Modern customers have high standards. 46% expect companies to respond to emails in less than 15 minutes, but agents take days to respond when your service desk is inundated with emails. Automating emails is a no-brainer solution to quickly clearing your email backlog.

The problem? Most email automation tools fail to generate personalized responses, understand the context of the conversation, and use your brand’s tone of voice. That’s where an AI agent comes in.

An AI agent can tailor-make responses for each email, refer to previous interactions to understand the context of the customer’s email, and follow your brand guidelines to generate responses that sound human.

In this guide, we walk you through the process of automating customer service emails and things to consider.

What is email automation for customer service?

Customer service email automation involves using AI-powered software to deliver automated and personalized responses to customers. An AI agent can take care of the most complex inquiries, send timely follow-ups, and keep your customers feeling like VIPs while your customer service team focuses on the strategic parts of their job.

How to automate customer service emails

The meaning of email automation varies across the board, whether it’s providing a generated response or responding autonomously. If you’re like most modern companies, you want software that can independently tackle complex queries. And that’s why selecting software that’s easily trainable and capable of generating hyper-personalized responses is critical.

With that in mind, let’s dive into the process of automating customer service emails. We’ve divided the process into two parts: selecting software and training the model.

1. Select automation software

Choose your weapon carefully. While the internet is loaded with email automation tools, a large portion of them are email marketing tools. Narrow your options down to tools that automate emails for customer service, and filter them based on:

• Availability of AI technologies: Look for conversational AI capabilities when selecting an automation platform. Steer clear of traditional tools that rely on scripted responses — they sound robotic and translate to lower customer engagement and satisfaction. Only tools with modern technologies like generative AI , natural language processing (NLP), and machine learning can help you deliver personalized responses at scale. You also want to be on the lookout for ones that regurgitate a generated response and wait for a human to approve it. We want to streamline and improve efficiency on your team, not add bottlenecks!
• Integrations: Pick a platform that plays ball with other systems in your tech stack. A generative AI agent that integrates with your email system (like Gmail or Outlook), CRM, and knowledge base makes it easier to access the pool of information required for quick and personalized responses.
• Reasoning capabilities: Instead of wasting time and resources on code-heavy, old-school scripted chatbots , use an AI-powered solution capable of reasoning and taking action through complex customer requests to deliver accurate, relevant, and safe resolutions.
• Coachability: Software with machine learning capabilities learns with every interaction. In addition to things it learns “on the job,” you can proactively offer additional coaching through feedback and guidance.
• Omnichannel support: Why stop at email? The top automation tools can help you automate customer service across channels, including chat, social media and phone. An added bonus if it's easy to apply across multiple channels.

Here’s the problem: most email automation tools don’t check all the boxes. If you’re looking to automate customer service emails with a dash of your brand’s personality, track response performance, deploy across channels, and coach itself based on interactions, consider Ada’s AI Agent.

It works as your service agent’s sidekick by automating not just email responses, but also actions that your customers request. For example, suppose a customer requests the AI agent to cancel an order. The AI agent can promptly take that action and make necessary changes to inventory records in your ERP or inventory management solution.

2. Train the software

An AI agent is easy to train with the right guidance and data. Ideally, the AI agent will have features that make it simple to train it on how you want it to interact with your customers. Here’s a quick overview of how you can get the process rolling:

• Gather training data: Collect training data for your AI agent. The dataset may include FAQs, knowledge base, and old customer conversations. Here are some examples of data to include:
  • Data to infuse brand personality: Add details about how you want your bot to sound. Is your brand’s tone professional, humorous, or playful? Provide the AI agent with instructions on matters like preferred format for responses and ways to handle sensitive topics. Old customer conversations are also a goldmine of training data. Select conversations that reflect your brand’s tone to help the AI understand what you’re aiming for.
  • Data that helps generate accurate responses: The more information the AI agent has about your product, company, and customers, the more accurately it will be able to respond to customers. Include FAQs, knowledge base content, and any internal documentation to offer the AI agent all the information it needs.
• Prepare training data: The data you feed needs to be error-free. This means you must audit and update information across sources, such as your knowledge base. To prepare your dataset:
  • Clean data: Replace personally identifiable information in the dataset with placeholders like [Customer Name] and [Address]. Remove irrelevant content, such as internal notes that customers don’t see, and spam emails. Also, remove outliers or anomalies.
  • Organize data: Maintain your data in a structured format, like CSV or JSON files. Divide your data into categories based on query type, such as order status, technical support, and product information. Tag each query and response with its corresponding category — this helps the AI agent understand the context and relevance of each interaction. It’s also important to ensure equal representation in all categories to avoid bias.
• Feed data: Once you’re ready with training data, feed the data to your AI agent. Most AI-powered automation tools have a built-in option to upload files in certain formats or paste plain text. Some may directly pull information from your knowledge base once it’s integrated.
• Test and iterate: Use the AI agent yourself to see how well it answers questions. Does it answer your questions accurately and adhere to brand guidelines? If not, make adjustments as needed. Be sure to implement a feedback loop where human agents can flag incorrect responses and provide corrections so the AI agent can learn continuously.

