to make you think, to give you a long to-do list and to be the most tweeted.
Tuesday, October, 01, 11:30am – 12:10pm •Back Bay
John Lovett, Senior Partner, Web Analytics Demystified
Even the most efficient social media programs operate at a frenetic pace today. It’s not uncommon for organizations to deliver content and conversation across the vast multitude of platforms by delivering cross-channel campaigns that leverage Twitter, Facebook, Pinterest, Instagram, YouTube, mobile apps and fixed websites simultaneously. Each social media campaign and every social interaction requires micro level management to execute and detailed metrics to quantify success. Yet, all too often in the hectic maelstrom of sustaining social operations, teams lose sight of their macro-level goals. In this session, John Lovett, author of Social Media Metrics Secrets, will demonstrate how leading organizations can execute at the speed of social, while supporting a long-term strategy that’s grounded by social analytics.
Tuesday, October, 01, 1:30pm – 2:15pm •Back Bay
Analytics of the Future
Brian Melinat, Social Media Listening Consultant, Dell
Helping business leaders understand how social media impacts brand health requires baselining the long-term impacts of overriding campaigns and overlaying specific, social events. Sometimes popular, short hand calculations to calculate Customer Lifetime Value can be useful, but these methods have flaws. Brians review various means of measuring social media ROI from cutting edge approaches to media mixed modeling to simplified calculation methods and outlines the benefits of each. Then, he takes a look at the transformation analytics will make in the next few decades, from influencing business decision makers to actually owning the decisions.
Tuesday, October, 01, 2:20pm – 3:00pm •Back Bay
Complex Metrics Help Simplify Publisher’s Data
Todd Schauman, Manager, Digital Analytics, The Christian Science Monitor
Todd showcases how creating custom variables and custom metrics can allow basic/beginner users to easily leverage data and make well informed business decisions. See how the Christian Science Monitor created a new set of reports by combining three standard variables into one, thus creating a new calculated metric. the result? Actionable data for its writers. Todd describes how this new metric provides insight into trending article content, top daily/weekly/monthly content and all with the ability to filter by author or section.
Tuesday, October, 01, 3:30pm – 4:10pm •Back Bay
Evolving General Mill’s Data-Driven Culture
Andrew Janis, Consumer Insights, General Mills
General Mills has been advancing their traditional, highly successful brand marketing organization into the always-on, digital and data-driven environment. By blending brand, social, email, agencies and site teams, and rallying around new digital business intelligence opportunities, an internal evolution is in process. Andrew describes how educating stakeholders on the possibilities possible and providing strategic direction on using consumer behavior data can spark a large organization to make a huge shift and get people on board with the vision. Then, he he gets specific about translating this crusade to the direct support of the campaigns from data for campaign ideation, campaign optimization in market and post-campaign insights generation.
Wednesday, October, 02, 2:20pm – 3:05pm •Back Bay
Augmenting Forecasting with Social Media Data
Gary Angel, Partner, EY
Building predictive models is a great way to drive better reporting AND cross over the barrier from reporting to analytics and traditional forecasting is significantly enhanced with Social Media research. Gary shows the essential elements in building a product launch or campaign forecast, including modeling of historical, econometric, sales, and brand data. But he takes this well beyond the traditional modeling realm by showing how Social Media sharpens forecasts and creates predictions in areas where little historical data exists. Learn how to move your reporting from building thermometers (what happened) to building barometers (what will happen).
Wednesday, October, 02, 3:30pm – 4:15pm •Back Bay
Facebook Media ROI
What if your Facebook community was driving 2 to 3 times more revenue than you thought? Would you be a happier than a body builder directing traffic? Every Facebook post has brand ripple effect. This impact is measured in data you easily have access to. Daniel and Cat describe how regression analysis and coefficient thresholds can help determine the credit you attribute to an original FB post as well as spotting and measuring the ripple effect across other marketing channels. They show that clickers may drive $1,000 in revenue, but you can show your Facebook post made $4,000. You’ll be happier than Gallagher at a Farmers Market.