For marketers, a considerable amount of time is spent looking at and studying customer behavior. One technology that helps the businesses in doing so is Big Data analytics. Its stores and evaluates data from various spheres of the business and thus reflects on the aspects that are doing good or need attention. Also, it gives a clear picture of what the customers actually look for in a product or service. 

Much of the analytics depends on a brand’s prior performance. Marketers often analyze what has happened, determine why it happened, and then accordingly adjust the findings. They often take assistance of CRM tools like Salesforce for predictive analytics and sales forecasting. 

So what else we can find here? Well, there’s always a chance to predict the future. Yeah, that’s right! Predictive sentiment analytics are definitely getting attention in the business domain to make businesses more customer-friendly than before.

A Case Study to Support the Fact

A recent study by software advice on the role of online reviews in selecting residential service providers concluded that positive reviews and higher ratings have influenced around 86% of survey respondents while selecting a service provider. They are even willing to pay extra to avail services from providers that are high-rated.


                                                          Source: Software Advice

Moreover, the customers view online reviews as their most valuable and effective weapon in finding and evaluating different options. Where 87% of the people looked for reviews specifying service quality; 78% wanted to know what are the costs involved in such a service.


                                                       Source: Software Advice

The Final Verdict!

This signifies that reviews and ratings are the deciding factors in availing any kind of service or to draw an inference regarding any product, business or service. Thus, analyzing these sentiments becomes a crucial part of the successful flourishing of any business; but more importantly, you need to convert that analysis into revenue.

In the age, where online reviews provide ease for customers to share their opinions with the masses, businesses from all domains - retail & ecommerce, banking & finance, etc. must do all they can to provide memorable customer experiences that encourage positive feedback. But, doing this the old school way can be tiring and is considered almost impossible.

The Problem Here

It is quite possible that you have hundreds or thousands of comments, feedback, reviews, etc. over the web, thanks to our ever-growing social media and reviews sites; then drawing a conclusion by going through all the customers speak is hardly practical.

What Is the Solution to This Big Issue?

News breaks instantly on the web and goes viral in an instant! It is important to keep your eyes and ears open all the time and remain updated with the business-relevant news. But is it enough? Definitely not!!! It is also necessary to analyze what is being said and how does it influence your brand and business. This will help in controlling your brand identity and online brand reputation.

Automating the sentiment analysis process can prove to be somewhat a realistic approach. Although before running an automated script, it’s better to prioritize the sentiments. This can be done based on three factors – Influence, Reputation & Intensity. These factors will help you drill down your negative mentions and draw a conclusion about your brand reputation.

As we know, insight isn't automated; what you do next depends on what you find, thus, it is required that businesses actively monitor and communicate with their reviewers, both positive and negative to identify as where they are going wrong and what makes their customers happy or unhappy.

To help you deal with the problem, here we discuss the simple strategies that can help you predict the sentiments of the customers. 

Strategies for Predictive Sentiment Analysis 

Decision Trees

This is a simple technique that uses data mining and ML technique. Here the process takes place in 3 different parts 

  • The Root 
  • The Branches 
  • The Leaves

Here the root and the leaf ask the question that mostly expects a “true” or “false” response.

Text Analytics 

Many of the big firms still rely on the traditional quarriable relational database management system. Here the data is stored in the well-structured form. Although with big data analysis in the picture, even semi-structured data can do good.

This technique simply works on the analysis of the data collected over different review forms and platforms. Big data analytics in the competitive market have become the need of the hour. 

Neural Networks

Traditional machine learning fails when it comes to handling a lot of data over the course of time. It is here that businesses move forward to other technologies to analyze the data gathered. Many businesses look forward to hiring IT consulting services that can analyze the data and come forward with great conversions. 

Wrapping Up All That Is Said!!!

When you decide to reach an IT consulting firm for some assistance make sure they do use predictive sentiment analysis to help your business outshine your peers. It is very important that everything that is being said or written about you adds value to the business. Although to do such a thing, you need expert guidance and support, so that every mention or sentiment can be turned positively into an opportunity. 

Also Read: Top 5 Trends of Using Advanced Application Development Services and Technologies

We at A3logics ensure that when you look forward for someone to analyze and evaluate the data that you have gathered over the course of time, we are a click away! We understand sometimes you may understand how the sentiments may work in your favor but are not able to decide the perfect action plan. Our team not only analyzes what you are up with but also ensures to provide solutions that only boost your conversion rates. An opportunity to grow! An opportunity to stand tall! An opportunity to build a positive online presence!