If you want to understand how people really feel about your brand, it's important to conduct sentiment analysis.
Successful and thorough sentiment analysis involves monitoring all brand mentions on social media platforms, tracking customer satisfaction and looking out for negative feedback, and capturing customer conversations to gain insights.
This is not an easy task to undertake without the right tools.
For a big brand, it would be impossible for an individual (or even a team) to keep track of all brand mentions across all social media networks and customer feedback channels.
And that's before we even consider the painstaking effort it would take to manually track and analyze the sentiment behind those mentions.
To successfully tackle this mammoth task, you'll need a powerful and easy-to-use sentiment analysis tool.
This will help you properly track and analyze all those brand mentions before automatically sorting them into positive and negative sentiment.
Fortunately, there are many sentiment analysis tools out there, each designed to make the job of tracking customer feedback a lot easier.
Different types of sentiment analysis tools
We can typically classify each individual sentiment analysis tool into one of three main categories:
- First, there are the big-name sentiment analysis tools used by some of the world's biggest brands. These come with a subscription cost, but often offer a dazzling array of features, such as in-depth sentiment analysis, natural language processing, and actionable insights.
- Next are the newcomers. These are powered by emerging technologies and are designed to deliver detailed customer insights and pinpoint customer pain points. A sentiment analysis tool like this may be able to uncover new data insights and patterns using AI-powered machine learning algorithms.
- Finally, there are a handful of free sentiment analysis tools that can be a game changer for a small business with a limited budget. While the features of a free sentiment analysis tool may be limited, they can still pack a punch when it comes to automatically scanning social media data and providing a simple sentiment score that can help inform your marketing campaigns.
Before you decide which sentiment analysis tool to choose, let's take a look at the main options on the market and how each can transform your approach to customer feedback, make sense of otherwise unstructured data, and analyze customer sentiment with ease.
In this guide:
What is a sentiment analysis tool?
Sentiment analysis tools are typically integrated into multi-function news or social media monitoring tools.
At their core, they help companies analyze customer feedback to better understand the emotions and opinions expressed by their customers in textual data such as social media posts or online reviews.
In other words, you could call them text analysis tools.
So, how do sentiment analysis tools work?
Sentiment analysis tools use natural language processing (NLP) and artificial intelligence (AI) to understand the emotions behind written content and provide a sentiment score across a target audience.
Even better, some sentiment analysis tools can understand customer sentiment in emoji-heavy social media mentions - either through machine learning or contextual clues.
Sentiment analysis tools can work superfast to assess brand reputation.
They are powered by artificial intelligence and machine learning, which means sentiment analysis can be performed at speed and scale.
A sentiment analysis model can analyze large amounts of textual data, such as social media posts, customer reviews, or press content, and assign a positive, negative, or neutral emotion to the input.
Some advanced sentiment analysis tools can alert users to further nuances in customer sentiment, such as indications of controversy or damage. This is undoubtedly helpful, and a feature that could help a brand avoid or mitigate an impending crisis.
By staying on top of both positive and negative sentiment, brands are in the best position to both identify lucrative marketing opportunities and avoid brand-shattering PR.
What are the benefits of using sentiment analysis tools?
Sentiment analysis tools are a great way to track customer satisfaction and turn unstructured data into actionable insights.
Here are some reasons why we love using sentiment analysis tools to track customer sentiment:
Save time and money
Rather than individually sifting through thousands of social posts and reviews to understand your brand perception - which can take hours, days, or even weeks - you can automate this particular task with an analysis tool.
This gives teams more time to address customer concerns before they escalate.
Make better marketing and PR decisions
You can also use some of the time you've saved on manual analysis to make decisions and invest in better marketing strategies.
For example, if the sentiment analysis tool shows negative sentiment around your brand's ESG initiative, you can launch a PR campaign to turn that around.
Improve product development
Getting a clearer sense of the opinions and customer feedback surrounding your products can help you refine those products to appeal to a wider audience
Transform customer service
A great sentiment analysis tool can scan your customer service team's inbox and automatically analyze the emotional subtext of customer conversations.
This can help you identify and resolve sensitive issues before they blow up.
