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Predictive marketing analytics adds another dimension to social media
Sponsored by IBM
Predicting consumer behavior can be a tricky, risky and expensive proposition. Yet given the massive amounts of incoming data from many and varied channels of communication, companies well know they don't have much choice if they're to remain competitive in the global marketplace. Marketing departments invariably are charged with the high-risk, high-reward responsibility of using analytics to predict outcomes and devising marketing campaigns based on sometimes tenuous information. As a result, marketing and sales strategies that rely on predictive analytics may look more like petri dishes designed to convert prospects, improve brand loyalty and enhance the customer journey. Primary among communication channels is social media, encompassing vast and fertile data real estate where companies can extract information, apply predictive marketing analytics and target specific needs of consumers.
This handbook examines predictive marketing analytics and ways that social media can help companies elevate consumer interactions to a higher and more personal level. In the first feature, professional marketer Matt James discusses how viral marketing on the web can capture an audience's complete attention, build trust and save promotional dollars. In the second feature, news writer Jesse Scardina reports on a lively panel discussion about the shift in consumer expectations during a recent Salesforce-Sales Hacker conference. "It's a relationship business now -- we're not selling products anymore, we're selling relationships," said panelist Teron Douglas, head of financial center sales at Bank of America Merrill Lynch. And in the third feature, consultant Shawn Shell reveals the three key ingredients necessary in concocting an effective brand awareness campaign on social media networks.