In the digital age, business organizations are empowered to analyze their live feeds, comments, and tweets to understand the sentiments of potential audiences and consumers. Once a customer has a positive experience after a purchase, his/her chances of coming back increase to about 85%. However, when they encounter a negative experience, the customer retention rate reduces to about 70%.
Customer sentiment is an efficient factor in driving potential customers’ purchase decisions. Sentiments have the potential to destroy or enhance the reputation of the business. While the sentiments are not upfront, they help in analyzing the behavior of the customer. In addition to this, they impact what the potential consumers are purchasing, and the time of purchase, to name a few. Before we dive into advanced analytics solutions approaches to get better insights, let’s find out what is sentiment analysis.
What is sentiment Analysis?
Sentiment analysis is the process of diagnosing the negative and positive sentiments present in the text. Different businesses are used to diagnose the sentiment present in the brand reputation, social data, and understanding of the targeted audience. Customers nowadays are expressing their feelings and thoughts more openly.
So, sentiment analysis has become a prominent tool to understand and track sentiment. It is useful in the Analysis of consumer feedback automatically. In addition to this, it helps analyze different opinions present in the survey responses. Also, through sentiment analysis, you will be capable of tracking other social media conversations.
Besides this, the brands will have the opportunity to understand what makes the customers frustrated or happy. So, they will be capable of tailoring the services and products to accomplish the customers’ needs.
As you adopt the below-mentioned approaches, you will be capable of seeking more insights:
Monitoring the perception of the potential customers
The primary option to make the right use of sentiment analysis is monitoring the perception of the customers. It helps in building the brand image of the business. Through sentiment analysis, you will have the opportunity to observe the online audiences, current customers, social media influencers, and industry experts for the recognition of discussions, that are going around the brand. For instance, there are about 16,000 reviews about a product, which comprise authentic and valuable opinions.
Sentiment analysis solutions help in the consolidation of the reviews. In addition to this, it helps in the extraction of different customer opinions. Apart from this, sentiment analysis is beneficial in hassle-free dissection. In addition to this, sentiment analysis provides the capabilities of processing massive data information, which is used for diving into the perception of potential customers.
Customer Service
Excellent customer service helps in enhancing revenue. However, poor customer service is detrimental to the business. As you perform the sentiment analysis, it is possible to understand if more customers are giving similar feedback and if you can analyze the specific pattern.
Plan product improvements
Every business aims to develop a product, that caters to the needs of the potential audience. The owners of the business want to see the queue of customers before their stores. The best option to do is to understand the needs of the potential audience. It is where sentiment analysis comes into being. Sentiment analysis is beneficial in learning about the improvements in the products. It is possible to use sentiment analysis which helps in analyzing Amazon reviews to understand the preference of the brand.
There are chances for filtering every comment through sentiment and topic. So, you will be capable of understanding the essential features and the ones that should be eliminated. The product development team can make the right use of sentiment analysis to understand the features, required by the potential audience.
Also Read: Text Analytics in Revenue Management System
Prevention of Future Crisis
Sentiment analysis offers a helping hand in the identification of different problems before they turn out to be a huge issue. Preventing and spotting a potential crisis happens to be one of the primary benefits of sentiment analysis. Once a brand tracks the emotions expressed by potential customers, it can prevent the occurrence of a colossal disaster, which would happen due to negative comments.
In addition to this, sentiment analysis is useful in backtracking the data. It helps you to get the data belonging to a specific period to conduct a trend analysis. Such type of information is helpful to the business organization in taking charge of the circumstance, thereby fixing it. With the identification of sudden negative online comments influx, the brands can recognize the crisis at ease.
Getting Competitor Insights
Competitor analysis happens to be another reason why it is recommended to opt for sentiment analysis, following the keywords relevant to the industry. Different brands make the right use of sentiment analysis to understand the needs of their customers. In addition to this, they need to find other strategies so that they can make the proper use of this information for changing the approach.
Such positive sentiments are useful to the brands to figure out the reason why customers are gaining success in the market. Negative sentiments help reveal different opportunities for the brand so that the void is filled.
Conclusion:
Till now, business organizations have adopted different regular techniques to analyze sentiments. Hence, focus groups, questionnaires, surveys, telephonic interviews, and discussions were sufficient for understanding the potential audience’s sentiment. With the combination of available data and the influx of the internet, artificial intelligence and machine learning technologies are becoming widely popular for the analysis of sentiments from a plethora of text, ensuring higher accuracy.
Text analytics solutions have a significant effect on brand perception. The algorithm which is used in the sentiment analysis is useful to different brands to enhance their reach. Various platforms are tools used in sentiment analysis that offer the required sources to start the process without delay.
FAQ’s:
By using natural language processing techniques, traders aim to understand whether the overall sentiment is positive or negative towards a particular asset or market. This helps traders make informed decisions about buying or selling securities based on market sentiment.
Detecting sarcasm with high accuracy remains a difficult task in natural language processing. Sentiment analysis can struggle to detect sarcasm accurately. Sarcasm often involves expressions that contradict their literal meaning, making it challenging for sentiment analysis algorithms to interpret correctly.
Several sentiment analysis tools are available in the market, catering to different needs and preferences. Here are some popular ones:
MonkeyLearn
IBM Watson
Azure Text Analytics
Lexalytics
RapidMiner
Sentiment analysis is crucial for businesses because it helps them understand customer sentiment, monitor brand reputation, conduct market research, improve customer service, and stay competitive in their industry.