Chat GPT is one of the most innovative tools transforming the landscape of customer service. This artificial intelligence model is redefining the “rules of the game” across multiple industries, and contact centers are no exception. In this article, we explore the opportunities ChatGPT provides for call centers and contact centers, as well as its transformative impact on the industry as a whole.
What Exactly Is Chat GPT?
Chat GPT (Generative Pretrained Transformer) is an artificial intelligence model developed by OpenAI. The technology was built using deep learning methods to generate text based on specific prompts. At its core, Chat GPT operates on vast datasets that encompass a wide range of topics.
However, it is important to note that the model’s training data is limited by specific timeframes. ChatGPT operates based on information available up until a certain point and does not update its knowledge in real time. For example, the model might not be aware of recent events or changes that occurred after its training was completed. Each version of ChatGPT specifies a cut-off date for its training data. When up-to-date information is required, this limitation should be considered, and the information should be verified using additional sources.
Model updates occur during the release of new versions when OpenAI retrains ChatGPT on more recent datasets. This means that versions of ChatGPT with later training dates contain updated information but still may not fully reflect the latest developments at the time of the query.
What is a Generative Pretrained Transformer (GPT)?
Previously, we mentioned the term “Generative Pretrained Transformer.” But what exactly does it mean? This is an artificial intelligence technology designed to create text based on a given prompt.
- “Generative” indicates the model generates new text.
- “Pretrained” means it has been trained on vast amounts of textual data.
- “Transformer” refers to the type of neural network that understands relationships between words in a text.
How it works:
During training, the model learns the structure, meaning, and context of billions of text examples. As a result, it can answer questions, generate articles, write code, and perform various text-based tasks.
The key feature of GPT is its ability to understand context and generate logically connected text. This makes ChatGPT valuable for various domains, from automating customer service to creative tasks.
What Is “Generative Artificial Intelligence”?
As mentioned earlier, Chat GPT learns from enormous volumes of text data, including books, articles, codes, dialogues, and more. During training, the model studies linguistic patterns, sentence structures, stylistics, and semantics. When you ask Chat GPT a question, it analyzes your query and searches its knowledge base for the best way to respond. It doesn’t just provide a pre-existing text fragment but generates new content by leveraging its understanding of context and available knowledge.
In other words, Chat GPT is an example of generative artificial intelligence, as it can create text-based responses based on input data and generate contextually appropriate replies to user queries.
Examples of Chat GPT Use in a Contact Center
Modern in-house and outsourced contact centers utilize Chat GPT across various workflows. Below are specific examples of its applications.
Chatbots for Handling Common Queries
Research indicates that nearly 40% of customer inquiries are repetitive or routine. ChatGPT can instantly resolve these issues, freeing up agents to handle more complex problems.
Many companies integrate Chat GPT capabilities into their customer support chat bots. The integration process generally involves:
- Configuring access to the company’s knowledge base (e.g., FAQs, internal guidelines, CRM).
- Uploading pre-existing response scripts or enhancing the model with specific instructions via API according to company policy.
- Testing and verifying the ChatGPT powered bot in various query scenarios.
- Deploying the chat bot to handle frequent inquiries with the option to escalate to a live agent when necessary.
For instance, consider a contact center for a telecommunications company. This is a prime example of a business where up to 90% of inquiries are standard: How to top up an account? How much balance is left? How to change a tariff plan? A generative AI-based chatbot can process such queries 24/7 within seconds, leaving agents to address tasks that require empathy and compassion.
Suggested Reading: How to Enhance Contact Center Services with Empathetic Support
Assisting Agents with Complex Issues
Generative AI provides extensive opportunities to improve the efficiency of contact center agents. ChatGPT can act as a tool to assist agents by generating quick responses, templates, or suggestions.
An example of such collaboration could involve an agent working in an outsourced call center for an insurance company. Take medical insurance as an example: clients often inquire about policy details, treatment coverage, assistance with arranging medical help abroad, or resolving disputes over payments. These inquiries frequently require knowledge of regional legislation, medical terminology, and even a psychological approach to the customer.
ChatGPT can help agents analyze inquiries, locate information sources, and generate responses. This “collaboration” helps improve key contact center performance indicators such as First Call Resolution (FCR) and Average Handling Time (AHT), boosting overall agent productivity.
Recommended Article: Average Handling Time (AHT): Is This Metric Still Relevant in the Age of AI?
Sentiment Analysis in Text-Based Interactions
What Is Sentiment Analysis? Sentiment analysis involves detecting one or more emotions from textual information. Generative AI models like Chat GPT excel at identifying sentiments and emotions. Using natural language processing (NLP), Chat GPT can detect satisfaction, concern, anger, surprise, anxiety, and other emotional nuances based on keywords.
In a contact center, sentiment analysis with ChatGPT can serve various purposes:
Customer Satisfaction Monitoring
By analyzing large volumes of interactions, trends in customer sentiment can be identified, allowing timely actions to improve service quality.
