Today, almost all online communications happen via text. Emails, live chats, social media comments, tweets, the list is endless. It’s impossible for human agents to cope with all the information that is produced on a daily basis (2.5 quintillion bytes of data is created every day!). Instead, companies need to implement tools that can help filter and interpret all the texts they receive.
Discovering how customers feel toward a product or service is essential today, but analyzing this data by hand is inefficient and boring. Luckily, sentiment analysis tools are here to help. This software uses Natural Language Processing (NLP) to examine pieces of text and automatically evaluate the overall feeling behind your customers’ messages, classifying them into positive, negative, or neutral.
You can build your own sentiment analysis from scratch using open source libraries, but this process is quite demanding in terms of time and resources. Plus, you’ll need to have a deep understanding of coding and machine learning to build an effective and reliable sentiment analysis model.
Sentiment analysis tools come in handy if you want to avoid the hassle of building a model from scratch. They are ready to use, so you won’t need to set up any infrastructure. Also, some sentiment analysis tools can be easily integrated with other everyday apps like Excel, Google Sheets, or Zapier.
Now that you understand what a sentiment analysis tool is and some of their benefits, let’s take a look at the top eight tools for sentiment analysis in 2019.
The Best Sentiment Analysis Tools of 2019
- IBM Watson
MonkeyLearn is a user-friendly machine learning platform for analyzing text. It offers a pre-trained sentiment analysis model that you can try out for free! MonkeyLearn also has integrations with apps (such as Excel, Google Sheets, Zapier, or Zendesk) that allows you to integrate its sentiment analysis tool with any software you use regularly.
And if you are looking for more accuracy or need a tailor-made model to suit your industry-specific texts, you can train your own sentiment analysis model with MonkeyLearn. You can choose the algorithm and even the parameters that define your model. Tagging texts is very intuitive and fast, and you even have performance stats to debug your model once it’s ready, giving you reliable and accurate results in no time. And don’t worry: you don’t need to know how to code to use this sentiment analysis tool!
Pricing: Includes a free plan. Premium plans start at $299 a month.
2. IBM Watson
IBM Watson is a multi-cloud platform that offers many APIs for sentiment analysis based on NLP. The Watson Tone Analyzer, for example, which focuses on support tickets and satisfaction surveys and monitors agent sentiment – whether they’re polite and eager to help, and if they truly solved the customer’s issue.
IBM Watson has a comprehensive approach to text analytics, flexible enough to meet the needs of any client, no matter your industry or field.
Pricing: Includes a free plan. Premium plans depend on the number of predictions needed.
Lexalytics is a tool that focuses on customer sentiment. It also uses NLP to process your texts (breaking them into sentences to evaluate elements like semantics and syntax) and then runs sentiment analysis to gauge the feelings and emotions behind customers’ words. Once the sentiment analysis is over, the tool delivers a set of visual results.
You can customize the tool in different ways, though this option is aimed at data scientists and other specialists in the field.
Pricing: Variable. Schedule a demo to find out more.
If you would like to perform multilingual sentiment analysis using an API, MeaningCloud has got you covered. This online tool runs aspect-based sentiment analysis to decide whether the texts are positive, negative, or neutral. It is also able to detect irony and polarity. Additionally, you can define a dictionary to include any specific vocabulary that you might use in your field.
Some of MeaningCloud’s best features are the detection of global sentiment (a general view of what the customer expressed in a certain text), identification of opinion versus fact, and spotting sentiment within each sentence of a text.
Pricing: Includes a free plan. Premium plans start at $100 a month.
Working with Rosette is a breeze. This is an API that uses AI to analyze natural language. It was first used to perform sentiment analysis on social media, but eventually branched out to analyze entire documents and individual entities mentioned in the text, for example, the sentiment expressed by customers when they mention a specific product, company, or person. Rosette is able to identify parts of speech by means of morphological analysis and lemmatization (the grouping of inflected word forms so they are not analyzed separately).
If you’re an international company you can train Rosette’s sentiment analysis tool to identify up to 30 languages.
Repustate offers an online tool for sentiment analysis that provides insights into 23 different languages. This software can even assess the sentiment behind slang, such as FYI, bc, tbh, and also emojis to determine if the sentiment behind a message is negative or positive. Repustate even offers a free trial so you can try the tool to see if it really suits your needs.
Plus, you can customize the API so it identifies a specific language, and help the tppñs recognize alternative meanings of words, which gives you a lot of control over how this sentiment analysis tool scans your texts.
Pricing: Starts at $99 a month.
Clarabridge has a Customer Experience Management Solution that includes a tool that creates metrics about your customers’ state of mind by analyzing their emails, chats, and surveys. It also combines lexical and grammatical approaches to carry out sentiment analysis of each sentence within a text.
Different from the tools mentioned above, Clarabridge also focuses on Speech Analytics, that is, performing sentiment analysis on audio data. This is particularly useful for companies that rely on call centers as a channel for selling or providing customer support. This online software not only analyzes the speech of the caller but also their tone and subtle cues to interpret sentiment.
Pricing: Variable. Request a demo and get a quote.
Aylien is another online tool that unlocks the hidden value of texts by performing sentiment analysis and classifying them into Positive or Negative, or into Subjective and Objective. You don’t have to be an expert to use the tool, but you will need to know how to code to be able to use the API. And if you are looking to dive deeper into your customer’s opinions and feelings, you have the option to run aspect-based sentiment analysis.
The text analysis platform also allows you to build your own model hassle-free, and you don’t need to know a lot about machine learning or NLP to get started.
Pricing: Starts at $149 a month.
Your customers are always sending you texts, asking for your help or providing feedback on their experience, and this sheer volume of data poses a challenge. Human agents are constantly overwhelmed by large numbers of texts to be analyzed. Plus, the task is so repetitive that your team becomes tired and is prone to making mistakes. Instead, you can use sentiment analysis tools powered by AI to make sense of this data.
While all the tools described above are great for sentiment analysis, MonkeyLearn might sway you with its intuitive interface, easy implementation, and smooth customizability. And don’t forget that you can easily integrate it with apps you use every day to automate your business workflows!