Data Science

Sentiment Analysis

Gain understanding on the attitudes and opinions expressed by your audience

Customers interact with organisations and provide feedback in many different ways. These ‘data points’ can be rich sources of information, allowing you to better understand customer experiences and help identify opportunities to improve the way you do business. When a customer contacts a call centre, posts a social media comment or sends an email, they use language that has positive and negative connotations. Analysing this language to identify the intent is known as Sentiment Analysis.

Business Value

Our clients harness the power of voice and text analysis for a variety of different use cases. This spans across reputation management, product and service development, training and support, call routing and regulatory compliance.

Here are just a few tangible ways sentiment analysis can add value to your business:

  • Improve customer service, with a focus on empathy for primarvnt enabled prioritisation and queuing
  • Overhaul or optimise service lines or key operational workflows
  • Use customer voice and text data to enable staff training and development
  • Utilise aggregated voice insights to improve product or service offering roadmaps
  • Adapt your sales and marketing strategies to be led by the voice of customer
  • Surface customer sentiment to front line staff to improve service
  • Align staff performance with customer feedback
  • Better manage brand reputation across all customer channels

How

At Aginic, we use a number of data analytical techniques to undertake sentiment analysis. We can process voice or text with natural language processing (NLP) to understand the topic, sentiment and outcomes of a customer interaction. Combining thousands or millions of interactions allows us to understand trends in customer behaviour and loyalty and to provide recommendations for improving the customer experience.

Using artificial intelligence, we can ingest data to extract and transform these data points straight from customer contact channels. For example, this enables us to perform entity recognition, which identifies sensitive information like names and email addresses. After removing sensitive information, we can perform sentiment analysis and extract key phrases, assigning positive, negative or neutral sentiment. Our sentiment analysis solution would enable your organisation to capture the most relevant topics from your customers.

By using algorithms that match your business needs and visualisation tools such as Power BI, Qlik, Tableau, or others, we can use the output of that extraction to show end users the important stuff to quickly and easily visualise how your customers feel and make decisions based on the facts.

Get started with Sentiment Analysis

Learn more about how our services can help your business. Get in touch with our team of experts today.

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