From Media Post
by Laurie Sullivan,
Search technology: Some companies will license it, while others build it from scratch. It depends on the egos of executives working at the company. Real-time search and social media have pushed technology to the forefront. Companies need sophisticated algorithms that can sort and index structured and unstructured data.
A recent Accenture report titled “Social CRM: The New Frontier of Marketing, Sales and Service” ties it all together. Joe Hughes, senior executive from Accenture’s customer service and support business, confirms that enterprise companies have begun to build search engine technology that will integrate into software applications and consumer hardware to help marketers, advertisers, agencies and others sort through the mounds of data created by social media.
Hughes defines social CRM as the conversation data from social media networks. And as marketers continue to try and make sense of the mounds of data flooding in from real-time search, Twitter streams, Facebook status updates, and behavioral targeting tags, they will need a faster method to sort, index and access data. Wow, are you overwhelmed yet?
Marketers need technology that can move feedback from customers and call center agents between channels with as much automation as possible. That will become the only way to analyze the data. Natural language query processing will also become a focus, to search through documents of unstructured and structured data as the mounds of social media data continues to mount.
Last year, tools measuring buzz metrics in social networks emerged. This year, the focus turns toward integrating the social data into traditional CRM platforms from companies like software-as-a-service (SaaS) provider Salesforce, which late last year integrated the feature, allowing people to search on that data in real time.
Until now, CRM packages did not allow marketers to view data collected on Twitter alongside traditional queries. But the real-time search movement has sent companies looking to improve search results back to the drawing board to build engines that can process structured and unstructured data, as well as sentiment analysis, taxonomy, classification and entity extractions, according to Hughes. “The strategy of combining structured and unstructured data will become more important,” he tells me.
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