Probably, you may have heard the term “sentiment analysis”, but never really paid much attention to how important it can be for your company?
But you should! When it all funnels down to branding, having an excellent product or an outstanding service is not enough. You have to mine your customer’s opinions with sentiment analysis, and if done properly, it can open gold mines.
So, to determine the true impact of a brand, it’s imperative to leverage an advanced sentiment analysis solution that offers much more profound insights that have a genuine effect on your action plan of growth. Herein, we have pocketed 14 unskippable insights that a reliable sentiment analysis software shares.
But, first thing first!
Defining “Sentiment Analysis”?
As the term suggests, Sentiment refers to the positivity or negativity expressed in a text. Therefore, sentiment analysis is an approach to understanding feelings expressed in data through Machine Learning tasks like text analysis, video content analysis, natural language processing, semantic clustering, etc.
Precisely, sentiment analysis software provides organizations with data-driven insights to understand present market trends, predict new customer trends, service improvisation plans, gaps in customer engagement, and insights to enhance employee experience.
One of the fascinating facts about sentiment analysis is how far-reaching and versatile mining customers’ opinions can be. So, to get the most of it, it’s essential to know what features of a sentiment analysis your software should have.
Advanced Features of a Sentiment Analysis Platform
A sentiment analysis dashboard can provide businesses with granular insights from the processed data. To do so, it uses the below-listed features; let’s look at them!
# Feature 1: Ability To Choose Industry-Based Aspects
The precision and accuracy of your insights from any Machine Learning platform come from its named entity recognition (NER) capability. The Named Entity Recognition ensures every entity like organization, person, logo, place, currency, etc. related to the domain is extracted for semantic and sentiment analysis.
Every industry has its own aspects, like a bank will have aspects of its industry like salary, money, withdrawal, deposits, etc whereas a restaurant will have aspects like the ambiance, price, drinks, food, customer service, etc. So, an advanced sentiment analysis platform will not just allow you to choose industry aspects based on your industry but also custom-create aspects that are unique to you.
# Feature 2: Ability to Evaluate Multiple Social Media
An entrusted and advanced sentiment analysis software will allow you to gather and analyze data from multiple sources, including text and video-centric. This includes social media platforms to online platforms for product reviews, like Facebook, Instagram, Amazon Review, Twitter, and many others added to the list.
# Feature 3: Ability to Analyze Multiple Language
A sentiment analysis tool can collect customer and employee insights in multiple languages. But, the real challenge is that they offer multilingual analysis based on translations. A truly advanced sentiment analysis platform will process and analyze data in multiple languages by using a speech tagger for each language separately.
# Feature 4: Ability to Analyze Video Content
To have a competitive edge, it is necessary to understand your customer base and the market perception of your product and brand. And, to make this possible, you need to clutch as much information as possible. After all, the more varied the data sources, the better.
In this context, the sentiment analysis software must also be able to extract findings from video content. The video AI allows you to get insights from YouTube video analysis or TikTok insights as easily as from text-based sources like Twitter.
# Feature 5: Ability to Create Custom Models, Entities and Adjust Sentiment Score
Another sophisticated benefit of truly advanced sentiment analysis software is that it helps you create custom models to meet your needs and adjust your entities accordingly. Also, it allows you to see insight from data filtered by custom filters.
For instance, in an employee setting, it can allow you to search for sentiments for those who worked for a specific time, were male, and were part of the supply chain department. Moreover, it allows you to assign sentiment scores to some exact keywords or phrases that may be very specific to your brand, industry, or audience.
Key Insights a Sentiment Analysis Platform Provides
A sentiment analysis offers you insight based on sentiment by language, data source, and the general sentiment overview. You have access to analyze entities, get the granular aspect-based sentiment, observe their frequency and witness the changes in sentiment over time.
Not to forget, there are many other key insights you can get. We will discuss them in all detail below:
# 1: General Sentiment Overview and Sentiment Score
The insight generated by a sentiment analysis API is the general sentiment overview of the subject you are analyzing. The sentiment analysis software will vet the internet for all relevant data or will analyze a data sheet that you have manually uploaded. It will also give you the number of total documents it has analyzed and the sentiments in color codes.
Here, it means green for positive, red for negative, and blue for neutral.
# 2: Aspect Occurrence Frequency Rates
Another unskippable thing about sentiment analysis is how frequently an aspect appears in the data. This provides you with an idea of which aspects of your product, service, or overall brand, are turning into the talk of the town.
# 3: Aspect-Based Sentiment Breakdown
The sentiment analysis platform offers a fine-grained analysis of every aspect it discovers and categorizes from the data. Especially for businesses to remain successful and relevant in bottleneck competition is to read the room. So here it is, the voice of its customers.