Avoid major PR disasters
Sentiment analysis tools can help you stay ahead of PR fallout through crisis management by alerting you to sudden drops in conversational tone across your audience and customer base.
This means that you can also plan crisis management strategies around your analytics tool, mapping out how to generate positive sentiment when your brand faces challenges.
The best sentiment analysis tools on the market
With so many sentiment analysis tools to choose from, the pressure to make the right choice can feel a little overwhelming.
To help, we've compiled a list of 8 of the best sentiment analysis tools on the market.
These will help you get the most out of sentiment analysis tools and ultimately increase customer satisfaction.
1. Brandwatch
If you're looking to take your social media sentiment analysis to the next level, Brandwatch is the tool for you.
Brandwatch can handle even the most complex language, slang, and dialects – and even helps users analyze the emotional context of emojis.
Brandwatch helps users dive deep into emotion distribution analysis, giving them insights into the prevalence of emotions like anger, disgust, fear, joy, sadness, and surprise surrounding their brand or its related topics.
This level of granularity can be invaluable for creating targeted marketing campaigns and addressing specific customer concerns.
An example of Brandwatch in action:
A global brand with a presence in multiple countries and languages could use Brandwatch's sentiment analysis in over 40 languages to ensure they're getting the full picture of how their brand is perceived around the world.
Product features:
- Sentiment analysis in over 40 officially supported languages, with the ability to classify sentiment in any language
- Sentiment accuracy typically in the range of 60-75% for supported languages, but can vary depending on data source
- Ability to manually override sentiment scores by selecting positive, negative, or neutral
- Filter feeds and conversation comments by sentiment, selecting the desired sentiment in advanced filters
- Analyze the overall sentiment and emotion distribution for a search, as well as the prevalence of different emotions such as anger, disgust, fear, joy, sadness, and surprise.
- State-of-the-art deep learning and natural language processing (NLP) techniques, including transfer learning, for more sophisticated sentiment analysis that can handle complex language, slang, and dialects
2. SproutSocial
Imagine being able to understand the sentiment behind every social media post, review, and direct message (DM).
Well, that's exactly what SproutSocial offers with its AI sentiment analysis tools.
SproutSocial allows users to perform sentiment analysis across social and review platforms, as well as within their Smart Inbox to analyze the sentiment of customer feedback via email.
An example of SproutSocial in action:
Say you're a tech brand that just launched a new update. Unfortunately, a bug was accidentally pushed live, and the app was taken down. Since there's no way to contact you through the app's chat feature, users start flooding your social media channels with negative customer feedback.
With SproutSocial, their sentiment analysis tools would alert you to this snowballing negative sentiment and allow you to quickly update users with a timeline for when they can expect the bug to be fixed.
Product features:
- Leverages AI to power its sentiment analysis tools
- Builds AI sentiment analysis into customer feedback classifications through its Smart Inbox
- Identifies and measures emojis in text, and measures alongside sentiment analysis
- Offers multilingual sentiment analysis tools
- Gap analysis & side-by-side competitive sentiment analysis comparisons
- Measure sentiment across X/Twitter, Facebook, Instagram, Yelp, TripAdvisor, and Glassdoor
- Social posts are automatically assigned a sentiment, and users can set up their own rules.
3. CisionOne
When it comes to monitoring your brand's reputation, CisionOne is a true powerhouse.
Its sentiment analysis tool lets you analyze both social and media, while also providing exclusive analysis of paywalled content from some of the most respected news sources, including The Wall Street Journal, MarketWatch, and The New York Times.
An example of CisionOne in action:
Let's say you manage social media for a well-known fashion company, and a major news outlet has just published an article about your latest product launch.
With CisionOne's sentiment analysis tools, you can analyze the sentiment surrounding the article and gauge how it's being perceived by the public.
Then you can use the sentiment analysis tool to dig deeper and look at different types of media, such as online news, print, television, and social media.
And it doesn't stop there. CisionOne's sentiment analysis tools also offer AI-powered risk score monitoring, which can help you stay ahead of potential crises by monitoring for controversial, emotional, or harmful content related to your brand.
Plus, the tool lets you dive deeper into specific negative news and customer satisfaction.
