Managing marketing: putting the puzzle together
Social media analytics and marketing
Estimates for the global market for social media analytics in 2014 range from just over a half billion to nearly $3 billion, with predictions for annual growth over the next five years ranging from about 25 percent to more than 35 percent. Initially, organizations used social media as a channel for customer service, but much of the demand is now being driven by the use of social analytics in marketing.
Social analytics includes listening, in which organizations monitor comments about their products or brand that are made on Facebook, Twitter and other online communities. The information gained can be used by marketers to segment potential customers or launch campaigns. Analysis of social profiles also can be used for segmentation and scoring of leads. Organizations can also track the extent to which potential ?customers are sharing content about their brand with others, and analyze the results of ratings.
It’s important to use social analytics in conjunction with other metrics. “Sentiment analysis algorithms have some limitations,” says Kashyap Kompella, senior industry analyst with Real Story Group. “Those analyses can trip over sarcasm or satire, and many of them can analyze only English. But when the data points from social media analytics are used with other metrics, they can enrich understanding.”
Social media analytics software also has been limited in its scalability and its ability to analyze both unstructured and structured data. A new offering, muWebfluenz E from Mu Sigma is aimed at large companies that want to analyze both structured and unstructured information from the Web and internal sources.
“MuWebfluenz E is uniquely placed with its capability to allow enterprises to better segment customers combining attitudinal information from social comments like interest categories, sentiment, etc., and behavioral information from CRM and internal systems,” said Deepinder Dhingra, head of strategy and products at Mu Sigma. A combination of software and custom services, muWebfluenz E uses natural language processing and advanced text mining techniques as well as other analytics.