How To Build a Data-Driven Email Marketing Campaign

What is data-driven email marketing?

Data-driven email marketing is the approach of using data to inform and improve your email strategy. It is a continuous cycle of collecting data, analyzing it, applying it to your email strategy, testing, and measuring the results. Then, you repeat the cycle and make adjustments based on the feedback and insights you get.

Data can help answer questions like:

• Who are your subscribers and what are their characteristics?
• What are their interests, preferences, and pain points?
• How do they interact with your emails and website?
• What are their goals and challenges?
• How do they move along the customer journey?
• What are the best ways to reach them and engage them?

By using data to answer these questions, your business can create more relevant, personalized, and effective email campaigns that resonate with your audience and drive conversions.

Why is a data-driven approach to email marketing important?

Email marketing is one of the most powerful and cost-effective marketing channels available. It can generate an average ROI of $36 for every $1 spent. But it also has a lot of variables like deliverability and spam filters, timing and frequency, etc. that affect your results.

To be able to run successful campaigns, you’ll need to rely on data.

Data-driven email marketing can help you:

• Understand your audience better and create more relevant and personalized emails that match their needs and preferences.
• Improve your email performance and results by optimizing every aspect of your email strategy, from design to content to timing.
• Experiment with different ideas and approaches and find out what works best for your audience and your goals.
• Measure the impact and value of your email campaigns and prove your email ROI to your stakeholders.

Now that you know why data-driven email marketing is important, you might be wondering how to use it in your own campaigns. The first step is to choose the right metrics to measure your email performance and set benchmarks.

The most important metrics to pay attention to

Data-driven email marketing requires tracking and measuring various metrics to evaluate and improve your email performance. Here are some of the most important metrics to pay attention to.

Deliverability rate

The deliverability rate is the percentage of emails that reach your subscribers’ inboxes. Calculate it with the following formula:   

The deliverability rate is crucial because it affects all other email metrics. If the emails don’t get delivered, they can’t be opened, clicked, or provide conversions. You need to ensure your deliverability rate is as high as possible. 

You can improve your deliverability rate by following best practices such as:

• Use a reputable email service provider like Selzy.
• Segment and clean your email list regularly.
• Avoid spammy words and phrases in your subject lines and content.
• Use responsive and accessible email templates.
• Send relevant and valuable emails to your subscribers.
• Test and optimize your emails before sending them.
• Track and resolve any delivery issues or errors.

Bounce rate

Bounce rate is the percentage of emails that are rejected by the recipient’s mail servers and returned to the sender. This is how to calculate it:

A high bounce rate can damage your sender reputation and affect your deliverability rate. There are many reasons why bounce happens. For example, the email address doesn’t exist, the inbox of your subscriber is full, sender reputation is poor due to spam complaints, and others. 

Here are a few things you could do to lower the bounce rate:

• Verify and validate your recipients’ email addresses before sending.
• Ask your subscribers to whitelist your sender address or add you to their contacts.
• Use double opt-in or confirmed opt-in to collect email addresses.

Open rate

Email open rate is the percentage of emails that are opened by the recipients. The formula to calculate it is:

The open rate indicates the level of interest and engagement of your subscribers. A high open rate means the email subject line, sender name, and preview text got your subscribers curious and eager to see what you have to offer. 

To improve the email open rate, consider doing this:

• Write catchy and compelling subject lines.
• Use clear and recognizable sender names and addresses.
• Send emails at optimal times and frequencies based on data and testing.
• Segment and personalize your emails based on subscriber data and behavior.

Click-through rate

Email click-through rate (CTR) is the percentage of opened emails that generated at least one click on a link or a button. Here is how to calculate it:

CTR shows the level of action and response of your subscribers. A high CTR means that subscribers are interested in the email’s offer and willing to take the next step. A low CTR might mean that the offer did not match what the subscribers needed or that the offer wasn’t persuasive enough.

Here are a few tips for improving the CTR:

• Write compelling subject lines.
• Avoid overstuffing the email with content and design elements.
• Optimize it for mobile devices.
• Include clear call-to-action (CTA) buttons or links.
• Segment your email list and adjust emails for each of the segments.

Conversion rate

Conversion rate is the percentage of delivered emails that resulted in a desired action or outcome. The action can be anything, depending on your business — e.g., purchase for an e-commerce store, trial or purchase of a paid subscription plan for SaaS. It can also be action from earlier in a buyer’s journey — like a download of a white paper.

Here is how to calculate it:

Conversion rate indicates the level of success and profitability of your email campaigns. Since clicking on a link or button in the email is also a type of conversion, just with a much lower barrier to conversion than buying something, the ways to improve your conversion rate are pretty similar to tips on boosting the CTR. 

The difference here is that you might also need to work on areas outside of email:

• Optimize your landing or sales page.
• Adjust your offer to match your target audience’s pain points better.
• Reconsider your website experience overall — make it more personalized or adjust it in some other way. 