Product features:
- AI sentiment trend timelines
- Monitor the sentiment of single or multiple topics
- Overall pi chart breakdowns of positive, neutral, and negative coverage
- Slice and dice sentiment analysis across news media: online, print, TV, magazines, radio, and podcast media
- Filter, segment, and analyze sentiment across social media: Facebook, X, and YouTube
- Limit sentiment analysis to specific sources
- Analyze sentiment through emoji count analysis
- AI-powered risk score monitoring across news media: Average risk score, controversy, emotionality, harm, spam
- Self-rated sentiment analysis tools
- Qualitative sentiment analysis tools: Content themes, leading hashtags
4. Lexalytics
Lexalytics is the hidden gem of the sentiment analysis world.
You may not have heard of it because it's not a direct-to-consumer product, but this powerful text analytics API is the engine that powers many market-leading sentiment analysis tools, including Microsoft and Cision.
Lexalytics also offers advanced NLP features like tokenization and part-of-speech tagging that brands can use to improve their sentiment scoring, categorization, and topic analysis.
An example of Lexalytics in action:
Product development teams working on a cutting-edge sentiment analysis solution can turn to Lexalytics to build a customized solution that meets the needs of their customers and industry. This could include customizing the sentiment scale or incorporating industry-specific vocabulary.
Product features:
- The underlying technology and raw sentiment data that powers other products in the market
- More likely to be integrated by product development teams in need of a sentiment analysis tool than by marketing or PR professionals
- Offers NLP capabilities, including tokenization and part-of-speech tagging, to enhance sentiment scoring, categorization, topic analysis, and more
- Fully customizable and can be adapted to your sentiment specifications - whether it's based on scale or industry-specific vocabulary
5. Brand24
Next up is Brand24, a comprehensive social media monitoring and sentiment analysis tool.
With Brand24, you can track sentiment across a wide range of platforms, including X, Instagram, Facebook, videos, podcasts, forums, and web content.
Brand24 also offers a reputation score, which can give you a quick snapshot of how your brand is perceived overall.
This can be particularly useful if you want to identify potential problems or areas for improvement.
But the most unique feature of Brand24 is its ability to help users decipher which of their referral sources are sending positive and negative sentiments their way.
An example of Brand24 in action:
Let's say you're a hotel chain, and you want to understsand how positively (or negatively) your traffic referrers describe your brand. With Brand24 you can study the emotionality of these brand mentions.
Product features:
- Tracks sentiment breakdowns across X, Instagram, Facebook, videos, podcasts, forums, and web content
- Sentiment over time
- Topic analysis by sentiment
- Sentiment of sources mentioning topics
- Reputation score
6. MonkeyLearn
MonkeyLearn has a full suite of tools to help with text analysis. It's out-of-the-box sentiment analysis tool is known for its exceptional accuracy.
One of the main selling points of this text analysis tool is its ability to integrate with other tools such as ZenDesk and Google Sheets.
A large company with a skilled technical team will be able to connect these tools to their stack using the MonkeyLearn API.
However, even if you don't have a tech team or personal coding skills, you still can build a custom classifier using a simple and accessible point-and-click interface.
An example of MonkeyLearn in action:
A small business could use MonkeyLearn to start tracking customer sentiment on their social media platforms without having to access any code. However, they would have the ability to create more complex integrations later as their business grows. They could also hire freelance technical help to customize the product to their needs.
Product features:
- Import data from a range of apps, including key social media platforms
- Use machine learning to train the sentiment analysis tool
- Automate processes within your apps to track sentiment and increase your overall customer satisfaction score
7. Hootsuite Insights
Social media management platform Hootsuite recently acquired social listening tool TalkWalker.
This means that social listening will soon be an even bigger part of the Hootsuite dashboard - a platform already used by brands to manage and streamline their activities across social media platforms.
While social listening has been part of Hootsuite's offering for years, the acquisition of TalkWalker is expected to take its capabilities in this area to the next level.
According to Irina Novoselsky, CEO of Hootsuite, the company is building a "social media performance engine" and will focus on using consumer data to deliver actionable insights and strategies that create measurable impact.
