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How to use AI to automate customer service emails

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Emails are the bane of many people’s lives especially if you are in the customer service section of your business or industry. Thanks to the explosion of artificial intelligence over the last few years automations are now available to help you manage your email inbox more effectively. This quick guide provides an overview of how you can automate up to 90% of all customer emails using AI.

Automating customer service emails using AI is an approach that has the potential to streamline operations, improve customer satisfaction, and save businesses significant amounts of money and employees time. Enabling them to turn their focus to other more human orientated tasks that are possibly a little less boring than replying to emails all day.

This method detailed by Michael Borman exploring how it’s possible to automate up to 90% of customer emails, handle multiple queries in one email, and connect to a company’s knowledge base for product information. It will also discuss how to look up the order database for shipping updates, use a Fast API endpoint to trigger the agent, and utilize a vector database for company documents and manuals.

How to use AI to automate customer service emails

The automation of customer service emails using AI involves creating an agent capable of handling multiple queries in a single email. This agent can connect to the company’s knowledge base to answer questions about products, and look up the order database to provide updated shipping information. The agent is hosted on a fast API endpoint and has access to two tools: a vector database of all company documents and manuals, and the order database. This allows the agent to look up a customer’s order based on their email and provide information about shipping and delivery dates.

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The responses generated by the agent are checked and formatted by another agent to ensure accuracy. If the response is correct, it is formatted using HTML and sent off automatically. This entire process takes about 40 seconds, allowing for quick responses to customer emails. This rapid turnaround time is a significant advantage of automating customer service emails using AI, as it can greatly enhance customer satisfaction.

The vector database, which is a crucial tool for the agent, is created using Pinecone. The large language model used in this process is GPT 3.5. The agent is instantiated with a system message that tells it what it needs to do, such as providing accurate and timely information, escalating issues to other departments if necessary, and obtaining all necessary information.

Once the agent is ready, it is deployed on Render, a cloud service provider. The automated process is set up on Integromat, a workflow automation tool, which watches for new emails, formats the JSON, makes an HTTP request, checks the email for formatting errors, and sends the email. This process is demonstrated using a hypothetical solar panel sales company, but it can be applied to any business that relies heavily on email communication with customers.

The automation of customer service emails using AI could save e-commerce sites thousands of dollars by reducing the need for virtual assistants. It’s a powerful tool that can significantly enhance the efficiency of customer service operations, allowing businesses to focus more on their core competencies and less on managing customer inquiries.

Automating customer service emails using AI is a game-changing approach that can revolutionize the way businesses handle customer inquiries. By leveraging AI, businesses can automate up to 90% of customer emails, handle multiple queries in one email, and connect to their knowledge base for product information. This not only improves customer satisfaction but also saves businesses significant amounts of money.

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John Smith

My John Smith is a seasoned technology writer with a passion for unraveling the complexities of the digital world. With a background in computer science and a keen interest in emerging trends, John has become a sought-after voice in translating intricate technological concepts into accessible and engaging articles.

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