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:
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.
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:
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.
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.
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:
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:
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:
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:
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:
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:
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:
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.
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:
You can also track click-to-open rate and other metrics.
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:
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:
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:
For example, Simply Be offers a voucher to a group of customers who purchased from the brand the previous month:
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:
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:
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:
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 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:
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 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.
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:
Here are a few ways to prevent (or fix, if they already exist) data silos:
By breaking down data silos and using data effectively, you can improve your email marketing campaigns and make them more successful.
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:
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.