AI for Email Automation: Use Machine Learning to Classify Incoming Emails

AI for Email Automation: Use Machine Learning to Classify Incoming Emails

Patricia Orza

Content Queen

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How Artificial Intelligence can help you automate your emails

Email marketing automation changed the game for businesses, and now email management automation is changing it again. We’re not talking about automating send times and email flows—we’re talking about using AI to revolutionize the way your team handles emails and inbox management.

We’re talking about the future of email management—interested?

Manual email management has some challenges and can cause chaos for you and your team. Native automation options are limited on traditional email platforms, and these systems aren’t built to learn and adapt.

The good news is: there’s a solution that can overcome these challenges—AI email automation tools.

In this article, we’re looking into:

  • What is email automation?
  • How will AI affect email automation?
  • What are the benefits of using AI-based email automation software?
  • What does implementing AI email automation look like?

Let’s get started.

What is AI-powered email automation?

AI-powered email solutions automate email inbox management to simplify your day-to-day email management and associated tasks.

Let’s say you’re starting an email campaign and are contacting a lot of prospects. A day later, you start getting responses to your campaign. It’s going great, and the response rate is really high!

At first, you’re super excited. It seems like your message is resonating with your audience and people are interested in what you have to offer.

But then, so many emails come in. You’re getting lost in the sea of responses—you can’t reply to all of them and your inbox has become a mess.

This is where email management automation saves the day. You can intelligently categorize emails based on their content using Machine Learning.

You’ll be able to address all responses in time, leaving no customer unhappy.

So, how does it work?

Email management automation uses AI-powered text classification to identify and categorize the language used in incoming emails. Text classification algorithms use previous data—data you feed it—to discover patterns that help identify the intent behind an email.

The first step to creating an email management AI model is to train your text classifier to identify different types of emails. There are a number of ways you can do this manually—such as using logistic regression, decision trees, or the KNN technique—or you can do it automatically—using a no-code AI solution. One’s significantly easier than the other—no prizes for guessing which.

Once you’ve trained your text classifier—you can then plug it into an AI model and define input—where new data to be classified comes from—and output—what happens following classification.

This process depends on the composition of the data, however—let’s take a look at the differences.

Structured vs. unstructured data

Data that is structured is ordered and fits neatly into worksheets and database systems. It’s spreadsheets and tables that can be easily connected and understood by machines.

Unstructured data does not have a predetermined structure or organization. It comes in the shape of text, music, photos, and videos, and it can be difficult to decipher for machines.

You can also have semi-structured data, which is somewhere in-between the previous two types.

For example, emails are semi-structured. You can structure them by the sender, topic, date, and other criteria—but, the content of the email is unstructured.

You need an AI solution that can help you with it all.

Table showing the differences between Unstructured Data vs Structured Data vs Semi-Structured Data
Unstructured Data vs Structured Data vs Semi-Structured Data

How will AI affect email automation and inbox management?

We’re glad you asked.

Let’s see what the benefits of implementing AI-based email automation services are in your marketing operations.

Use AI to individualize your responses

Consumers are 80% more likely to buy from a company that offers a personalized experience. Moreover, 72% of customers will only respond to tailored messages.

AI-powered inbox management automation enables you to provide more personalized responses to your emails.

For example, let’s say you send out an email campaign to a segment of your users you think would be interested. AI enables you to classify email campaign responses with tags of your choosing. The text classifying module reads the responses to your campaign, categorizes the replies, and enables you to craft a personalized response to each.

Example of a Levity Workflow Categorizing Email responses
Levity Workflow - Categorize Email Responses

Use AI to decrease your response time

AI is notorious for speeding things up—email management is no different. AI enables you to respond to your customers immediately—whether that’s a specialized support rep or an email automation reply.

For example, you can use AI email automation to instantly categorize service requests. This means that when a user gets in touch with your team, the AI system detects what they’re looking for right away—and sends it directly to the relevant member of staff.

Example of a Levity Workflow Categorizing Email responses
Levity Workflow - Categorize Service Requests

Use AI to increase your conversion rate

If you automate inbox management, you can answer each customer with a customized email and an offer that fits their specific needs.

You can use AI to categorize promising and not promising leads with text analysis—helping you identify leads that you should prioritize.

Send conversion-oriented emails to your priority leads in an automated and efficient way, and boost your conversion rate.

Use AI to track your customer data

AI-based email automation software enables you to track important transactional and behavioral customer data. You can collect data from incoming emails and send it to your integrated tools—such as Google Sheet or your CRM.

Having key customer info automatically sent to your data management tools speeds up your processes and ensures you don’t miss a thing. It enables you to make informed decisions on customer relations and marketing activities.

Use AI to make the most of your team resources

Automation will save your team a lot of time by replacing the manual effort your team is currently putting into managing emails alongside their other responsibilities.

By saving time with AI, your team will have more time to focus on meaningful activities that can grow your business.

Use AI to easily scale your strategy

AI helps you to easily scale any process, including inbox management. This means that if you get more emails, you won’t need more time to manage all these messages.

You’ll be able to seamlessly manage emails, allowing you to scale your workforce and save time.

AI as your email automation tool

Now, let’s see how you can practically implement AI as your best email automation solution.

How does the AI classify emails?

Simple—you provide the model with some labeled email automation examples and it learns to analyze and recognize emails to assign them one of your labels.

Example of a Levity Workflow Categorizing Emails
Levity Workflow - Email Classification

Here are some ideas for email classification:

  • Sentiment: the underlying feeling being relayed, whether that’s positive, negative, or neutral.
  • Topic: categorize depending on the subject matter of incoming emails.
  • Urgency: categorize and prioritize incoming emails by the level of urgency.
  • Team: direct emails to the relevant team member.

Once you’ve classified emails, you can create workflows to perform if this, then that actions—like respond automatically or send to a google sheet.

What could a workflow possibly look like?

So, what does this process look like from start to finish?

Let’s take a look at how you could approach an AI workflow for classifying email campaign responses:

  1. Upload your data: upload your emails to your AI tool so the Machine Learning algorithm can learn. You can also integrate with other tools and get data from external sources, such as Gmail.
  2. Train your model: label your data to teach your model how you want it to categorize incoming emails—whether that’s by sentiment, topic, or any other criteria. The more data, the better—the model becomes more accurate as it processes more data.
  3. Evaluate results: test your model's accuracy to see the quality of predictions. You can then add human review to minimize error and ensure your machine delivers more accurate results every time.
  4. Set up a workflow: this is where you instruct your AI model to perform actions following data categorization—if this, then that. In the case of AI for emails, this could be streamlining emails to the relevant inbox and team members.

If you want to see this process in action, check out how we use AI in our day-to-day at Levity here.

Wrapping up on AI for Email Automation

AI email automation will revolutionize the way you manage your inbox, and enable you to focus on what matters—your product and users.

AI offers a multitude of benefits for businesses of all sizes—whether you’re categorizing incoming emails or analyzing customer feedback.

Levity is an AI model training tool that works with images, documents, and text data. Its no-code approach to automation can help you save valuable time on mundane tasks—join a demo and get started today.

Now that you're here

Levity is a tool that allows you to train AI models on images, documents, and text data. You can rebuild manual workflows and connect everything to your existing systems without writing a single line of code.

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