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Text Analytics in Customer Service: The Way Businesses Engage with Customers

Contributing Author

8 min read

Dec 1, 2023

Have you ever talked about having a bad day, and no one listens? They say something like "That's rough" or nod while mindlessly scrolling through their phone.

It doesn't make you feel understood. You may feel upset or angry. It can make you stop talking when you want someone to listen and they don't.

How does this scenario apply to customer service or their experience? It gives an example of how they may feel about a bad experience with a business. Text analytics software is a great way to understand the customer because it provides critical data.

If the customers have a problem, they address it by talking to someone at the business. How the employee responds to customer sentiments determines whether or not they will be returning.

68% of people are okay with paying more for products or services if the business has excellent customer service. Companies spend millions on advertising, but service can be equally crucial.

There are several benefits of having excellent customer service. Text analysis is one of the best ways to improve it. In this post, you'll learn how text analysis works and its benefits.

Understanding text analytics

What is text analytics? How does it work?

Text analytics uses AI to identify trends, patterns, and other insights.

It converts massive amounts of unstructured text and tracks the qualitative data gathered (data that can be measured numerically). Let's look at an example.

Example

Did you know businesses can use text analysis to understand customer sentiment? This can make their call centers run more smoothly and increase their customer satisfaction score.

Using call center text analytics to learn customer sentiment helps to understand feedback.

Text analytics enables companies to develop strategies to improve customer experience. It allows businesses to save at-risk customers and offers quality service.

Text analytics solutions can help interpret data collected from internal and external sources, which can help provide actionable insights. It uses structured and unstructured data.

And the best part? Call-center text analytics software and integrated software solutions can help gather all this information discreetly and efficiently without needing active consumer feedback.

So, if you want to improve your call center's performance, a text analytics solution might be the solution you need!

The benefits of text analytics in customer engagement

Text analytics can provide valuable feedback data like customer pain points. It can extract meaningful information for businesses and market research agencies.

There are several benefits to using text analytics to improve engagement and support. In this section, you'll see the benefits of text analysis and how it can improve customer satisfaction.

Text analytics platform provides real-time insights

Businesses can benefit from text analytics by tracking feedback in real time. This feedback helps show customer pain points and allows a business to keep up with current trends and customer segments.

You'll be able to improve engagement and their all-around successful customer experience program by using text analysis.

The competitive advantage of using text analysis

Businesses can use text analytics software to beat the competition. How is that possible? It allows you to meet customer demands or needs by constantly making changes.

This will help lead to loyalty and growth, which helps increase revenue. It is a solid competitive advantage.

Text analysis saves time and money

There never seems to be enough time in the day, and businesses are always looking to cut costs. Automating the information gathered from a mass amount of unstructured text data streamlines the whole process.

This allows companies to save time and money on interactions. Customer retention saves money compared to attracting new ones.

Loyal customers are easier to sell to and will spend 67% more on products or services than first-time shoppers. This is why customer satisfaction is essential to business value.

Improved decision-making using customer data

The more information a business has, the more it can make intelligent choices. You want as much information as possible when considering product development, creating marketing strategies, using business metrics, and constantly improving service.

All the structured data gathered through text analysis can also be helpful for market research companies.

Sentiment analysis and customer satisfaction

Have you ever wanted to ask someone a question and wished you knew their mood? If you ask at the wrong time, their response may differ, and you are looking for positive feedback.

Reading minds would be helpful, but here's the next best thing since that's impossible. Sentiment analysis can help you identify customers' emotions.

Sentiment analysis

Sentiment analysis is often known as opinion mining. It uses natural language processing coupled with text analysis to identify customer emotions.

To get unstructured data, It can use social media posts or online reviews, among others, to get this information. It then can convert unstructured data into structured data.

Why is knowing customer emotions essential?

Natural language processing allows you to understand customers' opinions or emotions toward products, services, and brands using online data and other text analysis software. All the relevant data sources collected by text analysis keep you on the right track.

You can also see if there is a need to make drastic changes that customers will favor. Text Analytics data is another way to improve satisfaction by using feedback and working to improve customer experience.

Customer feedback and continuous improvement

When you gather feedback, you should treat these as actionable insights to improve your customer experience programs and support tickets.

They are not only customer feedback but provide you with answers to important questions like "How can we improve our product?"

Example

If you're selling shoes and a customer's pain point is that they are too slippery on the tile, you can improve that by changing it.

Maybe text analysis shows that customers say your product should come in more colors. Make more colors! This will enhance the customer experience and influence behavior.

Closed-loop system for continuous improvement

You can't afford to ignore the voice of the customer. One bad customer experience will take 12 positive experiences to make it up to them.

That's a ton of work! That's not the worst statistic, though. 91% of people won't return to a business or brand if they have a terrible experience.

You can see how the standards must be for your customer program to be successful. How can you exceed expectations and have excellent support? By using the closed-loop system!

The system consists of a few steps that each have more in-depth guidelines and representative analysis, but the key elements are:

Identify failures.
Corrective action.
Respond to the corrective action.
Define the root cause of the failure.
Implement the solution.

Challenges and limitations of text analytics

Using text analytics for customer support presents several challenges:

Data quality
Data complexity
Interoperability
Data privacy

Text data

All the data can be noisy, ambiguous, and incomplete, making it difficult for analysis tools to understand. The unstructured data may be in incompatible systems, making extraction and integration challenging.

Privacy

Privacy concerns should be considered because of the chances of personally identifiable information being pulled within unstructured data. Data cleaning, transformation, and PII redaction techniques can help these challenges.

Fixing the challenges

Choosing a robust text analytics solution or tool compatible with existing infrastructure can make integrating it easier. By correcting these challenges, businesses can benefit from text analysis to improve customer service.

Future trends in text analytics

You can benefit from using other integrations and text analytics software solutions for a holistic approach to delivering business insights. Integrations can automate repetitive and time-consuming tasks that can save you time when interpreting customer data.

It helps update deal statuses or exchange data with your CRM and more. The best integrations to pair with text analysis can include:

WordPress
Zapier
HubSpot
Jira
Salesforce
GitHub
OpenWidget

Predictive maintenance

AI plays an essential role in the predictive maintenance of cloud infrastructure. It supports proactive maintenance, which helps provide optimal cloud system performance, scalability, and reliability.

With AI, potential issues can be identified, system failures predicted, and necessary actions taken before they impact operations. AI can help proactive maintenance by improving system reliability, cost savings, enhanced scalability, and reduced workload.

AI drives predictive analytics in three ways:

Anomaly detection.
Failure prediction.
Optimized maintenance scheduling.

Real-world examples from industry leaders like Google and Netflix demonstrate the effectiveness and benefits of AI-powered proactive maintenance.

Using text analytics tools helps identify customer emotions, which can help improve satisfaction. It is a valuable tool for companies looking to improve service and loyalty.

Customers want to be listened to, which is the best way a business can create a customer experience program. If you are ready to enhance your service and focus on retention, then HelpDesk is an excellent place to start.

Conclusion

Text analytics software can help businesses understand customer sentiments and improve service. It is more expensive to bring in customers than it is to have loyal ones. This is why having a strong customer experience program is essential.

Since loyal customers spend more than new ones, this shows how essential it is to keep them happy and gather data using text analysis.

Text analysis can offer several benefits:

Provide real-time insights.
Give a competitive edge.
Save time and money.
Improve decision-making.

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