Find out what makes your customers and employees happy—or not so happy. Leverage the insights obtained to quickly address areas for improvement and create better experiences.
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Understanding what makes people tick is one of the most powerful secrets in business. If you can figure out what drives your customers and employees, you can use that knowledge to build trust, loyalty, and long-term success.
Since 2007, Arbisoft has been helping businesses like yours gain a nuanced understanding of what sparks joy or frustration in their users. We use smart technology like AI and machine learning to analyze text data and determine the underlying sentiment. This gives you the actionable insights you need to make the best decisions.
You’ve worked so hard to build your brand. But what your customers think can make all the difference. That’s why you need to know how they really feel about your products or services. This is where we step in!
We leverage the latest tech and natural language processing (NLP) to do sentiment analysis at scale. Our “voice of customer” solutions analyze feedback from social media comments, posts, surveys, emails, and more. So you can understand what your customers are saying and improve their experience.
Replacing an employee costs 50-200% of their annual salary. Yet, nearly 13.5% of employees leave their jobs voluntarily, and many more are fired. That’s a lot of turnover—and a lot of money lost. If you’re dealing with this challenge, it’s time to take control with data-driven insights.
Through our ‘voice of employee’ solution, you’ll get clarity on what your employees are thinking and how they really feel. We help you analyze data from feedback forms, surveys, emails, support tickets, Slack messages, and more. This enables you to tackle issues before they escalate, and foster a culture that boosts employee engagement and reduces churn.
When our team of experts gets together to deliver sentiment analysis solutions for you, they utilize industry best practices to get you the results that will make all the difference.
For effective sentiment analysis, it’s essential to clean and pre-process the data. At Arbisoft, we make sure the data is free from irrelevant characters, misspellings, or formatting errors. We use techniques such as tokenization, stemming, and stop word removal to guarantee high-quality, accurate sentiment analysis for your business.
Sentiment analysis is carried out using several algorithms, such as the rule-based method, machine learning approach, and hybrid model. We select the one that best fits your business context. For instance, if your project includes large-scale datasets coming from various sources, we leverage machine learning models for their ability to handle complex data effectively. Similarly, we opt for rule-based sentiment analysis if you have smaller datasets. Thus, choosing the right algorithm helps us ensure the sentiment analysis is accurate, efficient, and aligned with your goals.
Context is crucial to comprehending the accurate meaning of words or phrases in a specific situation. Sentiment analysis should count for sarcasm and context. Sarcasm can make positive statements seem negative and vice versa. To overcome this problem, Arbisoft implements cutting-edge NLP models that are adept at detecting sarcastic expressions and contextual cues. As a result, we deliver you a more accurate sentiment assessment.
In sentiment analysis, customer data must be handled ethically and in complete compliance with the data protection laws. This is what Arbisoft does. We understand that neglecting data privacy and compliance could lead to serious consequences. Hence, we always prioritize customer data protection by following ethical guidelines and data privacy regulations. Our approach ensures that customer trust remains at the heart of our sentiment analysis solutions.
Years building custom solutions and applications
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Specialists with decades of experience
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Sentiment analysis (also referred to as opinion mining) is a process that determines whether a piece of text is positive, negative, or neutral. It’s a sort of text research method that looks at words and phrases to comprehend the general mood of a conversation.
Yes! Sentiment insights can greatly improve any marketing strategy by providing valuable insights into how customers feel about products, services, or campaigns. If you carefully analyze those customer emotions, it will help you identify areas for improvement and create more targeted campaigns. This would ultimately lead to increased user engagement and increased revenue.
Sentiment analysis helps identify customer pain points. It reveals what your customers like or dislike about your products or services. Using this information, you can apply appropriate changes to reduce complaints and improve customer satisfaction.
Sentiment analysis makes use of natural language processing (NLP) to dig into digital text. By looking at words, phrases, keywords, and context, it can tell whether the mood is positive, negative, mixed, or neutral. The process often involves machine learning models that are trained on large sets of data to spot patterns in language and predict the sentiment. The system then classifies the overall mood of the text based on what it has learned from these patterns.
Context is very important in sentiment analysis. You can’t accurately understand sentiment unless you know how the words or phrases were used together in a sentence or conversation. To solve this problem, we utilize contextual sentiment analysis tools that leverage deep learning to capture tone and context. This enables us to ensure accurate interpretation of the sentiment.
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