Table of Contents
show
Sentiment analysis is a technique that can break down and analyze comments on your blogs for opinion analysis: positive, negative, neutral, and beyond. Known as opinion mining in some worlds, it’s an extremely helpful mechanism that can work on truckloads of data to analyze the ‘sentiments’ behind all the statements made all across the web. Primarily on blogs, YouTube comments, Yelp reviews, Facebook comments, and thousands of tweets.
Building a content strategy is a key element in marketing. So what is a sure shot way of building an impeccable blog and understanding what your audience seeks? Analyzing how they are communicating with your content. At every stage. And modifying your craft accordingly. And the first step to analyzing sentiments online is to first scrape relevant data. Blog comment section data extraction is the initiation stage of understanding what your audience seeks. Let us break down why we need to scrape data to identify consumer behavior and how we can go about it. Blog comment scraper can help gather comment data at your desired frequency.
How Emotions Guide Purchase Decisions
Consumers are more than just data points. Humans are rarely that simple. Hence, understanding their complex emotions requires machine learning and predictive analysis algorithm which is aided by scraped data. Emotions are the number one factor in making purchasing decisions. With ease of access and digital penetration, consumers have no qualms about sharing what they truly feel. It quite literally pays for brands to have a pulse on how their products make people feel. Those feelings can be translated into actual data points. Sentiment analysis is based on four values that make up the scale:
Positive – I cannot stop gushing over this burger.
Negative – The worst customer care in the world!
Neutral – Too many armchair activists are opining on critical issues.
No Sentiment (default value) – How sad! (too little data to be construed as anything constructive in terms of sentiment)
Sentiment analysis for literally every sort of public opinion. Automate your sentiment analysis across all profiles! If you want to streamline this whole process, there is literally no other way other than automation. This means that absolutely no red flags will be missed and you will be able to flag all discrepancies.
Automated sentiment analysis is available for blog comments, tweets, mentions, and a gamut of other important things. Once all the data (relevant comments, in this case) is parsed, automated sentiment first studies all comments then it applies an emotion based natural language processing. This is where sentiment analysis gets somewhat tricky. The sheer volume of emotion related terms doesn’t always tell the full story of how your customers really feel.
For example, fans of hugely popular web series use internet lingo to express how they truly feel. Throwing around words like sick, cry, depressed will obviously through your automated tool into a tizzy. If you see those terms pop up in your mentions without any context, you might go into a tizzy too. Sarcasm can also create confusion when it comes to sentiment analysis. When somebody tweets “Don’t you just love it when you lose your luggage after a 16 hour flight?” they obviously aren’t particularly euphoric about their airline experience. These outliers need to be accounted for.
A combination of manual listening and machine learning is absolutely ideal for getting the most ‘on point’ sentiment analysis possible.
Why Businesses Must Scrape Data for Sentiment Analysis
The analysis gleaned from sentiment analysis can translate directly into actual sales for your business over a course of time and it is an essential component of brand health.
1) Customer service
As must be already understood, sentiment analysis gets brands to keep a closer eye on wherever they are mentioned. This means being more attentive to concerns and feedback. Responding to them timely will have an immediate effect in establishing you as an empathetic brand.
2) Better products
Your audience is your best critic. You always have to rely in what exactly is that they’re seeking. Taking their cumulative feedback into account will help you up-sell.
3) Comprehensive competitive analysis
Your business cannot work in silos. You need to know hoe customers are reacting to all the veterans in your industry. Especially when they are looking for recommendations, multiple brands are tagged together. By scraping data for sentiment analysis, you can get a better understanding of why someone prefer their product to yours.
4) Tone of voice guideline
Establishing the tone of voice of your brand can be a daunting task. But, you can now just see how people are reacting to different tones in your blog and find a voice that resonates with them the most. It could be caring, humorous, informative.
5) Brand health
Sentiment analysis is extremely important when your business is changing dimensions. For example, product launches, pricing changes and any other big announcement could see a significant upheaval in your brand sentiment. Comment scraper can help evaluate brand health for businesses of all sizes.
How to Scrape Data for Sentiment Analysis
Navigating through reviews, comments, and feedback is a humongous task. But what if we tell you (we already have!) there is an even easier way to utilize sentiment analysis? You guessed it. Data scraping! Data scraping is the automated process of gathering large amounts of, well, data about any subject. In order to parse data for sentiment analysis, all you need is to instruct the scraper to search for the data you need. So, if you want all the comments on every blog written on sentiment analysis, a comment scraper can do a sweep of all these comments, grab it, and arrange it into a neat file. The benefit of comment scraper on the working end of sentiment analysis is the enormous time saved on the part of a researcher. Web crawling and scraping data feeds is a natural first step in the analysis process.
Wrapping Up
Our emotions and words are the mightiest and most resourceful of all things at play. They can control you or you can control and capture it and translate it into something tangible. Consumers always believe that corporations and big businesses are just faceless money making machines. This lends them a garb of empathy. 2021 is no time to shy away from sentiment. Sentiment analysis helps companies, big or small and it also encourages the consumer to keep providing valuable feedback. Because guess what? If your marketing team takes all the quick actions of a comment scraper and the positive outcomes of sentiment analysis, you are already leagues ahead of the competition. But don’t just take our word for it, scrape, analyze, and see.
