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Sentiment analysis software

AI automatically identifies and tags positive and negative sentiments in your text, enabling you to analyze interviews to evaluate the tone, intent, and emotion behind the words.

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Make sense of large amounts of data with speed by automatically clustering your highlights by theme in canvas.

Automatic interview transcription

Advanced speech engine that automatically creates accurate transcripts across topics, industries, and accents. Enabling you to analyze quicker.

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From user interviews to sales calls and industry reports, uncover deep customer insights at speed.

What is sentiment analysis software?

Sentiment Analysis Software, or Opinion Mining Software, is a technological marvel designed to decipher the emotional tone within a text. When a human reads a text, they can easily understand whether the person is responding negatively or positively. Using advanced natural language processing (NLP), today's computers can perform the same task.

Not only that, but they can do it on a much larger scale than any human could. Sentiment analysis tools take advantage of this technology to classify a piece of text data as positive, negative, or neutral.

The earliest sentiment analysis tools relied on a predefined set of positive and negative words to perform their task.

Newer solutions use advanced machine-learning algorithms better at detecting nuance, sarcasm, and other confounding variables. This makes them ideal for quickly analyzing social media posts, online reviews, customer feedback surveys, news articles, and any other piece of text that may discuss your company or its products.

How does sentiment analysis software work?

Sentiment Analysis Software employs a multi-step process to understand and classify sentiments accurately:

1. Text preprocessing: The software cleans and prepares the text by removing irrelevant information such as punctuation.

2. Tokenization: The text is broken down into smaller units or tokens, such as words or phrases.

3. Sentiment classification: Using a combination of machine learning algorithms and predefined sentiment dictionaries, the software assigns a sentiment label to each token.

4. Sentiment aggregation: The sentiment scores of individual tokens are aggregated to determine the overall sentiment of the text.

Why is sentiment analysis important?

Sentiment analysis is important for several reasons. The way the public responds to a business has a profound impact on your business's success. Sentiment analysis is the most efficient way of understanding how the public is responding, and it allows you to adapt in a way that drives your company in the right direction.

When analyzing reviews or other publicly available text, this can be helpful in brand reputation and product development. For even further insights, you can create specific surveys and ask customers to fill them out. Here, you'll be able to get a fine-grained analysis of how customers feel about specific areas of your business or product.

Long before tools to automate the process were available, companies understood the need for sentiment analysis. It's why they paid attention to reviews and solicited feedback from the public in the first place. Sentiment analysis tools take that time-honored tradition and supercharge it with far greater capacity than was possible in years past.

Sentiment analysis tools for different use cases

There are limitless uses for a better understanding of how your customers feel about you. Each industry will have its own set of niche use cases, but all of them will fall into a few broad categories.

Below are some of the major areas in which companies use sentiment analysis to improve business operations:

1. Brand reputation management

Every brand wants the public to have a positive perception of its business, but that isn't always the case. If things get too bad, it can be hard to recover from. Sentiment analysis helps brands discover when negative sentiment starts to manifest and take steps to stop it before it grows.

2. Customer feedback analysis

The customer feedback cycle is an important part of many business processes. When performed manually, it can be time-consuming. Sentiment analysis allows for quick and accurate summation of customer feedback for improved decision-making and a more efficient feedback cycle.

3. Competitor analysis

The best way to rise above the competition is to stay ahead of them. By analyzing the sentiment around a competitor's customers, brands can identify weak spots and discover ways to differentiate themselves in the market. They can use this to refine product development or marketing strategy.

4. Product development

It isn't enough to refine products based on feedback from competitors. Sentiment analysis on your own products can also provide significant instruction on which direction to take them. It also prevents competitors from using their own analysis of your products against you with their own competitor analysis.

5. Campaign analysis

Some marketing campaigns are huge hits, and others fall flat. Occasionally, a brand misses the mark so badly that its campaign receives backlash and hurts them. Sentiment analysis keeps you aware of how the public is responding to a campaign so it can be adjusted as needed for maximum ROI.

Benefits of adopting a sentiment analysis tool

Understanding the needs and preferences of your customers is one of the most vital aspects of running a business. A brand that consistently provides customers with what they want can rise above the competition and develop market security even during economic downturns.

Sentiment analysis tools like Dovetail allow you to take those needs and preferences straight from the mouths of customers. Below are some of the most significant ways this type of analysis can help your business:

Faster and more accurate analysis of customer feedback

Without sentiment analysis tools, you're limited by how much a human can read and process. With a large customer base, reading everything from everyone is impractical. With the analysis tools, the computer can process large volumes of feedback in real-time, with far greater pattern-matching capabilities than humans alone are capable of.

Improved customer service

When customers aren't happy, they tend to be very vocal about it. This makes sentiment analysis a great way to understand where your product or service is falling short so you can take proactive steps to improve in those areas. When you address problems more quickly, fewer customers experience them, and your customer service staff is freed up to address other, less common concerns.

Better decision-making

You should focus nearly every business decision you make on the customer. From new product development to marketing strategies, the idea is to connect with the customer as much as possible. Sentiment analysis provides key insights into how your specific customers think, allowing you to make decisions that more accurately address their specific concerns.

Collaboration and sharing of insights

Some sentiment analysis tools, like Dovetail, offer collaboration features. These enable you to share insights with team members and stakeholders, allowing for cross-functional analysis and a more transparent view of how your brand is perceived by its customers.

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