NLP (Natural Language Processing) is a branch of artificial intelligence that enables computers to understand and process natural/human language.
The use cases of NLP fit into many applications in CX delivery, such as chatbots, sentiment analysis, text summarization, and more. Therefore, leveraging NLP in contact center can allow organizations to benefit considerably through enhanced CX delivery.
However, integrating NLP into CX delivery also comes with some challenges and trade-offs that should not be ignored.
Read on to explore some of the key benefits and main challenges to be considered and addressed when implementing NLP in your CX strategy.
Key benefits of NLP integration within contact centers
The heightened interest and main draw towards using NLP in contact centers is its ability to provide several benefits to businesses that opt to do so. The main benefits that organisations can leverage include:
Integrating NLP allows organisations to automate repetitive tasks and reduce response times to streamline operations and improve the efficiency of their contact centers.
Applications such as chatbots can handle simple inquiries, allowing human agents to focus on more complex issues that are assigned a greater priority.
Functionalities including text classification can improve CX delivery times by automating the routing of inquiries to the appropriate team, reducing response times and ensuring that inquiries are handled by the most appropriate team.
Customer satisfaction and engagement can be boosted significantly as NLP can improve the quality of interactions between contact centers and customers.
The number of engaging interactions can improve as chatbots can provide quick and efficient responses to customer inquiries, reducing wait times and improving the overall delivery of CX.
Using sentiment analysis can improve the quality of interactions by promptly identifying dissatisfied customers and addressing their concerns before they escalate, improving customer satisfaction.
Leveraging NLP can cut down on the cost of CX delivery and support by using automation to carry out routine and repetitive tasks which results in the reduced need for human agents. The lower requirement for agent hours in the contact center can lead to cost savings for businesses, as they can handle a larger volume of inquiries with fewer agents.
Additionally, chatbots can be available 24/7, allowing businesses to maintain CX delivery at all times by providing customer support outside of regular business hours without incurring additional costs.
Main challenges of NLP integration within contact centers
While NLP has the potential to transform CX delivery in contact centers, there are also some challenges that businesses need to consider. Leaving these challenges unaddressed or ignored can offset any benefits of NLP integration and can lead to organisations incurring significant costs—both financially as a result of lost revenues and non-financially in terms of reputational damage and disgruntled customers.
The main challenges that organisations need to overcome when integrating NLP into their contact centers include:
Solutions using NLP are most often trained on standard language models and may struggle to understand different accents, dialects, or languages, particularly in cases where the customer uses non-standard language or jargon.
This can lead to misinterpretation and miscommunication, which can impact the quality of interactions and lead to poor engagement overall, causing frustrations and adversely affecting CX delivery.
Lack of empathy or human touch
Using NLP in CX delivery can allow contact centers to provide quick and efficient responses to customer inquiries, but it may lack the empathy and personal touch that human agents can provide.
Any form of CX delivery that comes across as artificial, mechanical, or unempathetic can impact customer satisfaction, particularly in cases where the customer is experiencing a complex or emotional issue and is expecting a personalized resolution to this through the interaction.
Data security, privacy concerns and risk of breaches
The use of NLP in contact centers requires the collection and processing of large amounts of personal data from customers, which can raise concerns about data privacy and security against unauthorized access and misuse.
Organizations need to ensure that they comply with data protection regulations and that they have robust cybersecurity measures in place to protect sensitive customer data.
Is NLP the right move for your contact center?
Find out without a doubt whether integrating NLP is the right move for your contact center operations and how it may affect the CX delivery of your organisation through a comprehensive analysis of the configurations of your legacy contact center or CCaaS solution.
Class-leading automated discovery services can ensure accuracy and speed in providing the insights you need within your CX environment so that you can make data-backed decisions geared toward CX excellence.