Meeting Archive:
Webcast: Mining Social Data for Insights


Meeting Description:

 According to Digiday, “48% of digital marketing executives surveyed said they focused ‘relentlessly’ on building customer insights, and yet, few are executing those strategies in meaningful ways.” A mind-boggling amount of data is being created every second, increasingly coming from social properties.

By 2020, Gartner predicts, data volumes will grow to 20x of today’s volumes. Social media provide a vast wealth of data that is both personal and insightful and can tell you a lot about your brand—but even more about your customers.

Before this data becomes overwhelming for your organization, come to this session to hear top tips from social media analysts to find out which data matters and how to use it across functions to uncover new opportunities for your business.

Details
Date: Thu, Apr 24, 2014
Time: 02:00 PM EDT
Duration: 1 hour
Host(s): Oracle Social Cloud
 Presenter Information
Tara Roberts, Vice President, Oracle Social Cloud
Speaker Photo

Tara leads the product management team responsible for listening and analyzing social conversations and other unstructured data. She also manages partner relationships for Oracle Social. Prior to joining the Oracle Social Cloud team, Tara led Oracle’s social CRM product management team. Prior to Oracle, Tara led the Siebel Life Sciences product management team, driving product development efforts for Siebel’s Pharma, Medical and Clinical product lines. Tara has a BS degree from the University of Virginia and an MBA from the Wharton School of Business at the University of Pennsylvania.


Mehrshad Setayesh, Vice President of Software Development, Oracle Social Cloud
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Responsible for managing several distributed teams tasked with creating advanced data collection, processing, analytics, and distribution systems with the goal of scaling from a current hundred of millions of daily messages to billions of global social and enterprise text messages analyzed using LSA (Latent Semantic Analysis) and NLP (Natural Language Processing) with the goal of optimizing signal to noise ratio followed by large scale distribution within the Oracle cloud and on-premise eco-system.