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How To Analyze Email Marketing Data: A Complete
Guide For SaaS Businesses

How To Analyze Email Marketing Data

 

Email marketing is one of the most effective channels for acquiring and retaining customers for SaaS companies.

According to HubSpot, a solid email marketing campaign can yield you up to $36 per dollar spent. That’s a 3,600% return on investment (ROI).

And the thing about any digital marketing campaign is that it’s always important to assess your performance. How else would you know what’s working and what’s not?

This is especially true for email marketing. In order to make the most of your campaign, you need to know how to analyze email marketing data.

And that’s what we’re going to do in this article. We will talk about everything you need to know so that you can properly analyze your email marketing efforts.

 

Factors To Consider In Analyzing Email Marketing Data

 

One thing you need to consider when it comes to interpreting your email marketing data is the diversity of your campaigns. That’s because there are a lot of different factors that can affect how each email is performing.

Here are some factors that you need to be aware of:

 

Email Campaign Type

 

Not all SaaS email marketing efforts are the same. Some are designed to increase brand awareness while others are designed to nurture leads.

All the different types of email marketing campaigns have different goals and recipients. So you need to take this into account when you’re analyzing your data.

For example, if you have a newsletter campaign, it would have different email marketing data from a campaign that’s designed to increase free trial sign-ups.

So, comparing your email marketing data among different campaign types would only be like comparing apples to oranges.

Not very helpful, right?

What you need to do is to take a look at each campaign type separately. This will give you a more accurate idea of how each campaign is performing and what needs to be improved.

 

Your Industry

 

The industry you’re in will also have an effect on how your email marketing data should be interpreted.

For example, if you’re in the B2B SaaS industry, your customers are more likely to be using work emails. This means that there’s a higher chance that they’ll see your emails during work hours.

On the other hand, if you’re in the B2C SaaS industry, your customers are more likely to use personal email addresses. They might receive your emails at any time of day, but they’re more likely to see them during their free time.

What’s more, the SaaS industry itself is pretty diverse. You could be offering a SaaS product for sales, accounting, human resources, project management, or any other number of business functions.

And each type of SaaS product will have a different target market. So you need to take that into account when you’re looking at your email marketing data.

You can’t simply compare email marketing data between two different industries and markets. You need to look at how each industry and market affect email marketing data before you can make any conclusions.

 

Target Segment

 

Different email list segments will have different levels of engagement.

For example, you might notice that millennials and Gen Z audiences might be less inclined to engage with your emails compared to recipients comprising of older generations.

Or you could be segmenting your email lists based on SaaS sales funnel stages.

In this case, you would expect people who are in the awareness stage to have lower engagement levels than those who are in the consideration or decision stages.

And that’s perfectly normal.

Again, what would be helpful is analyzing your email marketing data separately for each target segment.

 

What Is The Iceberg Model?

 

Like we have discussed earlier, the iceberg model is a systems thinking tool that is typically used for rooting out the causes for problems in an organization.

The iceberg has four parts: event, pattern, structures, and mental models.

Let’s explore each one.

 

Event

 

This is the tip of the iceberg. It’s what you can see on the surface. It’s what is happening here and now. If people are involved, it’s their current behavior.

Since we’ve established that you can use the iceberg model for troubleshooting problems, let’s take an example in that area.

Let’s say that you just released an update for your SaaS solution and you get user feedback saying that it’s riddled with bugs.

I know it can be tempting to just patch it and move on. But those bugs could just be the tip of the iceberg.

Sure, you need to debug your software as soon as you can. But you don’t stop there.

Does this problem happen frequently? If it does, the pattern for this problem could lead you to a much deeper root cause.

 

Pattern or Trend

 

This is the event that keeps on happening or even escalating.

Just to balance this out, not all events may belong to a pattern. Some are just isolated cases and may never come up again.

Still, it’s worth investigating if a particular problem has a bigger root cause.

And besides, all patterns start out with one seemingly isolated event.

In our example, imagine that the last several updates also had bugs that you needed to fix.

The same event has occurred more than once.
Now that’s a pattern. Time to find the factors that make it so.

