Why would you use the 'Voice of Customer' dictionary in SAP HANA Text Analysis?

The 'Voice of Customer' dictionary in SAP HANA Text Analysis is specifically designed to extract sentiment from customer feedback, especially from unstructured data sources like social media. This capability allows organizations to gauge customer opinions, feelings, and attitudes towards products or services based on their feedback. By analyzing this sentiment, businesses can better understand how their offerings are perceived, identify areas for improvement, and make data-driven decisions to enhance customer experience.

Using this dictionary is vital for recognizing positive, negative, or neutral sentiments expressed in customer comments, which can be critical for brand management and customer relationship strategies. It focuses on capturing the emotional tone of the customers' language, providing insights into their experiences and satisfaction levels.

In contrast, while other options may represent various functionalities of text analysis, they do not specifically relate to the intent of the 'Voice of Customer' dictionary, which is primarily centered around sentiment extraction. For instance, identifying close matches in words relates more to spelling correction than sentiment, pinpointing customer problems focuses on issues rather than feelings, and extraction of common entities pertains to categorization of data rather than the emotional context. Thus, sentiment extraction stands out as the primary function of the 'Voice of Customer' dictionary.