One of the most important principles of developing and implementing a differentiated customer experience is simply understanding how customers perceive the current offering. To mine this data, brands worldwide are turning to technologies that allow them to dig into qualitative data to track and analyze customer sentiment and craft processes accordingly.
One such platform that allows for this kind of analytics, CloudCherry, recently made improvements surrounding a substantial challenge facing this kind of data analytics. Because these text samples—and language as a whole—are so influenced by outside factors like culture and context, the accuracy of this analysis can sometimes be called into question as it relates to determining the sentiment of consumers.
To tackle this issue, the platform allows clients to choose from the leading analysis tools on the market, Microsoft Azure, IBM Watson, and CloudCherry’s proprietary solution, to meet their specific needs. Because each tool offers slightly different strengths and challenges, businesses can tailor text analytics according to their specific circumstances.
“The need for brands to understand and analyze customer sentiment using text analytics is quite unprecedented,” said Vinod Muthukrishnan, co-founder & CEO, CloudCherry. “With more customers commenting about their experience in detail via free-text comment boxes and also turning to social media to engage with brands, there’s a ton of valuable insights that businesses can extract to shape customer experience. And by using IBM Watson and Microsoft Azure on our Text Analytics platform, brands can make the most of these conversations, and obtain a highly comprehensive and accurate understanding of customer sentiment and behavior.”
With the rise of data analytics in both text and speech, brands are now armed with the technology needed to precisely determine the cracks found in their CX offerings. Especially crucial in the customer service sphere, this kind of measurement can create a substantial impact on a company’s relationship with its customers. Brands like Amazon and Starbucks have shown a knack for understanding customer sentiment, and have grown into giants within their respective industries as a result. Through the leveraging of text analytics, brands can now tap into this rich data to build that same kind of strong relationship with consumers.

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