If shoe company ALDO had listened to what its customers were saying about the tawdry quality of their shoes and bags and customer service, they would not be in the situation they are in today. On the contrary, the 80-years old business of Browns Shoes remains strong as it constantly evolves by listening to its customers and understanding the market trends.
In fact, aspect-based sentiment analysis offers you the power to carve your niche by keeping an eye on every detail of your brand.
# 4: Sentiment By Keyword
You can quickly get sentiment by keyword. The sentiment analysis platform processes all the data related to customer experience, the employee’s voice, healthcare, and brand monitoring. It immediately picks out the sentiment attached to essential words, as in, the most commonly occurring words and phrases in that project.
This approach is beneficial as it presents a holistic picture of the data you are analyzing and even picks up things that didn’t relate to you as a brand.
# 5: Define Alerts and Get Notifications in Real-Time
A resourceful sentiment analysis platform allows you to set alerts to receive notifications through text or email for different requirements in real-time. For example, you can define an alert for every time a keyword you have assigned is mentioned or there is a rise in your social media mention.
# 6: Sentiment Overview By Data Source
Another great insight you have is the ability to see sentiment by the data source. But, again, this is because the audience demographics are so different across various social media platforms.
This clearly presents that sentiment analysis based on your data sources can tell you that the negative sentiments you see are not necessarily because of a lack in your offering but because your target audience is not suitable for your offering.
Similarly, you can use these sentiment analysis platform insights to test new markets or product innovations.
# 7: Aspect Co-Occurrence
With advanced sentiment analysis, you get an aspect of co-occurrence data that shows you how often some specific aspects occurred together. For instance, an aspect like “service” occurred with “availability,” or the aspect “packaging” came up with “appearance”.
These insights provide you with vital information about audience opinion regarding several facets of your brand and help you develop strategies for improvements in your product or service.
# 8: Emotion Aspect Co-Occurrence
The sentiment analysis can give you insight into what emotions occurred most frequently with which aspects. Supposedly, you intend to find insights for internal use from the video repository, including all your social media content specific to a continental food menu. In such a case, the solution would first help you search for the related content through a search inside the video, and then the data will be extracted from all the videos that pop up.
Here, the sentiment analysis platform will analyze emotions in a way that you get to know how often the emotion “love” and “hate” appears with aspects like “food,” “customer service,” and “ambiance” in the video comments. This will eventually help you with factors that need your attention more keenly than others.
# 9: Sentiment Overview By Language
Integrating a multilingual sentiment analysis software allows you to engage with more users. Unlike other multilingual platforms, a trusted sentiment analysis software will use specific taggers for each language so that no nuances are lost when analyzing non-English data.
When amalgamated with a comprehensive named Entity Recognition Capability, you get more precise results than other major platforms in the market.
# 10: Changes In Sentiment Over Time
There’s no doubt that customer sentiment is a fickle master, quick to change overnight over a single controversial news item. So, not keeping track of the changes in market sentiment about your brand can lead to severe implications.
For example, once-powerful Disneyland realizes it slipped to the second position in the face of one PR disaster after another. Therefore, having sentiment analysis software that lets you monitor changes in your brand sentiment over time is invaluable.
# 11: Changes in Aspect Sentiment Over Time
Being aware of the changing market sentiments about your brand, simultaneously, you get a deeper insight into customer emotions about individual aspects of your business.
# 12: Toggle Between Aspect Sentiment & Text Chunks
One of the critical insights you get from an AI-powered sentiment analysis software is when you are toggling between aspect sentiment and text pieces in the data. Also, you can go back to see where those aspects appeared in which part of the data and then observe the sentiments around those aspects.
# 13: Named Entities, Classifications, and Entity Frequency
The sentiment analysis software applies Named Entity Recognition and offers you entities that it has discovered, extracted, and analyzed. To understand better, let’s take an example – “Anguish” is an emotion a person has, or “French” is the Language a person speaks.
Besides, it’s interesting to note that it realizes the difference between “French” the language and “French” the people as it classifies these entities. But, again, this is because of its capability to bring intelligence from semantics and contextual reference.
In a Nutshell
Many people are on social media, writing their opinions on blogs, connecting on news articles, filling out surveys, giving reviews of their employers on websites, and even through internal employee forums.
So, when mixed with the sheer scale of opinions floating around on the internet, the task eventually turns daunting. However, with AI-powered sentiment analysis of this enormous data, you can have the clear insight you need to create genius strategies for tangible results in terms of revenue and growth.