I'll be participating on panels at each conference, moderating the OMMA Metrics panel.
Here are the details, and I hope to see you there!
Register here: https://www.mediapost.com/events/index.cfm?/showID/OMMABehavioral.11.SF/type/Register/itemID/2073/OMMABehavioral-Register.html
OMMA Metrics will take place on July 21, 2011 San Francisco at the JW Marriott Union Square
| Panel: Predicting Future Behavior: Applying Rigorous Quantitative Methods for Maintaining or Creating Opportunities to Generate Profitable Revenue | |||
| While the analytics industry often speaks of complex mathematics, business reality dictates that advanced modeling and statistical concepts need to be “dumbed down” for stakeholders. In fact, few people understand truly advanced concepts like multiple logistic regression, chi-squares, and Gaussian and non-Gaussian statistics. Thus, while people in the industry talk a lot about “predictive analytics,” few actually successful deliver business value by telling business people about their fat tailed, stochastic, and autoregressive conditional heteroskedastic volatility model for online advertising in ad exchanges. Yet, high-order mathematics and statistics exist in many companies. These models are created by highly-educated people who do complex work, and then must explain in business language why their hard work matters and how it can help make their companies and/or clients money. In this session, you’ll hear from experts who create and use verifiable and statistically-valid quantitative methods. You will learn from professionals who have successfully crossed the academic chasm of mathematical research ideals to the other side: using statistics and modeling to generate quantifiable profit. | |||
OMMA Behavioral will take place on July 20, 2011 San Francisco at the JW Marriott Union Square
| You Might Like This…The New Age of Discovery in Recommendation Nation | |||
| Marketers aren’t the only ones getting overwhelmed with data sources. In the one-click-away Internet publishers and retailers are struggling to increase engagement by helping users discover more of what they want and need without going elsewhere. The recommendation engines of old now have the jet fuel of Facebook ‘Likes,’ the social graph and now mobile geo-location added to the blend. And now the art and science of discovery has expanded far beyond retail and into video, devices and content. Some publishers use third party engines to help extend their content reach into other Web sites, while others are leveraging their own engines to target ads for clients. And now personalized recommendation engines are emerging in video and mobile platforms to help consumers discover products and resources. But how does this art and science of discovery ultimately help content providers, e-retailers and the marketers who work with them better understand their audiences and craft smarter ad and content distribution strategies in the cluttered digital environment? | |||
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