ROI

ROI (return on investment) is the ratio of revenue generated by an email campaign to its cost. Here is how to calculate it (or simply use Selzy’s ROI calculator for marketing campaigns):

ROI shows the efficiency and effectiveness of your email marketing strategy. A high ROI means that you are getting more value from your email marketing than what you are spending on it. A low ROI means that you are not getting enough value from your email marketing compared to its cost.

Here are a few simple tips that might help to improve it: 

• Segment your email list and create different versions of your email, tailored for each of the segments.
• Personalize.
• A/B test different variations of the subject line, email preview, personalization options, and other changes to find the best-performing email version.

Average order value

Average order value (AOV) is the average amount of money spent by customers who make a purchase through an email campaign. It is calculated with the following formula:

A higher AOV means increased revenue and profit. There are many tactics and strategies to increase the average order value — use upsell and cross-sell, offer special package deals, and so on. Here are a few examples: 

• Create an order minimum (e.g., total purchase should be $100 or higher) for the “free shipping” option to become available.
• Set up a cross-sell — offer a product that complements or combines well with customers’ chosen products. E.g.: recommend a t-shirt when they buy jeans, drinks, and desserts when they order a take-out, or pots and growing soils when they buy seeds of flowers.  
• Set up an upsell — offer a more expensive product or service instead of the one they are buying. For example, a subscription plan that has more features (for SaaS), higher quality ear plugs that are better for listening to music, or a gaming laptop with a more powerful graphic card.

Best strategies for data-driven email marketing

Using these strategies, you can enhance the effectiveness of your data-driven email marketing efforts and create impactful and successful email campaigns that resonate with your audience.

Choose your metrics

The first step in data-driven email marketing is to choose the right metrics to measure your email performance. Depending on your email objectives, these might be the best and most important ones:

• Deliverability rate
• Open rate
• Click-through rate (CTR)
• Conversion rate
• ROI
• Average order value (AOV)

You can also track click-to-open rate and other metrics.

Set benchmarks

The next step in data-driven email marketing is to set benchmarks for your metrics. Benchmarks are the standards or targets that you want to achieve or exceed with your email campaigns. They help you compare your current performance with your desired performance and see how you do against your competitors or industry averages.

You can set benchmarks based on your own historical data, your competitors’ data, or industry data. This will help you set up realistic and achievable goals for your email campaigns, and help evaluate your progress.

If you haven’t done any email marketing before, using industry averages as goals might be a good starting point. It will still be a good start even if you’ve done some — but relying on your own historical data is best. Let’s say your average email open rate was 5%. It will be your basis for an email open rate metric, and you can plan your monthly and quarterly goals to be increased from there.   

To start, look at the average email open rate for your industry displayed on the chart below:

And here is a chart showing average order value for different industries: 

Segment your list

Segmentation is the process of dividing your email list into smaller groups based on common characteristics or behaviors. You can segment your list based on:

• Demographic — data such as age, gender, location, income, etc.
• Psychographics — interests, preferences, values, etc.
• Behavior — purchase history, browsing history, email engagement, etc.
• Lifecycle stage — awareness, consideration, decision, retention, etc.

Create different segments for different types of subscribers. Each segment you create should be based on collected data.

Segmenting your list, you can send more relevant and personalized emails to each group and increase your engagement and conversions.

Here are a few examples of how this could play out:

• Segmenting the email database by age into young adults, middle-aged and seniors would let a restaurant send promotions about senior-relevant menus only to them while leaving out the other two groups.
• Segmenting by job titles and then sending content relevant to the roles would immediately make your emails much more personalized and relevant to the readers. E.g., send inventory updates to people from the procurement team.  
• Having a segment for loyal customers (i.e., those who stayed with a business for a year and more) would let you send exclusive discounts or gifts only to these people.

For example, Simply Be offers a voucher to a group of customers who purchased from the brand the previous month:

Personalize your emails

Another way to leverage data for email marketing is to personalize the emails based on the information you have about each subscriber. This should make the message more relevant and appealing to each individual recipient.    

Personalization can look like:

• Using the subscriber’s name or other personal details in the subject line or email body
• Sending emails from a real person or a recognizable sender name
• Sending emails at the optimal time and frequency for each subscriber
• Preparing emails based on the subscriber’s behavior or preferences (like abandoned carts emails, win-back emails, etc.)
• Using emails with dynamic content that changes based on the subscriber’s attributes

By personalizing your emails, you can make them more human and engaging and build trust and loyalty with your subscribers. 

A great example of this is Uniqlo — the company personalized the emails with weather data from the reader’s location:

Analyze the behavior of your subscribers

An analysis is a must when it comes to data-driven campaigns. Specifically, behavior analysis — the process of tracking and understanding how your subscribers interact with your emails and website.