An example of Hootsuite Insights in action:
As an agency, you've been using Hootsuite for years to juggle multiple social media platforms and brands. Your team is familiar with the interface and finds it easy to use. Instead of introducing and training them on an entirely separate sentiment analysis tool, you can get a deeper understanding of the sentiment of your target audience all in one place. Making everyday office life a little easier.
Product features:
While we don't know exactly what Hootsuite's upgraded sentiment analysis feature will look like, it promises the following:
- Expanded listening coverage: tracking global sentiment across 100+ social networks
- Enhanced AI trained exclusively for social media platforms using BlueSilk™ GPT
- An all-in-one social media performance engine to minimize the need to download and learn multiple tools
8. Google Alerts
With a little research, you'll find that most advanced sentiment analysis tools come with a subscription and a range of sophisticated features to justify the price.
However, for those just starting out, you may just want something super simple - and free.
In that case, Google Alerts might be the best place to start.
It's a really simple media monitoring tool, but it will catch all mentions of your brand on websites, news sites and blogs. Using it could mean that you catch a critical mention of your brand in a corner of the web that you would have otherwise missed.
It's important to note that Google Alerts does not track social media mentions.
To track both, you'll need to use a social media monitoring tool and set up hashtag or keyword alerts so you don't miss any brand mentions.
An example of Google Alerts in action:
For a tiny business, almost any mention of your brand online is an exciting day at the office. A small business owner can set up a simple Google Alert to catch a critical mention of their service on news sites or blogs. In the early stages of the business, when there may be only a few mentions, customer perception is easier to track by simply reading the results delivered in these alerts. Complex analytics may not be needed - yet!
Product features:
- Google Alerts are delivered directly to your email inbox
- You can set your region and language
- Alerts can be delivered once a day, once a week, or on an as-it-happens basis
Challenges of sentiment analysis tools
Sentiment analysis tools aren't foolproof. Sometimes emotional classifications are off, and as with any AI-based initiative, a human-in-the-loop approach is critical.
While sentiment analysis tools offer many benefits, they also present some challenges:
Accuracy limitations
Sentiment analysis algorithms can struggle with sarcasm, idioms, and contextual language, leading to inaccurate classifications.
Data quality issues
The quality of sentiment analysis is highly dependent on the quality and relevance of the input data. Noisy or irrelevant data can affect the results.
Lack of nuance
Most sentiment analysis tools classify text into broad categories such as positive, negative, or neutral, and fail to capture more nuanced emotions or sentiments.
Language barriers
Many tools are designed primarily for English text and may perform poorly on other languages, especially those with complex grammar or writing systems.
Ethical considerations
As sentiment analysis tools become more prevalent - and most are powered by powerful AI - it's important to consider the ethical implications:
Privacy concerns
Sentiment analysis of public data such as social media posts raises privacy concerns, especially if the data is used for targeted advertising or other purposes without user consent.
Bias and discrimination
Sentiment analysis algorithms can perpetuate societal biases present in the training data. We need to be aware that this could lead to unfair or discriminatory treatment of certain groups and be vigilant to prevent this from happening.
Manipulation and misuse
There is some concern that sentiment analysis could potentially be used to influence public opinion or manipulate emotions on a large scale, raising concerns about the ethics of such practices.
Future trends in sentiment analysis
As with all aspects of digital marketing, the field of sentiment analysis is evolving rapidly.
As we write this guide, we're seeing several key trends emerge.
Let's take a look:
Multimodal analysis
Tools are beginning to incorporate sentiment analysis from multiple data sources, such as text, images, audio, and video, for a more comprehensive understanding.
Aspect-based sentiment analysis
Rather than classifying sentiment at the document level, newer techniques aim to identify sentiment about specific aspects or features of a product or service.
Explainable AI
There is a growing focus on developing sentiment analysis models that are transparent and can explain their reasoning, increasing trust and accountability.
Transfer learning
Sentiment analysis models are becoming more sophisticated as they begin to use pre-trained language models and transfer learning techniques. This can improve their accuracy and adaptability, especially for low-resource languages or domains.
The last word on sentiment analysis
So, there you have it – the top eight sentiment analysis tools that are worth your attention.
Whether you're a small business or a global enterprise, these tools can give you the insights you need to stay ahead of the competition and make informed business decisions that drive success.
