Digital PR firms have long sought to gain an edge on the competition by spotting trends early. Some have been using mainstream media to uncover trends while others have begun tracking keywords used in search and social media.
Top digital PR researchers are now developing methods to glean big data from search queries that will allow them to spot new trends and develop projections.
Rex Yuxing Du, University of Houston and Wagner A. Kamakura, Duke University, have developed a model to incorporate data streams of commonly used search terms for new vehicle sales. To test their model, they compiled search queries used in Google, BlogPulse by Nielsen and Trendistic for Twitter. They gathered data from a 7-year period and weighted seven consumer search factors, including words and phrases for foreign brands such as Honda or Nissan, U.S. brands such as Chevrolet or Ford, and European luxury brands such as Porsche and BMW.
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Not surprisingly, search trends correlated to 74 percent of the variation in new vehicle sales. This held true especially when significant events were studied, such as theCash for Clunkers program. Correlating other search phrases and terms, such as an increase in unemployment, was shown to lead to a measurable decrease in the number of searches done on foreign brands such a Honda or Nissan one month later. Similarly, higher gas prices lead to more interest in foreign cars and less interest in brands like Ford two months out.
The researchers suggest that marketers will be able to apply models like theirs to understand which factors most affect future demands for specific products and to predict the potential rise and fall of sales.
This type of information will also allow businesses to confidently develop digital PR campaigns to offset the effect of negative trends.
By Kathy Crosett
[Source: Du, Rex. University of Houston. Kamakura, Wagner. Duke University. Quantitative Trendspotting 2012. Web. 22 Aug. 2012]