How AI is simplifying deliverability for enterprises

Email has been around for decades, and it remains one of the most important communication channels for businesses. Almost every big enterprise, from tech giants to retail chains, relies on email to reach customers, partners, and employees. But sending an email isn’t as easy as typing a message and hitting “Send”. When companies want to send thousands or even millions of emails, there is a big problem they run into: ensuring those emails get delivered to the inbox and not the spam folder.

For a long time, companies have depended on best practices and manual checks to ensure their emails don’t get stuck or blocked. They have followed rules about how often to send, how to avoid spammy content, and how to maintain a good sender reputation. At the same time, artificial intelligence (AI) has made huge strides in marketing. Today, many email/marketing teams use AI to figure out who the best audience is, when the best time to send is, and what kind of content is most engaging. But surprisingly, less attention has been given to one crucial piece of the puzzle: how those emails are sent.

“How to send” refers to the technical steps involved in making sure your emails travel smoothly from the sender’s server to the receiver’s inbox. This involves complex processes like handling bounces, managing sending speeds, shaping traffic so you don’t overload certain internet service providers (ISPs), and keeping your sender reputation high. Now, AI is stepping in to revolutionize these processes, making them more efficient and smarter than ever before.

What is email deliverability and why does it matter?

Before we jump into the role AI is playing, it helps to have a clear idea of what “email deliverability” means. When we talk about deliverability, we’re asking: What percentage of the emails you send land in the inbox rather than the spam folder (or getting blocked altogether)? If you send 1,000 emails and only 500 of them make it to people’s inboxes, you’ve got a deliverability problem.

• Low deliverability = wasted money, lost chances to speak to customers, and a hit to your brand’s reputation.
• High deliverability = your emails reach the right people at the right time, which often leads to more engagement, more sales, or better communication overall.

For enterprises, this can be the difference between a successful marketing campaign and a failed one. If you’re a direct sender, meaning you manage your own email infrastructure or use a specialized sending service, you need to pay close attention to factors like your IP reputation, domain reputation, and the content of your emails. Until now, many of these tasks have been done with help from tools or best-practice guidelines. But with AI, we can make these tasks smarter, faster, and more predictive.

When people talk about AI in email, they often think about:

• Personalization: Using data to decide which product or content to show each subscriber.
• Segmentation: Grouping subscribers based on their interests or buying history.
• Send-time optimization: Finding the best time of day to send emails to each subscriber.

These are very helpful, but they don’t address the underlying question of deliverability directly. It’s one thing to know what kind of content your audience wants. It’s another thing entirely to ensure that your email systems are recognized by mailbox providers (like Gmail, Outlook, etc.) as trustworthy.

Why should I focus on “How to send”?

Below, we’ll explore four key areas where AI is simplifying these technical challenges:

1. Reputation management – Protecting your email-sending reputation by analyzing and responding to engagement data, spam complaints, and other crucial signals.
2. Dynamic traffic shaping – Controlling the speed and volume of your sends so mailbox providers don’t get overloaded or suspicious.
3. Intelligent bounce handling – Learning from bounce data in real time, spotting trends, and making smart decisions to protect your lists and your sender reputation.
4. Enhanced reporting and insights – Giving you clear, actionable feedback on your email performance, and guiding next steps to fix deliverability issues.

In the following sections, we’ll dive into each area and look at how AI can take the guesswork out of “how to send,” helping you deliver messages smoothly and keep your sender reputation on solid ground.

1. Reputation management

Your email-sending reputation is like a credit score for your IP address or domain. Mailbox providers track if you send emails that get a lot of opens and clicks (good signals) or if you send emails that get marked as spam or bounced back (bad signals). These signals can cause your reputation to go up or down.

A good reputation helps you deliver more emails to inboxes. A poor reputation sends more of your emails straight to spam. Managing this reputation usually involves careful checking of bounce rates, spam complaints, and other engagement metrics. Many teams try to keep bad signals low, but it can be complicated to figure out how to fix problems if the numbers start trending in the wrong direction.

AI-powered reputation management can analyze huge amounts of data in real-time. For instance, an AI system can look at your bounce rates, spam complaints, and engagement rates from different mailbox providers. Then it can compare that data against patterns it has seen before.

• Early warnings: If the system notices that your emails to a certain mailbox provider are suddenly bouncing more than normal, it can sound an alarm right away or reduce the sending speed. This prevents a situation where you keep sending more and more emails that get bounced, which would hurt your reputation even more.
• Adaptation to mailbox provider policies: Each mailbox provider has its own rules and thresholds. AI can pick up on these rules by learning from your sending history and adjusting your sending behavior. This might include slowing down sends to Gmail if it notices a slightly higher spam complaint rate.
• Insights for improvement: An AI system might notice patterns like “Emails with certain content features tend to have more spam complaints”. Then it could warn you to adjust your content.

With AI’s help, you don’t have to wait for a major reputation problem to show up in your metrics. You get proactive suggestions, allowing you to keep your reputation safe and strong over time.

Traffic shaping means controlling how many emails you send at a time and in what order, especially when you have a large list. Imagine you have a million emails to send. Should you send them all in one go to everyone, or should you spread them out over hours or days? And does it matter if you send to Gmail first, then Yahoo, then Outlook, or all at once? The answer is yes, it matters a lot.