 

Structures

 

This pertains to the practices that allow the pattern to develop. It has to do more with the systemic structures that exist in your workplace.

And the best way to find these structures is to identify the events present in the pattern you’re mapping out.

Let’s go back to our example with the bugs. You decide to investigate why the bugs on the new features make it to release. And you find out that the new features don’t go through proper testing and quality assurance before rolling it out.

Why? Well, you’ll need to dig deeper still.
Which leads us to the deepest part of the iceberg.

 

Mental Models

 

Now, this is the root of the problem. They are the mindsets, motives, and processes that shape the structures.

Going back to our example, you find out that the developers feel the need to forego testing because they are pressured to keep up with the deadlines.

Supervisors don’t make room for adjustments as they are more concerned about meeting deadlines rather than the quality of the product.

That’s the root cause of your bug problem. Now you can make the necessary changes that would make your development teams prioritize the quality of your product.

As a result, it would encourage them to make sure that it doesn’t have any bugs before submitting the updates.

Dealing with mental models is one of the best ways of solving problems within your organization. If you only deal with the event or structure without changing prevalent mindsets, those problems will inevitably return.

 

How To Track Email Marketing Analytics

 

Now, let’s talk about the practicals on how you can track your email marketing metrics and analytics.

There are two ways to track your email marketing analytics:

Each method has its own set of advantages and disadvantages.

Email marketing tools, like Campaign Monitor and Mailchimp, have analytics tools that will give you more detailed data about your email campaign performance. However, they can be expensive and some of them can be difficult to use.

Google Analytics, on the other hand, is a free tool that’s easy to use. However, it doesn’t give you as much data as a paid email marketing solution does.

Ultimately, the decision on how to track your email marketing analytics comes down to your needs and budget.

If you have the money and need detailed data, go for an email marketing solution. If you’re on a tight budget and you just need the basics, go for Google Analytics.

 

Email Analytics: Output Metrics

 

When it comes to SaaS email analytics, there are two types of metrics you need to know: output and outcome metrics.

Output metrics focus on how well you execute your email marketing strategy. These are the metrics that can affect your email sender’s reputation and email deliverability.

You see, email service providers (ESPs) and anti-spam networks monitor these output metrics to determine whether or not you are a trustworthy email sender.

Here are some email output metrics you need to track:

  • Bounce rate
  • Spam rate
  • Unsubscribe Rate

Let’s talk about them one by one.

 

Bounce Rate

 

Your bounce rate is the percentage of emails that were not delivered among the number of emails that you sent.

For example, if you sent an email to 100 people and 10 of them did not receive it, your bounce rate would be 10%.

Now, it is very important to keep an eye on your bounce rate.

ESPs and anti-spam networks generally see high bounce rates as an indicator that you’re not a trustworthy email sender.

So if your bounce rate is too high, you could get blacklisted, which would seriously damage your email delivery rates.

So how do emails get bounced in the first place?

There are two types of email bounces: soft bounces and hard bounces.

A soft bounce usually happens when an email server is temporarily down or when an inbox is full. These types of bounces are not a big deal because they don’t mean that the email address is invalid.

A hard bounce, on the other hand, happens when an email address is invalid or non-existent. This type of bounce should be addressed because it means that you’re wasting your time sending emails to people who will never see them.

Either way, having a bounced email means you’re sending to inactive or invalid email addresses, which could damage your reputation as an email sender.

Now, how do you reduce your email bounce rate? Here are a few tips:

  • Remove invalid email addresses from your list
  • Verify new email addresses before adding them to your list
  • Use a double opt-in to avoid typos
  • Monitor your email sender reputation

Bounce rate benchmark for SaaS businesses: 1.17%

 

Spam Rate

 

Your spam rate, or spam complaint rate, is the number of people who marked your email as spam divided by the total number of people who received it.

For example, if you sent an email to 100 people and 5 of them marked it as spam, your spam complaint rate would be 5%.

There are a lot of possible factors that can contribute to a high spam complaint rate.