Identifying Problem Areas
Negative feedback analysis helps pinpoint recurring issues customers face and enables the development of effective solutions.
Evaluating Marketing Campaign Effectiveness
Feedback on marketing campaigns can be analyzed to assess their impact and make necessary adjustments.
Personalizing Customer Service
Depending on the customer’s sentiment, agents can adopt an individualized approach to each interaction. Given the trend toward hyper-personalization in contact centers, implementing ChatGPT for sentiment analysis is highly relevant.
Automating Outbound Communications
ChatGPT significantly enhances the efficiency of outbound communications in contact centers. By generating various text formats, it can automate the creation of personalized messages tailored to individual customers. Applications include:
- Generating customized email responses.
- Creating text for mass mailings (promotions, reminders, thank-you messages, etc.).
- Crafting scripts for outbound IVR menus.
- Automatically generating responses to customer reviews on social media.
These examples illustrate how ChatGPT can support outbound contact center operations. However, as mentioned earlier, the results generated by ChatGPT require mandatory human review. This ensures the avoidance of potential errors, misinterpretation of data, or misunderstandings that could negatively impact interactions with clients. Human oversight guarantees the accuracy of the content and its compliance with corporate standards and policies.
Training and Onboarding New Employees
When it comes to AI in contact centers, creating an internal ChatGPT-based chatbot for training is often one of the first ideas that comes to mind. By uploading information about company policies, conversation scripts, and product or service specifics, you can create a ready-to-use training simulator for agents to practice handling online chats.
Additionally, ChatGPT can be used to build a knowledge base containing answers to frequently asked customer questions. New agents can quickly find the necessary information using ChatGPT as a search tool. This enables them to provide clients with more accurate and prompt responses.
Advantages of ChatGPT for Customer Service in Contact Centers
The implementation of ChatGPT in contact center processes is one of the most effective ways to optimize customer interactions. This tool helps reduce agents’ workload, provide quick responses, and improve the overall customer experience. Let’s explore its most significant benefits in more detail.
24/7 Availability
One of ChatGPT’s key advantages in contact centers is its ability to operate around the clock. This ensures that customers always receive support, regardless of the time or location. For instance, customers can submit inquiries outside regular business hours or from different time zones and receive instant responses.
For outsourcing contact centers that serve international companies or industries with a high volume of incoming requests, 24/7 availability helps reduce wait times and maintain high customer satisfaction levels.
Fast Response Time
ChatGPT facilitates quicker processing of standard customer inquiries. This is especially critical for industries with high inquiry volumes, such as telecommunications or e-commerce contact centers.
AI-based tools provide responses within seconds, significantly reducing wait times. Furthermore, ChatGPT can interact with multiple customers simultaneously, easing agents’ workload and speeding up service processes.
Cost Reduction
Using ChatGPT in customer service allows contact centers to optimize their budgets. Automating routine tasks reduces the number of agents needed to handle standard queries. For companies operating with limited resources, this enables them to redirect saved funds toward other business processes or innovations.
Support During Peak Loads
During seasonal surges in activity or promotional campaigns, the volume of customer inquiries can increase significantly. ChatGPT ensures efficient handling of high volumes of requests, providing timely support even during peak loads.
For example, consider an outsourced contact center for the travel and tourism industry. During holiday periods, ChatGPT can handle inquiries about bookings, tariffs, or travel regulations, allowing agents to focus on resolving more complex issues.
Standardization of Responses
When integrated with contact center systems, ChatGPT can maintain a unified knowledge base, ensuring consistent and accurate responses. This is particularly vital in industries requiring precise information, such as finance or healthcare.
In contact centers, this helps prevent errors and confusion, enhancing trust and customer loyalty. Agents can also leverage ChatGPT for quick access to information, ensuring high-quality service.
Improved Contact Center Processes
ChatGPT proves valuable for optimizing contact center workflows, including tasks related to after-call work (ACW). With ChatGPT integration, agents can automatically receive structured information about interactions, such as conversation highlights, recognition of key customer queries, and recommendations for follow-up actions.
For instance, after a call, ChatGPT can automatically generate notes for CRM systems or create response templates for future customer interactions. This significantly reduces the time spent on post-call processing, enabling agents to focus on their next tasks. As a result, team productivity increases, and customer inquiries are handled more efficiently.
Conclusion
AI-powered tools like ChatGPT are becoming essential in contact center operations. They automate routine tasks, such as handling standard inquiries or preparing reports, allowing agents to focus on more complex issues requiring a human touch.
Despite AI’s efficiency, agents remain indispensable for resolving emotionally sensitive situations or non-standard customer requests. Currently, neither ChatGPT nor any other AI model can fully replace contact center agents. However, AI tools can significantly enhance their performance, creating a synergy of technology and personalized service.
By adopting AI, contact centers reach a new level of digital customer experience. Process automation and accurate data analysis not only improve service but also ensure fast and high-quality support for customers.
