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This is a guest post written by Victor Trac, Cloud Architect at Bazaarvoice.
Bazaarvoice is a company that people interact with on a regular basis but have probably never heard of. If you read customer reviews on sites like bestbuy.com, nike.com, or walmart.com, you are using Bazaarvoice services. These sites, along with thousands of others, rely on Bazaarvoice to supply the software and technology to collect and display user conversations about products and services. All of this means that Bazaarvoice processes a lot of sentiment data on most of the products we all use daily.
Bazaarvoice helps our clients make better products by using a combination of machine learning and natural language processing to extract useful information and user sentiments from the millions of free-text reviews that go through our platform. This data gets boiled down into reports that clients can use to improve their products and services. We are also starting to look at how to show personalized sortings of reviews that speak to what we think customers care about the most. A mother browsing for cars, for example, may prefer to read reviews about safety features as compared to a 20-something male, who might want to know about the car’s performance. As more companies use Bazaarvoice technology, consumers become more informed and make better buying decisions.
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