Sending a burst of emails all at once can trigger spam filters if it looks suspicious. On the other hand, sending too slowly can mean your promotions or announcements arrive too late. Finding the right balance is tricky, and in many cases, people rely on guesswork or basic rules.

AI excels at pattern recognition and optimization. With an AI system in charge of traffic shaping:

• Real-time adjustments: The AI can monitor bounce rates, complaint rates, and delivery speeds from different mailbox providers in real-time. If it sees that a certain mailbox provider is slowing down or blocking emails, it can reduce traffic to that mailbox provider automatically until it’s safe to resume.
• Predictive analysis: Over time, the AI learns the rhythms of your email campaigns and how mailbox providers respond to them. If the AI sees certain behaviors that often lead to a bounce, for example, more bounces in a certain time frame, or slow down in traffic acceptance by a certain mailbox provider, it could suggest corrective actions.

This dynamic approach frees your team from constantly babysitting the sending process. Instead of manually monitoring traffic in real-time and looking for anomalies, you can rely on AI to shape your traffic flow in a way that maximizes deliverability.

3. Intelligent bounce handling

A “bounce” happens when your email cannot be delivered to a certain address. There are two main types:

1. Soft bounce: Temporary issues like a full mailbox or a problem with the receiver’s server. These can sometimes be fixed if you try again later.
2. Hard bounce: Permanent issues like an invalid email address. If you keep sending to these addresses, your reputation can drop.

If you have too many bounces, mailbox providers see you as a careless sender. It suggests you don’t manage your lists well, which can lead to more of your emails landing in the spam folder or being blocked.

Traditionally, bounce handling is done with static rules: If you see a hard bounce, you remove the address from your list. If you see a soft bounce, maybe you try again later or remove it if it happens too many times. However, static rules don’t always catch patterns or react quickly to changes.

• Pattern recognition: An AI can notice new text patterns in bounces and automatically categorize them for you so that bounces with unknown text patterns are also addressed.
• Contextual decisions: AI can deduce the impact of a certain pattern in bounces. It can look at the error message and the history of that domain, then decide if it’s worth trying again and when. This saves good addresses that might otherwise get removed too soon due to non-delivery for a long period. 

With intelligent bounce handling, you lower your bounce rate, which improves your reputation in the eyes of mailbox providers.

4. Enhanced reporting and insights

If you don’t measure it, you can’t improve it. Reporting tools help you see how well your email campaigns are doing. Are they bouncing? Are people engaging positively with them? Reading standard reports can sometimes be confusing, though. You might see a high bounce rate and not know what to do next. AI-based reporting can do more than just show you data. It can give you insights and actionable advice:

• Automatic analysis: Instead of a long spreadsheet of metrics, you might see a dashboard with key highlights. For example, “Your bounce rate is 2% higher than last week on Gmail because of an uptick in soft bounces. We suggest slowing sending to Gmail until the issue resolves.”
• Drill-Down suggestions: AI can let you click on a high-level metric and see a deeper breakdown of why it’s happening. This helps you avoid guesswork and saves time.
• Predictive delivery analytics: An AI system might predict that, based on your recent open rates, your deliverability is likely to fall next week unless you improve your subject lines or remove unengaged subscribers.

This kind of intelligence is a game-changer because it lets you stay ahead of problems. Instead of reacting after your deliverability has already dropped, you can act early so that it doesn’t affect your sending reputation and ensures your emails are getting through.

Now that we’ve covered four major areas - reputation management, dynamic traffic shaping, intelligent bounce handling, and enhanced reporting - it’s clear that AI can do more than just deciding what to send and who to send it to. By focusing on “how to send,” AI can help senders in several ways:

1. Time savings: A lot of deliverability tasks require constant vigilance. AI systems can handle them automatically, freeing your team to focus on strategy, content, or other marketing efforts.
2. Cost efficiency: Getting blacklisted or landing in spam folders can cost a lot of money in lost sales or lost brand value. AI helps you prevent some of these problems before they happen.
3. Better decision-making: Instead of guessing, you have data-driven insights. AI can say, “Slow down sends to Yahoo because bounce rates are increasing,” or “Remove addresses from this segment because they’re likely to bounce.”
4. Constant improvement: AI gets better over time, as it learns from your sending patterns and your audience’s behavior. The more data you feed it, the smarter it becomes.
5. Higher engagement and revenue: Better deliverability means more emails in the inbox, which leads to more opens, clicks, and conversions.

While AI brings a lot of promise, it’s not magic. You still need to keep a few best practices in mind:

• Data quality is key: AI is only as good as the data it sees. Make sure your email lists are clean, your bounce logs are accurate, and you track user engagement properly.
• Keep up with mailbox provider rules: Mailbox providers are always changing their policies. An AI system needs to be updated or be able to adapt to new rules as they come along.
• Human oversight: AI can do a lot, but you still want a human in the loop. Sometimes you might want to override the AI’s decisions if you have extra context or a specific goal.
• Privacy and compliance: With AI handling large amounts of data, you must make sure you respect privacy laws like GDPR or CAN-SPAM. AI solutions should also uphold these regulations and protect user data.

If you have any questions on email deliverability or would like to know more about how you can effectively use AI, feel free to reach out to us here.