4 Things to consider when automating customer service emails

Before you jump in and start automating customer service emails, here are a few things to keep in mind:

Speak your customer’s language

Select an email automation tool that’s capable of understanding emails and generating responses in multiple languages. Multilingual support is critical for multinational brands. In fact, 40% of global consumers won’t buy from a company that doesn’t speak their native language.

It’s also important for brands that only operate in North America — about 8.5% of the U.S. population 5 years and older spoke English less than “very well” according to the United States Census Bureau . To offer these customers help in a way that’s easy for them to understand and to take a more inclusive approach to offering great customer service, you need a multilingual AI agent.

Context is critical

Don’t let your AI agent be a clueless intern. Ensure the AI agent has the ability to understand the context of the conversation. Here’s how:

• Dynamic data retrieval: Enable the AI agent to fetch real-time data from back-end systems. If a customer asks about their order status, the AI agent should have access to your order management system so it can fetch the correct information and relay it to the customer. Ada’s AI agent can even modify the orders based on the customer’s request.

• Annotate training data: Annotations help the AI agent understand how different pieces of information are related. This is vital for the AI agent to learn to naturally maintain context. If a customer asks about their order status in one email and a change of address in another, annotations will help the AI agent understand that these are connected.
• Regularly update information sources: Keep your knowledge base and other information sources updated with the latest information about your products, services, and policies. Access to updated information allows the AI agent to provide contextually appropriate responses. For example, if a customer asks if they can return their product under the new return policy, the AI agent will understand what the customer is talking about if you’ve updated your internal documentation and fed it to the AI agent.

Don’t play fast and loose with data

Before you put money on the table, make sure the platform you’re about to sign up for isn’t a security sieve. Here’s how you can vet your customer service email automation tool:

• Look for encryption: Find a tool that offers end-to-end encryption for data in transit and at rest. Encryption ensures that customers’ sensitive data doesn’t float around on the internet waiting to be stolen by cybercriminals.
• Compliance credentials: Major data protection credentials like SOC2 and HIPAA tell you that the company cares about your privacy and has measures in place to protect it. It’s a badge of honor they earn after passing rigorous tests and meeting the governing body’s standards for data protection.
• Regular audits: The company should be as paranoid as you when it comes to security. Regular security audits and vulnerability assessments tell you that the company is confident about its security measures and is proactively looking for ways to find and fix any gaps.
• Secure APIs: Make sure the AI software isn’t an open door. If the platform offers APIs, look for authentication mechanisms like OAuth and ensure they follow best practices to prevent data breaches.

Test, tweak, repeat

You don’t want to be caught off guard with half-baked responses from your automation tool. That’s why you should rigorously test the AI agent and make sure it’s capable of answering the most bizarre queries. To test the AI agent:

• Simulate customer interactions: Throw a mix of common, complex, and bizarre questions to see how the AI agent handles them. You want the AI agent to respond respectfully and accurately and use a tone suitable to the context of the conversation under all circumstances.
• A/B test: Use A/B tests to compare different versions of the AI agent’s responses. Analyze which version offers the best automated resolution rate and highest customer satisfaction scores .
• Test for unusual scenarios: Analyze how the AI agent deals with unusual, rare, and tricky queries. Does it crumble under pressure or handle these situations gracefully?

There may be more tests to consider, depending on your business model and industry. Run these tests periodically and make adjustments where needed.

Goodbye, customer attrition

Automation is the only practical way to respond to customers in real time at scale. Thanks to AI, these responses are accurate, extensive, and personalized. But businesses beware, not all AI solutions are capable of delivering the experience you strive to offer your customers.

That’s where Ada comes in. Ada helps you transform customer experience through its fully generative, omnichannel AI Agent that automates customer service via emails, calls, and chat. If that sounds interesting, let’s talk about how Ada’s AI Agent can give you an edge over competitors.