January 24, 2024

How Omnichannel Sentiment Analysis Improves Customer Experience

How Omnichannel Sentiment Analysis Improves Customer Experience

All business people know that your company must focus on customer service to thrive. Consumers expect you to offer excellent products and services delivered with ease. You undoubtedly spend significant time and money to achieve these goals. However, your company can always grow in this marketing area. Improving your customer experience ultimately helps build brand loyalty and influences new customers to continue patronizing your company.

How do you evaluate this part of your business? You need to understand exactly how you are doing and how to improve. One way to gauge your customers’ experience is through sentiment analysis during their interactions with your contact center.

What is Sentiment Analysis?

Consumers learn about your company through huge amounts of digital text such as emails, service reviews, social media postings, chat transcripts, etc. Some of that messaging is quite positive while some paints a negative picture of your company. You must evaluate authors’ and speakers’ attitudes toward your products and services to protect and build your company’s reputation.

Sentiment analysis allows you to identify essential issues and take steps to remediate them. In this era of digital text, you need to use sophisticated tools to help you make these determinations.

Speech Sentiment Analysis with AI

Artificial intelligence has made sentiment analysis much more effective by allowing for automatic speech recognition (ASR), which can analyze audio files. This technology has clear implications for call centers that rely heavily on oral communication. ASR can easily transcribe audio files into text, allowing for in-depth agent/customer communications analysis. ASR also helps advance communications using voice assistants, improving customer experience with machines. For instance, it enriches your company’s self-service call options, a frequent cause of consumer frustration.

ASR eliminates the need for human transcription, a time-consuming process that is expensive and labor-intensive. It improves your company’s productivity while enabling more effective data analysis.

Text Sentiment Analysis

Text sentiment analysis has two main stages and uses natural language processes. NLP can enable software to understand text much as humans do. The results are invaluable for your marketing efforts.

Preprocessing

During the first stage, preprocessing, sentiment analysis technology chooses keywords essential to the text’s meaning. The steps include:

  • Tokenization: A process that identifies the key elements (tokens) of a sentence.
  • Lemmatization: Converting words into their roots, such as “seek” as the root form of “sought.”
  • Stop-word removal: Eliminating essentially meaningless words from the sentence such as “with, for, at, and of” that serve mainly to hinder the communication flow.

Keyword Analysis

The process then analyzes the keywords and gives them a sentiment score to indicate the emotional meaning of the words. An author or speaker’s satisfactory experience is represented by a 10. Words indicating dissatisfaction are given a zero.

Benefits of Omnichannel Sentiment Analysis

Sentiment analysis can identify the customer’s feelings during voice and chat conversations with your contact center. Implementing this technology for both communication forms will help build more significant insight into your customers’ experience. The following are some valuable ways omnichannel sentiment analysis will help improve CX.

Customer Insight

Using sentiment analysis lets you dig deeper into your customers’ opinions and emotions. Understanding their attitudes toward your business products and services lets you market more effectively.

Brand Reputation

Enhancing and protecting your brand reputation is essential to your company’s long-term success. Sentiment analysis quickly alerts you to serious customer concerns expressed in written and oral communications. You can then move immediately to remediate any issues.

Market Research

This technology allows you to accurately evaluate current market trends and competitors’ sentiments so you can better position your products and services. Sentiment analysis lets you understand how customers feel about your competitors, which helps you improve your company’s business model.

Product Improvement

Your call center must gauge customer satisfaction with your product and services. Sentiment analysis gives you insight into how consumers feel about these items, allowing you to rework products and services that are not highly rated.

Agent Interactions

Often, management evaluates call center agents by listening to their calls and offering feedback. This process can be hit or miss, leading to lost instruction opportunities. ASR transcribes these interactions into text, allowing you to use sentiment analysis. You then have access to accurate and actionable data that can improve agent interactions with consumers.

Sentiment Analysis Enhances Marketing Efforts

These processes are highly technical and rely on sophisticated software. Fortunately, you have access to these tools which do not require software experts to use. They do the hard work of automatic voice recognition and digital text transcription, allowing you in-depth insight into your customers’ experiences. The language they use when discussing your products and services reveals areas where you can improve. You can also get valuable insight into how consumers feel about your competitors.

To stay competitive in today’s complex marketing world, you must use these advanced software and AI tools. Your competitors are certainly taking advantage of this technology. Achieving the best customer experience possible depends on it.

See how Call Tools can support your enterprise today!

What Anti-Robocall Measures Can Call Centers Expect in 2024?

9 Tools to Improve Average Handle Time (AHT) in Contact Centers

Want More From Your Dialer?

Let our platform experts show you on a live demo!