How Customer Sentiment Data Analysis Benefits Your Business
Having up-to-the-minute customer sentiment data about your business is essential because today’s marketplace is fast-moving and crowded. For example, 49% of consumers left a brand last year because they felt negative about it. When a shopper feels negative about a brand, it’s nearly effortless to find and switch to a competitor using the smartphone in their hand.
Table of Contents
Collecting and analyzing customer sentiment data keeps you on top of how people feel about your business. As a result, you can make necessary changes fast — before a trickle of lost buyers becomes a flood. The clickable table of contents below will help you skip around to the information that’s most valuable to you.
What Is Customer Sentiment?
Customer sentiment is a measure of how your customers feel about your business. However, most other business metrics are used quantitatively to measure key performance indicators (KPIs), displaying them as numbers or percentages.
But because it’s challenging to apply numbers to feelings, we gauge customer sentiment using a qualitative approach. The most commonly used customer sentiment ratings are:
- Positive
- Normal
- Negative
For applications needing more refined ratings, businesses add very positive and very negative ratings to get a broader view.
The meaning of customer sentiment doesn’t change when it’s called opinion mining. Retail and e-commerce businesses often use opinion mining to discover how customers feel about their brands, products, and marketing efforts.
What Is Customer Sentiment Data?
Customer sentiment analysis evaluates text using natural language processing (NLP) to determine the emotional state of the person writing. The analysis procedure uses data mining, artificial intelligence, and machine learning techniques to examine text gleaned from targeted sources:
- Emails
- Blog posts
- Support tickets
- Web chats
- Social media channels
- Forums
- Comments
- Reviews
The many different sources of text-based customer sentiment data complicate gathering data manually, but there are customer sentiment analysis tools that can help.
How Might a Company Get Some Information on Customer Sentiment?
While it’s possible to mine customer sentiment data manually, the sheer volume of data that needs to be searched makes a manual approach impractical. Algorithms using a rule-based system, an automatic system, or a combination of both are much faster. They can search thousands of pages in minutes. Rule-based systems use vocabulary-based inputs, while automated systems use machine learning.
While you could use code to build your web scraper, using a pre-built bot or having a pre-built bot modified for your custom application is much easier and more cost-effective.
Data or web scraping is the gathering and organizing of information from the internet, making it usable for your business. Web scrapers are used widely by businesses, including Fortune 500 companies.
Scraping Robot is one of the best solutions for scraping web and social sites for data. This software can help you increase your data arsenal and learn critical information about competitors and customers in your industry. With Scraping Robot, you no longer have to worry about all the headaches that come with scraping, like proxy management and rotation, server management, browser scalability, CAPTCHA solving, and looking out for new anti-scraping updates from target websites. Furthermore, there are no hidden fees, monthly costs, or complicated pricing tiers. In addition, they have a reliable support system and 24/7 customer assistance!
Besides managing proxies, other issues that complicate using scraping bots are captchas, blocks, and browser scaling. However, helpful services like Scraping Robot manage all the complexities so that you can enjoy the many benefits of customer sentiment analysis without the headaches.
Types of Customer Sentiment Data
While there are many types of customer sentiment data analysis, there are only five widely used by businesses to gauge the broad range of human emotions.
Fine-grained analysis
Fine-grained analysis models allow you to quantify the qualitative data scraping bots analyze. For example, instead of using the very positive to very negative scale, you could assign numerical values, as the five-star rating system does.
To get even more granular, you could use the numbers 1 through 10, with 1 being extremely negative and ten being extremely positive.
Text analysis tools even allow you to quantify answers to open-ended questions asked in surveys and comments left on different review and social media sites.
Aspect-based analysis
You can dig deeper into customer sentiment data analytics by using aspect-based techniques. Fine-grained analysis gives you the overall picture of how customers feel, but aspect-based analysis tells what category customers feel those emotions about.
Consumers may be pretty happy with your product or service but unhappy with a different aspect of your business, like shipping, customer service, or your stance on sustainability.
