Social media has made the leap to becoming a platform for businesses to launch, or to gain a larger following. The many forms of social media have countless postings detailing how the poster is feeling. This text can actually be used to help businesses improve their understanding of the customer’s wants and needs. Because the amount of texts on social media is uncountable, it is a job better suited to a computer program.
Need More Insight Into Your Customers’ Experience?
Big data mining is one technique to gain better insight into what the customer is thinking about a company. Two specific methods are aspect based sentiment analysis, and text analytics. These methods focus on analyzing the text of reviews and posts to gain a clear understanding of how each customer experiences the company’s product or service.
How Does Aspect Based Sentiment Analysis Help Customer Relations?
Aspect based sentiment analysis is a method of distinguishing different facets of the customer experience of a product or service. Instead of simply judging whether a customer had a “good” experience or a “bad” experience. It is difficult for a business to improve, if they are unsure what needs to be improved on according to the customer.
Aspect based sentiment analysis mines the text of a review to determine what went right, or what went wrong. For example, a review might say that the customer enjoyed the food, but perhaps the table was dirty. The reviewer then gave a lower rating as a result.
If the business does not use aspect based sentiment analysis, then there is a good chance they would see the negative aspect of the review. The bigger the company, the more reviews to mine through. Using sentiment analysis, the company can instead have a program break down the individual sentiments of reviews.
How Does Text Analytics Boost Business?
What is text analytics? It is the process of analyzing text to find relevant information. Text analytics is an aspect of big data mining. The text mining process itself has four steps:
1. Information Retrival
Natural Language Processing
Information Extraction
Data Mining
This process of analyzation is not used as often as it could be. The International Data Corporation, or IDC, estimates that barely 1% of all text data is properly analyzed. Text analytics is one method that could raise that percentage.
Text analytics can also help businesses in concrete ways. One prominent way is saving time. A wide range of documents can be mined for important information, without requiring someone to read through each document line by line. Secondly, doing this can lead to an increase in security as the method accurately assesses threats, risks, and compliance. Lastly, text analytics can provide early insight into customer trends.
Will Text Analytics In Social Media Become a Standard Business Practice?
Text analytics and aspect based sentiment analysis are techniques that could be utilized in tandem with growing social media to improve business standing. These techniques get to the heart of customer experiences by analyzing the customer’s own words. The attraction of these analysis methods is that a special program extracts the relevant information.
Sentiment analysis software saves manpower in that a software program is mining the text. Secondly, the software does this task faster than a person could. This supports fact-based decision making.
Social media is often described as unnecessary and a time waste. It is both, and yet it endures as a tool to keep people connected. Businesses have seen social media as a way to connect with their customers. To best leverage this closer connection, it is a good idea to gain a clear understanding of what is really being said.
