Data analytics is a broad field that requires attention to a lot of aspects. Specialists would agree that analyzing data and trends, even using an all-automatic tool, is not everyone’s cup of tea. It requires exceptional focus and immense understanding of why is the data being analyzed and how can the analysis be used to generate revenues and drive initiatives.
Once you have a sound understanding of what needs to be achieved, the result of the analysis can provide fruitful benefits. It is the desire to increase these benefits that researchers are coming up with new and innovative ways to make the most of the available data. And, this pursuit has given rise to sentiment analysis.
Sentiment Analysis Is the Buzzword
The name itself is sufficient to give you an idea about what is being analyzed. But, you would certainly curious about how is it possible. Sentiment analysis is performed on a data set that comprises customer reviews. Now, customers generally express their sentiments (happy or sad) in the reviews that they post about a product or service. The data analysts make use of these sentiments to identify the trends, the success parameters, etc.
Let’s try to understand the concept with the help of an example. A company is selling a bedsheet “X” and another bedsheet “Y.” These two products are hot-selling and as a result a lot of reviews are posted on different mediums about these products. So, you hire a company providing big data solutions India to do a sentiment analysis. The reviews in this case become the data source where sentiments are being expressed.
The first step in analysis is to identify the traits with keywords. Traits are features of a product. In this case, the traits can be fabric, color, print, etc. Identifying these helps in narrowing down the reviews and streamlining them to have a clear understanding of negative traits and positive traits.
The second step is to identify the related sentiment. This is done by detecting the relevant words used in the review. In the current example, a customer might post a review saying, “A great product.” The word “great” signifies a happy sentiment and therefore denotes a positive review. Similarly, if a customer writes, “Waste of money. The fabric is third-class,” the keyword “waste” signifies sad sentiment and therefore denotes a negative review.
The data (customer reviews) which were otherwise just some content posted on the website for other users is now meaningful data for the company. These reviews were previously acting as a deterrent or motivator for your customers but were not of much use to you. But, with the help of sentiment analysis, you are now able to use these reviews for your benefit.
The above example helped in recognizing the aspects that can be analyzed. Considering the same example, if the number of positive reviews are more then, your product is not only popular but popular for good reasons. Similarly, if the negative reviews are high. Then, the so-called popularity might soon subside and this is a trigger for the company to act.
This is where the traits come into picture. In the above example, the traits like color, fabrics, etc. were identified. So, now if the review is “Waste of money. The fabric is third-class,” the hired company providing big data solutions India can relate the features (fabric) to the sentiments (waste) and identify which trait is the problem area. Depending on the nature of the product or service, the company can deal with the issue. In this case, the fabric is the issue, so company can provide alternative products with better fabrics.
A good analysis should be quick to understand and what better way to understand data than classic histograms and pie charts. The solution providers are making use of these classic methods to present their revelations.
One innovative approach is to show the traits identified on the basis of the review in a tabular form, then show the negatives and positives as histograms where each can be compared. The histograms are accompanied with keywords depicting the sentiments. These visual aids provide a clear picture about the performance of a product and help a company decide the future course of action on the basis of a small presentation that is backed by strong data and realistic analytics.
The sentiment analysis is trending as the approach in many industries predominantly in e-commerce business where customers rely heavily on reviews of a product or service. Such analysis help companies create strategies that are more centered to what customers want. These also help in addressing customer concerns because the problem area is more prominently identified. The benefits of sentiment analysis are proven and their effectiveness has contributed to its popularity.