Emotion analysis
As much as humans like to think they are governed by logic, astute advertisers have long recognized that human emotions are a more powerful sales driver. When you know which emotions your customers are experiencing, you can start devising ways to channel or change their emotions.
Text-based customer sentiment tools often struggle to classify human emotion correctly, but artificial intelligence and machine learning (ML) programs do much better.
The comment “That’s one bad car!” would be interpreted as a negative emotion by a lexicon-based tool, resulting in a negative rating. But an ML-based customer sentiment analysis tool would analyze the feeling driving this comment as admiration, giving it a positive rating.
Intent analysis
You could consider intent analysis as a step beyond fine-grained and emotional analysis. For example, intent analysis tells you the likelihood of a customer acting like buying now, buying later, or not buying.
You can then:
- Focus immediate sales efforts on the buying now group.
- Use content marketing or advertising on the buying later group to stay top-of-mind.
- Refrain from wasting effort on the not buying group.
Multilingual analysis
Analyzing multiple languages is possible through training ML for each language. However, treating each language separately is required for accuracy because analyzing translations does not yield accurate results.
How to Use Customer Sentiment Analysis to Improve Your Business
How your business can derive the most customer sentiment analysis benefits depends on your business structure, the type of business activity you’re analyzing, and your data source.
You can get a quick snapshot of your business or monitor it over time to observe the results of changes you make. Here are nine possible uses to spark your creativity.
Brand awareness
How do people really feel about your business? What needs changing?
You’ll discover the answers through customer review sentiment analysis and social listening. Researching all the places people are mentioning your brand will give you a much more complete picture than customer feedback alone can provide.
Customer feedback
Analyzing customer feedback from surveys, comments, and external sources lets you keep an eye on developing issues, trends, and needs for new products. You’ll also gain insights into customers’ feelings and language.
Customer service and customer experience
Because of market maturation and saturation, customer service and customer experience have become today’s battleground for many companies. As a result, up-to-date information on your customers’ feelings about your front-line efforts cannot be overvalued. These areas make or break many businesses.
You can analyze information from:
- Chatbots
- Surveys
- Support tickets
- Emails
- Social media
Social media analysis
Social listening on the social media channels frequented by your customers gives you real-time information about what people are saying about your brand, products, and marketing efforts.
Competitor research
Are your competitors spying on you?
If they’re not, they probably should be a little bit. And by keeping an eye back on them, you can gain vital information about their activities, like pricing and buzz surrounding new products. Click here to learn how to use a scraping bot to gather retail price intelligence.
Marketing campaign research
Not all marketing campaigns go as hoped. For example, Burger King caused a tremendous backlash with its insensitive 2021 Women’s Day tweet, “Women belong in the kitchen.”
Ongoing social listening analysis helps you quickly catch developing trends regarding your marketing campaigns. You’ll also be able to observe and use the same type of language your target audience uses to create personalized content.
Product improvement and development
Knowing what customers want improved allows you to develop the iterations and new products that keep you ahead of the competition. You can even analyze people who aren’t your customers but belong to a group you want to penetrate.
Real estate
Scraping data from digital real estate sites helps you appraise and compare property values, estimate rental returns, and forecast market direction.
Evaluating financial and investment opportunities
It can be highly time-consuming to manually gather and analyze the financial data and customer sentiment surrounding only one investment opportunity. Also, options appear and disappear fast.
Mining customer sentiment data will speed up the process and enable you to make informed decisions in the fast-moving finance and investment environment. Click here to dig deeper into financial data extraction.
Final Words
Your competitors are probably busy mining customer data to get ahead of you, and you can too! Companies increasingly realize the value of the many insights they can glean using customer sentiment analysis software. So don’t get left behind.
Although you could build your scraping bot and deal with all the associated issues involved with operating it, it’s faster, easier, and more cost-effective to use or customize a pre-built bot like Scraping Robot. You can start analyzing customer sentiment hassle-free without needing to code or download anything. Reach out to Scraping Robot today!
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