Gael Breton8 min readPartner postsOctober 3, 2019

Analyzing your historical data to improve email marketing

Analyzing your historical data to improve email marketing

According to HubSpot, 93% of B2B marketers use email to distribute content. Moreover, it is estimated that companies in the United States will spend over 350 million dollars on email advertising in 2019.

Email is one of the most effective marketing channels you can use. However, there is a difference between email marketing and email marketing that generates results.

If you want to be part of the group that generates results (and who doesn’t?) just keep reading. You’ll learn about the different types of historical data you can use to improve your email efforts.

An essential part of your email marketing strategy is knowing how to extract and use historical data to fuel your future campaigns.

With the right strategy in place, you will know what to do when examining metrics such as:

  • Click-through rate (CTR)
  • Open rate
  • Conversion rate
  • Return on investment (ROI)

On the other hand, if your strategy is outdated or non-existent, your performance will suffer.

While similar in some ways to A/B testing, there’s one big difference: instead of running a test to see what generates the best result, you are focusing on useful information that you already have. And since you already have what you need, it’s easier to hit the ground running.

Let’s start with the most obvious way to use data to make more informed decisions.

You’ll run campaigns that are successful. You’ll also run campaigns that flop. It’s in identifying what went wrong with the ones that flopped where your future success lies. 

By reviewing the data associated with both your successes and failures, you will be able to tell what changes you need to make to your future campaigns in order to generate positive results.

To illustrate this better, let’s take a look at the following metrics that show how two different campaigns performed:

MetricsCampaign #1Campaign #2
Open rate20%24%
Conversion rate2%3%

Both campaigns performed well, but there’s more to this data than meets the eye.

Overall, campaign #2 performed best. A higher open rate resulted in a higher CTR. And a higher conversion rate led to a higher ROI.

Your goal is to decipher why campaign #2 outperformed campaign #1. To do this, you can ask yourself questions like:

  • Did you send the email to the same list (and to the same number of subscribers)?
  • Did you send the email on the same day, at the same time?
  • What were the major differences? Subject line? Headline? Use of images? Colors?

As you answer these and other appropriate questions, you’ll find yourself analyzing different types of data, including the following:

Transactional data

Some companies use email marketing primarily to inform their customers and prospects of industry news, new products and services, and other similar announcements.

Others, however, spend a lot of resources on improving their email marketing efforts with the goal of generating more revenue. For these brands, ROI is the most important metric.

Snapfish is a great example of a company effectively using email marketing to generate sales. Here’s an email they recently sent:

snapfish email marketing newsletter example

Clearly, Snapfish wanted this email to get them more sales and increase their web traffic, as most of us do. Pay close attention to:

  • The use of the word “free” to grab the reader’s attention
  • The use of two call to action buttons, both of which are colorful and “loud”
  • The use of a coupon code for 75% off

Sending an email like this can provide you with mounds of transactional data. There are also other types of transactional data that you should keep in mind, such as:

  • Purchase date
  • Total amount spent
  • New or returning customer
  • Number of items purchased
  • Number of purchases (if a repeat customer)
  • Average order value

This data can help you identify your best customers and products while keeping track of how well each call to action performs.

Using transactional data can be a game-changer for your email strategy. You can use this data to create future campaigns based on past performance, with a special focus on the transactional side of your strategy.

Demographic data

Every brand has a target audience, but not every brand has a full understanding of who these people are.

You think you know your target audience, but do you really? How would you describe them?

Examining historical data will answer these questions once and for all. The three most common examples of demographic data include:

  • Age
  • Gender
  • Location

This data is useful for many purposes, including but not limited to:

  • Segmenting your email list
  • Personalizing your emails
  • Email automation

For instance, if you’re running an event in a particular region, you can segment your email list based on people within some fixed distance. This allows you to get a specific message in front of those subscribers for whom the message best resonates.

Behavioral data

Behavioral data is an indicator of what your subscribers are interested in and how they’re engaging with your brand.

There are many ways to collect behavioral data, such as tracking the CTR and open rate of each email.

With the right data, you can make important decisions on how to better engage and connect with your audience.

One technique that allows you to get this data from your email list is to send a behavioral-based email to a subscriber who abandons their shopping cart.

Considering that the average online shopping cart abandonment rate is nearly 70 percent, you can use behavioral data to send a follow-up email and re-engage with subscribers who didn’t complete their purchase with the goal of them completing it.

This chart from the Baymard Institute outlines the top reasons for abandonment during checkout:

top reasons for cart abandonment

The data you collect can help you pinpoint why subscribers are leaving your site without them completing a purchase.

Maybe you find that most of them leave right before entering their credit card information. Or maybe you learn that a website error at checkout drives them away.

Regardless of your findings, a follow-up email - typically within 24 hours of abandonment - can do wonders for your conversion rate.

Here’s an email example you could use to bring customers back to their shopping carts:

Hey [First Name],

We noticed you abandoned your shopping cart at checkout. What happened?

If it has anything to do with price, here’s a 10% off coupon to help you out. And if something else chased you away, don’t hesitate to contact us with your questions and concerns. We’ll take care of you!

Thanks again for visiting our website!


[Company Name]

Your email won’t bring back every single person who abandoned their cart, but it should successfully re-engage at least some of your subscribers.

When you go beyond the basics of how to use behavioral data, you’ll find a variety of ways to make it a prominent part of your overall email marketing strategy.

Are you among the 96 percent of people/organizations that believe email personalization can improve performance?

If not, you’re doing your company a disservice.

Here’s the harsh, yet true, reality: with so much data at your fingertips, there’s no excuse you can make to ignore email personalization. It’s as simple as that.

These are just a few of the many ways to personalize your emails:

  • Offer coupon codes to specific subscribers, like those who have made a previous purchase
  • Personalize your email content based on your subscriber’s location, age, or gender
  • Display products/services based on your subscriber’s transactional data, such as purchase date and amount spent

Email personalization isn’t a daunting task if you have the right data. Fortunately, the right data can be found by combing through past email campaigns.

Extracting and using historical data allows you to tweak future email marketing campaigns to improve your CTR, conversion rate, open rate, and most importantly, your ROI.

If you’re not sure of where to start, the points discussed in this article are a good starting point, let them guide you. Soon enough, you’ll have a better understanding of how to use historical data to improve your email marketing strategy. If you choose to start using and understanding what your data means, be sure that your efforts will not be in vain.

Do you currently use historical data when creating a new email marketing campaign? What data points do you consider most important? Let us know in the comments!

Gael Breton

Gael Breton is Co-founder of Authority Hacker. He is passionate about online marketing and is tinkering with new marketing techniques all the time. You'll often find him testing the latest tools or getting hands-on with the latest online marketing trends over at

He loves marketing automation and is always playing around with new funnel ideas to make the most out his audience engagement. If there's a way to get his audience more involved, Gael is on it in a heartbeat! You'll also often find him musing over the latest online marketing trends, trying to work out what's going on in this crazy world of internet marketing. He loves trying to predict the future of the industry (even if he sometimes misses the mark!)