Sentiment analysis interprets a document’s tone, mood, and general sentiment to extract meaningful data automatically. In this article, we introduce a classification scheme that can group the vernacular substance into six categories: positive mood (happy), negative mood (sad), neutral mood (neither), satisfaction, displeasure, and anger. This classification scheme will help businesses optimize their usage of sentiment analysis for specific business goals. It is crucial that companies collect the most accurate data to make sure they are using sentiment effectively and correctly while maximizing analytics potential. It can be helpful in many aspects of the business, including marketing, customer service, business planning, and more. Here are the types of data companies may want to collect to optimize their use of sentiment analysis:
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1. Surveys
In an ideal scenario, a company would have collected the data needed for sentiment analysis before the sentiment analysis was done. For example, when a customer calls in with an issue, the call center agent may ask, “How likely are you to recommend this product?”. The call center agent can then enter the answer into his system and use it for future interactions with customers (a feedback loop). The survey is particularly helpful when companies need to collect a wide range of data, like how customers feel about different features and attributes of the product or service. Survey data could also be used to guide product development and marketing campaigns. For example, a company may want to know the specific reasons that made customers unhappy with a previous version of the product. They can make sure those reasons are not present in the new version and can be better prepared with marketing materials explaining why those issues were fixed.
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2. Customer reviews
Customer reviews are a great source of information. The most important thing is to understand the customer’s question in the review and what efforts a company can make to answer that question. For example, “How likely are you to recommend this product?” does not mean much. If a person reviews their experience with a product for “how likely would you be to recommend”? Then it’s much more useful.
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3. Social media comments
Social media comments can be a great source of sentiment data and are available to everybody. For example, companies like Yelp, Facebook, and Twitter allow users to post reviews from their experiences with a company or product. Additionally, companies can create hashtags for their products on social media platforms. These hashtags should be carefully selected to capture the customer experience in the study. For example, if a company wants to know what people think about its brand, it could create a hashtag such as #company. Alternatively, if a company wants to know what people think about its products, it could create a hashtag such as #productname. Any posts that contain the hashtag will then show up on the company’s account. Hashtags can be extremely useful because they allow companies to filter out irrelevant information while searching for relevant information.
4. Customer and Sales data
Customer data is the most important piece of information that companies can collect. This can come from surveys, social media, and customer reviews. However, this data is critical as it gives companies insight into how the public perceives their products. Likewise, sales data will help companies see what customers are buying and how much they are buying. This can be very helpful when a company is trying to determine how much to invest in new marketing initiatives or improve their existing marketing campaigns.
5. Product data
Product data can be helpful if a company wants to know how customers feel about the quality of a product. Information like this will allow companies to tweak their products further and improve their end-user experience.
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6. Brand perception and reputation data
Brands play an important role in a company’s success and overall reputation in society. A good way for companies to measure brand perception is by asking customers what they think of them. This can be done through surveys or reviews from social media platforms such as Yelp, Facebook, Twitter, etc.
Conclusion
While sentiment analysis is useful in many aspects of business, it should be used with caution and only surpassed by other tools. The work that researchers on the topic have done has made a major contribution to society. However, because of the size and scale of many companies, there will always be room for improvement.
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