Generative AI is an effective tool for enhancing customer service experiences. With increased service productivity, it allows companies to address customer concerns 24/7. With the help of large language models (LLMs) and deep learning techniques, computer programs can understand complex customer queries and respond like a human.
These AI models generate contextually, technically correct, and coherent responses while analyzing query intent and sentiment. As AI can also extract and process customer’s data, they can provide personalized responses based on the customer’s history faster than a human.
Let’s analyze how generative AI can disrupt customer service and its outcomes.
A Short Note on Generative AI
Generative artificial intelligence is a subset of AI specializing in original and unique content creation based through extensive data sets and analytical capabilities. While operating like a chatbot, generative AI can identify and replicate complex patterns, styles, and structures to generate responses.
It can be answered in the form of text, images, code, audio, etc., and has an uncanny resemblance with the content produced by humans. It has natural language processing features, allowing the programs running on this technology to understand human language and respond in the same manner within seconds.
However, this is not the same as conversational AI, which is also a subset of artificial intelligence but with different configurations. Conversational AI uses predefined results to generate responses, learning from structured data and improving over time.
But generative AI, learns on the fly and sources information through unstructured data, but it does require manual training to become fully functional.
Use Cases of Generative AI in Customer Service Operations
A chatbot has become pivotal for companies to maintain contact with customers and ensure their queries are addressed. Generative AI-based chatbots can further enhance the customer experience by giving personalized responses.
Leveraging its natural language processing capabilities, chatbots, and similar tools can revamp how companies communicate with their customers and build a loyal customer base.
1. Conversational Search
Finely tuned language models can generate natural responses quickly. With these, the customers can find personalized to their requirements and history with the company.
In addition to this, generative AI can further improve this service by providing relevant information for the search query based on the customer’s language. This ultimately leads to better response generation while minimizing the efforts required for translation.
2. Better Customer Service Knowledge
A lot of customer service knowledge is GIGO (Garbage In, Garbage Out). However, the content created for this purpose must be easy to consume, correct, and compliant.
With generative AI capabilities, call center management improves the customer and agent experience by making it easier for the latter to find answers. It can be used to create drafts and repurpose them to address customer concerns.
3. Enhance Call Center Operations
With generative AI, call center operators can automate repetitive tasks and save more time to focus on improving customer service experience. With this, it will become easier to close the feedback loop in customer service operations.
AI can analyze customer complaints, sort them, and organize them into groups. Using this information, companies can make product changes and address the root cause.
4. Taking Actions By Connecting to Backend
Customers can get answers to simple questions like checking order status, accessing bills, updating payments, scheduling appointments, etc., through a bot. These AI-powered bots can index and provide the latest information to the customers.
They can also retrieve real-time information and take action on the customer service agent’s behalf. So, tasks like booking tickets, submitting queries, etc., can be completed by AI bots.
5. Predictive Support
With generative AI, call center managers and operators can predict potential issues with customer experience and product. It can successfully help gauge customer expectations and align them with business priorities.
Sophisticated AI algorithms are employed to identify customer sentiment trends, and conduct real-time analysis, leading to quick and personalized responses.
6. Customer Request Routing
As first-line responders, AI chatbots can successfully handle a high volume of requests and resolve issues. In case the queries are beyond the chatbot’s support, it can promptly escalate the conversation to a human agent to resolve the issues.
The AI program successfully chooses the customer service agent according to their area of expertise and availability.
Implementing Generative AI for Customer Service Support
According to an IBM survey, around 75% of CEOs are eager to implement AI solutions to increase organizational productivity. Within this, the CEOs must implement GenAI for customer services in the following method.
- Define Your Needs: Decide your end goal by implementing AI into customer service support. Figure out the appropriate KPIs to quantify AI’s progress and establish a timeline to implement the system.
- Gather Customer Service Data: Collect and feed customer service data into the AI system. Check the service logs, conduct sentiment analysis, and talk to the support team to get first-hand insights of customer challenges. Shaip generative AI experts can help you collect customer data and build training programs for AI tools.
- Upload Datasets in AI Tool: Train the AI program with relevant, structured, and unstructured data. Categorize the data for contextual understanding and scrape the identifiable information with data de-identification.
- AI Program Training: Choosing a suitable neural network model to build the foundation of your training program, add a range of interaction styles to prepare the AI for customer service support.
- Test and Refine: Test the AI model before full-scale deployment. Conduct pilot tests within a control group and check the performance metrics. Make necessary adjustments to improve the KPIs to their best levels.
Conclusion
Generative AI has some powerful features and functionalities set to overhaul customer services support systems. Where it can address the customer’s issues promptly, generative AI can also replace agents as first responders and communicate with customers like a human.
Whether you are running a call center or have established an in-house customer service support team, generative AI and conversational AI are instrumental in improving customer service experiences.
At Shaip, we help all sorts of companies in setting up their generative AI solutions to improve customer and agent experience.
About Author
Vatsal Ghiya is a serial entrepreneur with more than 20 years of experience in healthcare AI software and services. He is the CEO and co-founder of Shaip, which enables the on-demand scaling of our platform, processes, and people for companies with the most demanding machine learning and artificial intelligence initiatives.
Linkedin: https://www.linkedin.com/in/vatsal-ghiya-4191855/
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