AI in Customer Service: Beyond the Hype Cycle and into Enhanced CX
According to Gartner’s Hype Cycle for AI Customer Service and Support Technologies report, 20-25% of AI advocates plan to replace some of their service agents with AI-powered customer service bots or systems. While this might sound concerning for service jobs, the real impact is more significant on customer experience (CX) than on employment.
Below is a diagrammatic representation of AI’s hype in customer support:
(Source)
As per the report, generative AI is at the peak while many others are already lying low in the trough of disillusionment, a phase where after the initial hype and inflated expectations surrounding a new technology, there comes a period where interest wanes as implementations start failing to deliver expected results.
The question is: will AI face the same in customer services? This article will explore AI’s utility in enhancing CX through better interactions.
How AI-Powered Customer Service Transforms Support and Communication
1. Automated Responses to Inquiries and Complaints
AI-powered customer service allows businesses to automate responses to common inquiries and complaints. These tools possess NLP capabilities that allow them to interpret complex user queries with a more nuanced understanding. With this knowledge, these tools can understand different questions, know the intent behind complaints, and provide accurate answers to resolve them quickly.
The Result: Improved response times, making the customers feel more acknowledged.
2. Exit Intent
Exit intent refers to the exact moment when a customer shows signs of leaving a website or application. Integrating AI in customer support practices can help you stay ahead of them. AI can study visitors’ behavior and identify certain “signs” after which a majority of them leave. This information allows businesses to engage with them through timely prompts, special offers, or product recommendations in an attempt to make them stay.
The Result: Reduced bounce rates which helps with customer loyalty.
3. Self-Service Assistance with AI Chatbots
The integration of AI in customer support also extends to providing self-service assistance through intelligent chatbots. These chatbots help customers navigate through your website/application, assist with FAQs, troubleshoot common issues, and provide other resources to help visitors discover what they’re looking for. This makes it easier for them to find solutions on their own.
The Result: A convenient customer experience that may generate more repeated visits.
4. Personalized Recommendations
AI-powered customer service bots can enhance the shopping experience by offering personalized product and service recommendations. By understanding their preferences and behaviors, AI can identify the products or services that are most likely to appeal to each customer. This way, the bots can suggest products or services tailored to individual preferences, making it more likely that customers will make a purchase.
The Result: Increased likelihood of conversations.
5. Internal Employee Communications
AI-driven customer service solutions can also improve internal employee communications. Besides automating routine workflows, they can provide easy access to information by retrieving answers to common questions, such as HR policies or IT support queries. This reduces waiting times, allowing employees to find what need quickly and get back to their primary responsibilities.
The Result: Enhanced overall efficiency and productivity.
6. Round-the-Clock Support
AI-powered customer service has enabled businesses to offer 24/7 support to customers in different time zones. This constant availability is particularly beneficial for international companies, allowing them to cater to global customers without any delay, no matter where they are. Whether it’s a query in the middle of the night or a weekend issue, AI can handle it even if you’re not there at the moment.
The Result: Increased customer satisfaction and the ability to cater to global customers across different time zones.
The Impact of AI-Powered Customer-Facing Services
Let’s look at a few numbers to picture the true impact of integrating AI tools, such as ChatGPT.
- Custom-trained AI chatbots can reduce customer bounce rates by up to 45%.
- AI in customer support can improve response accuracy by as much as 80%.
- A 2023 study found that nearly 25% of surveyed companies saved between $50,000 and $75,000 annually by integrating AI tools like ChatGPT into their customer support operations.
Evidently, ChatGPT has transformed how we interact with customers, automating responses with nuanced contextual understanding. This automation has reduced reliance on human customer service executives, allowing businesses to handle routine queries and communications more efficiently. The benefits are clear: cost savings, better response accuracy, and streamlined operations, all driven by AI-powered customer service.
Implementing AI-Powered Customer Service
While integrating AI in your customer service operations offers many benefits, it is a complex process that alters traditional workflows. It’s essential to approach this transition thoughtfully to avoid potential disruptions and ensure a smooth implementation. Here is a guide to help you make this leap with ease.
1. Custom-Train a GPT Model Using your Data
To get the most accurate and relevant responses, it’s essential to train it on your company’s specific data and knowledge base. This will involve gathering information on:
- Consumer queries and your teams’ responses
- Complaints
- FAQs
- Product details, including reviews
- Troubleshooting guides
This will help the AI chatbot to better understand your business and target audience.
Note: If you already have AI in customer support operations, you can fine-tune it for more targeted use cases using relevant data.
2. Process and Anonymize your Data for Privacy
Before training an AI model, it’s crucial to prioritize customer privacy and adhere to data protection regulations. This means cleaning your dataset to remove any personally identifiable information (PII). Taking these steps not only protects customer data but also builds trust in your AI-powered customer service system. When customers see their information is handled responsibly, they feel more comfortable.
3. Fine-Tune a GPT Model
Once you have processed your data, use it to fine-tune the latest GPT model. This is done by formatting this data into structured conversation-like exchanges so that the model learns from both prompts and responses. The next step is to use certain algorithms to identify patterns and relationships within this data and adjust its parameters to get the desired output.
4. Monitor and Optimize
After fine-tuning, it’s important to see your AI-powered customer service bot’s performance by testing its responses to various customer inquiries in different scenarios. This will allow you to identify areas for improvement and understand how well the bot performs. Based on the results, you may have to retrain the model with some additional data or refine its training.
The process might seem intimidating, but today, there are readily available low-code and no-code ChatGPT builders that simplify building and deploying a basic AI-powered customer service system. However, these off-the-shelf solutions may lack the specific functionalities needed to address unique challenges in your business. In these situations, a custom-built AI-powered customer service system may be a better option. Working with experts in ChatGPT integration or AI/ML development can ensure the system is designed to meet your unique business needs.
Endnote
The benefits of AI in customer support are undeniable, but relying solely on AI to enhance your customer-facing operations isn’t advisable. There’s a growing concern that AI could make it harder for customers to reach a live agent, potentially discouraging them from seeking help for more complex queries or complaints. The key is to strike a balance between automating support and maintaining a level of personal assistance to preserve that “human touch,” and this onus lies with service and support leaders. They must gradually and consciously build consumers’ trust in AI; only then can it be a successful transition to automated customer service.
Author Bio:
Amelia Swank is a seasoned Digital Marketing Specialist at SunTec India with over eight years of experience in IT industry. She excels in SEO, PPC, and content marketing, and is proficient in Google Analytics, SEMrush, and HubSpot. She is a subject matter expert in Application Development, Software Engineering, AI/ML, QA Testing, Cloud Management, DevOps, and Staff Augmentation (Hire mobile app developers, hire WordPress developers, and hire full stack developers etc.). Amelia stays updated with industry trends and loves experimenting with new marketing techniques.
ABOUT THE AUTHOR
