How to Extract Valuable Insights With Text Analysis

Text analysis, more commonly referred to as text analytics in the contact centre industry, is the process of extracting data from written texts, like phone call transcripts, emails, SMS, customer surveys and more, to learn more about customer behavior and thoughts. Businesses use text analytics to improve the customer experience.

In this guide, CallMiner explores how text analysis works and how contact centres can leverage text analysis solutions to derive valuable insights that can improve the customer experience – and the company’s bottom line. In this article:

• How text analysis works
• How call centres use text analysis to extract valuable insights
• Leveraging text analysis to improve customer experience
• Frequently asked questions

How Text Analysis Works

The text analysis process relies on artificial intelligence, machine learning, and natural language processing.

Text analytics is quite complex behind the scenes, but to simplify it, we can generally break it down into the following steps:

1. Text analytics software identifies keywords that allow the rest of the process to understand sentences and sentiment. Then, sentences get tagged according to their interpreted meaning. For example, if a customer mentions the word, “disappointed,” the system may tag the sentence accordingly to let an agent know that follow-up is necessary.
2. The software uncovers deeper meaning from text by grouping similar sentences together and creating rules. These rules dig into the potential intent behind a sentence, essentially cleaning up the data and continuing to train the algorithm.
3. The later steps in the text analysis process focus on the sentiment of the text. This is when the software provides insight into how a customer feels in a conversation based on what they say. Businesses can use this output to improve customer experiences.

How Call Centres Use Text Analysis to Extract Valuable Insights

Call centres use text analytics software to automate data extraction and provide valuable insights that improve agent skills and lead to better customer outcomes. The following are some of the top uses for text analysis.

Guide Agents in Real Time

Text analytics can support contact centre agents by giving them the information they need to adjust their customer support tactics in real time.

When paired with real-time transcription software, text analytics software can analyze a phone conversation as it happens and provide suggestions to an agent on how to improve the conversation.

For example, text analytics can pinpoint whether a customer becomes frustrated with an offer presented to them.

That data becomes part of a complete conversation analytics solution, prompting the software to deliver real-time guidance to the agent that could boost customer satisfaction, like suggesting another offer or a refund.

Gain More Insight From Customer Feedback Surveys

Text analytics can help businesses extract key pieces of information from customer feedback surveys. Using text analysis software, companies can determine the overall sentiment of open-ended responses, find keywords that commonly appear in feedback surveys, and determine whether a customer might be at risk of churn based on their feedback.

Understand Customer Feelings in the Moment

Sentiment analysis is a driving force behind improving customer experience. It quantifies a customer’s overall attitude during a conversation.

Text analysis technology can pick up on trigger words, speech patterns, and other indicators in a customer conversation to help agents see the overarching sentiment of the conversation as it happens.

Then, they can effectively use that information to drive higher satisfaction and improve brand experience.

Automate the Tagging Process

Proper categorization of customer conversations ensures that customers get the support they need when they need it.

A tagging system sends incoming inquiries to the right place, like the IT team or the refund department.

Doing this manually can take time and is prone to error. Text analytics software automates the process, usually much more accurately than humans can.

Using this approach, you can save time prioritizing and routing customer conversations, make tickets easier to find, and improve customer contact data accuracy.

Leveraging Text Analysis to Improve Customer Experience

Text analysis software improves over time the more you use it. As customers continue interacting with your business from multiple channels, text analysis algorithms keep getting better as they learn more about your customers, your business, and the priorities for each.

Frequently Asked Questions

What is Text Analytics in a Call Centre?

Text analytics uses artificial intelligence and natural language processing systems to extract meaning and insights from text-based conversations within a call or contact centre, like phone call transcripts and support tickets. Companies can use this data to improve brand and customer experience.

What’s the Difference Between Text Analytics and Speech Analytics?

Speech analytics tools analyze speech conversations, like voicemails and phone calls. In contrast, text analytics tools evaluate text-based conversations, like text messages, support tickets, emails, and social media messages.

Speech and text analytics both serve the same purpose of extracting data and insights to increase customer satisfaction.

Sophisticated conversation intelligence solutions analyze 100% of customer interactions across channels, including both text and speech interactions, providing deep insights to inform decision-making and drive customer satisfaction.

How Can Text Analysis Enhance Customer Interactions?

Text analysis allows agents to discover insights about customer interactions as and after they happen. Then, they can use that information to improve customer experience and satisfaction.

Companies also use text analysis to monitor their brand reputation on social media and quickly respond to problems mentioned by customers.

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