Behavior analysis can help you:

• Identify what triggers or motivates your subscribers to open, click, or convert.
• Find out what barriers or challenges hinder the subscribers from acting (e.g., clicking on a link in the email). 
• See the patterns or trends that are there in your subscribers’ behavior.

You can gain insights into their needs, wants, pain points, and goals. 

These insights can then help to create more relevant and effective emails that are a better fit for your customers’ problems. You will understand what content to send to each segment of your email list, whether a sale is effective, when, and what type of campaign is best for it, etc. 

Optimize your send time

Optimize your send time based on when your subscribers are most likely to open and engage with your emails. Collect the open rate, click-through rate, and conversion rate across different days of the week and times of day and compare them to determine the best time and day to send your emails.

Send time optimization can help you:

• Increase your open rate by reaching your subscribers when they are most active.
• Increase your click-through rate by reaching your subscribers when they are most interested.
• Increase your conversion rate by reaching your subscribers when they are most ready.

A/B test

A/B test different elements of your email campaigns and use the results to improve them. This will let you continuously optimize your emails for better performance and engagement. According to Litmus, brands that A/B test every email get 37% higher ROI than those that never do A/B tests.

Test different subject lines, email designs, calls-to-action, or content variations to see what resonates best with your audience. Then analyze the results to identify winning variations and use them in your future campaigns. 

A/B testing is part of the process for The Hustle, an email newsletter that curates some of the day’s most important headlines in business, tech, and culture.

They constantly test subject lines, which always tie back to their first story of the day, and are often creative and funny:

Send surveys

Send out surveys to your subscribers to learn about their preferences, challenges, or opinions. Use the survey results in your email marketing strategies to refine your messaging, segmentations, and offers. 

Surveys provide direct feedback from your audience and help you tailor your campaigns to their specific needs.

The problem of data silos and how to prevent it

Since the data-driven approach relies on using data, the data needs to be available to the person in charge of email marketing. However, sometimes it may not be the case. Enter a data silo — a data storage accessible to one department or role in a company but isolated from other employees in the same organization.

Data silos happen when information is kept separate in different departments or tools. In email marketing, this means that important data about customers, like their preferences and buying habits, or metrics like ROI and AOV, is kept in different places, and email marketers (or other departments) may not have access to it when they need it. In that case, the decisions are made blindly or based only on partial data.

The same situation can happen if only higher management or certain departments can see the data (while the email marketer who actually does the work can not). This happens more often in bigger companies or in places that have a very clear separation between departments. 

Here’s why data silos are a problem:

• Incomplete customer profiles. Data silos can make it hard to see the full picture of your customers. Without all the information in one place, it’s difficult to personalize your emails and make them relevant to each customer.
• Less effective targeting. When data is in silos, it’s hard to group customers together based on their interests or behaviors. This means your emails might not reach the right people with the right messages, making them less effective.
• Inconsistent messages. If your data is scattered, it can be hard to make sure your messages are consistent across different channels. Inconsistent messages can confuse customers and make them less likely to engage with your emails.
• Missed opportunities for improvement. Data silos make it tough to find patterns or trends in your data that could help you improve your email marketing. Without a complete view of the data, you might miss opportunities to make your campaigns better.

Here are a few ways to prevent (or fix, if they already exist) data silos: 

• Try to bring all your customer data together in one central location, like a customer database or CRM system. This way, you can see all the information you need to create effective email campaigns.
• Make sure the different systems in your company can talk to each other and share data. Connect tools like your email marketing software, CRM system, and e-commerce platform so that information can flow smoothly.
• Set rules and standards for how your data is collected, stored, and used. This helps keep it accurate and secure and makes it easier to share across departments.
• Encourage people from different departments to work together and share knowledge. Regular meetings and collaborations can help break down silos and make sure everyone is using data effectively.
• Make sure your team knows how to use data and understands its importance in email marketing. Provide training and resources to help them improve their skills.

By breaking down data silos and using data effectively, you can improve your email marketing campaigns and make them more successful.

Final thoughts

Data-driven email marketing is a powerful way to create and deliver emails that match your audience’s needs and preferences. By using data to inform and improve your email strategy, you can boost your email performance and results. 

To implement data-driven email marketing, you need to:

• Choose the right metrics to measure your email performance and set benchmarks for them.
• Segment your email list based on common characteristics or behaviors of your subscribers.
• Personalize your emails based on the information you have about each subscriber.
• Analyze the behavior of your subscribers and how they interact with your emails and website.
• Optimize your send time based on when your subscribers are most likely to open and engage with your emails.
• A/B test different elements of your email campaigns and use the results to improve them.
• Send surveys to your subscribers to gather insights about their preferences, challenges, or opinions.

By following these tips and strategies, you can build a data-driven email marketing campaign that will help you reach and engage your audience better and increase your email ROI.