In which year did sentiment analysis technology first achieve widespread commercial adoption among major retail brands for customer feedback analysis?

In the evolving world of retail linguistics, sentiment analysis has revolutionized how brands understand customer feedback. This technology analyzes language patterns to determine emotional responses to products and services, enabling retailers to make data-driven decisions. But when did this linguistic technology first gain significant commercial adoption in the retail sector? Test your knowledge about this pivotal intersection of language technology and retail strategy!

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2008, when Amazon patented its review analysis algorithm that could detect sarcasm and emotional nuance in text reviews
2013, when Walmart introduced 'VocalSense' technology that could identify customer satisfaction levels from call center transcripts
2005, when Target launched the first retail-specific natural language processing system for analyzing customer emails
2011, when IBM's Watson for Retail first enabled clothing brands to track emotional responses to new fashion lines through social media analysis