Some of the most common ones are:

  • The aggressiveness of the email content
  • Use of spam trigger words
  • Email frequency and volume

To lower your spam complaint rate, you can make sure that you’re only sending emails to people who have opted in and that your content is relevant to them. You should also avoid using too many images and links in your emails.

Spam rate benchmark for SaaS businesses: 0.01%

 

Unsubscribe Rate

 

Your unsubscribe rate is the number of people who unsubscribed from your email list divided by the total number of people who received your email.

For example, if you sent an email to 100 people and 10 of them unsubscribed, your unsubscribe rate would be 10%.

A high unsubscribe rate could be a sign that your emails are not relevant to your audience or that they’re too frequent and have become annoying to your email subscribers.

There are a few factors that can affect your unsubscribe rate:

  • Email frequency
  • Email content relevance
  • Email length
  • The overall design of the email
  • Whether or not you’re using double opt-in

To lower your unsubscribe rate, you can try reducing the frequency of your emails or making your content more relevant to your audience. You may also want to experiment with different email designs.

Unsubscribe rate benchmark for SaaS businesses: 0.17%

 

Email Analytics: Outcome Metrics

 

Outcome metrics measure—well—the outcome or the effectiveness of your email marketing campaign.

They focus on the engagement of your email and how it impacts your business goals.

Below are some email outcome metrics that you need to track and analyze:

  • Open rate
  • Click-through rate (CTR)
  • Click-to-open-rate (CTOR)
  • Conversion rate

 

Open Rate

 

Your open rate is the number of people who open your email divided by the total number of people who received it.

For example, if you sent an email to 100 people and 20 people opened it, your open rate would be 20%.

There are a few factors that can affect your email open rate:

  • Subject line
  • Preview text
  • Sender name
  • Email relevance

You can improve your open rate by testing different subject lines and preview text. You can also try using a different sender name or changing the email content to make it more relevant to your audience.

Open rate benchmark for SaaS businesses: 17.96%

 

Click-Through Rate (CTR)

 

Your click-through rate is the number of people who click on links in your email divided by the total number of people who received it.

For example, if there are 100 people in your email list and 10 of them clicked on a link, your click-through rate would be 10%.

This is one of the most critical email marketing metrics out there because it tells you how effective your email content is.

Given that email recipients need to open your email before they can click a link in it, a high CTR usually indicates a good email open rate as well.

Additional factors that can affect your click-through rate include the following:

  • Email relevance
  • Call-to-action (CTA) buttons
  • Links in the email
  • The overall design of the email
  • Mobile-friendliness of your layout

One way to improve your click-through rate is by making your emails more relevant to your audience.

You may also want to optimize and test out different elements in your email content, such as the email body, layout, and CTAs.

CTR benchmark for SaaS businesses: 2.71%

 

Click-To-Open Rate (CTOR)

 

Now, don’t get this email marketing metric confused with the CTR.

Your click-to-open rate is the number of people who click on links in your email divided by the number of people who opened it.

Unlike CTR, your CTOR doesn’t consider the total number of email recipients. It only looks at the number of people who actually opened your email.

For example, if you have an email list of 100 people and 20 of them opened your email, but only 10 of them clicked on a link, your click-to-open rate would be 50%.

This metric is important because it tells you how effective your email content is at getting people to take action.

It pretty much has the same factors that affect your CTR. So, to improve your CTOR, you can make your email content more relevant and test different elements in your email design.

CTOR benchmark for SaaS businesses: 15.02%

 

Conversion Rate

 

Your conversion rate is the number of people who take a desired action divided by the total number of people who received your email.

For example, if you sent an email to 100 people and 10 of them signed up for a free trial, your conversion rate would be 10%.

“Conversion” can be any action, depending on the goal of your email marketing campaign.

If your goal is to get people to sign up for a free trial, then your conversion rate would be the number of people who signed up divided by the total number of email recipients.

Or if your goal is to get people to finally buy your SaaS product, then your conversion rate would be the number of people who bought it divided by the total number of email recipients.

There are a lot of factors that can affect your email conversion rate. A few of them include the following:

  • Email relevance
  • CTA buttons
  • Links in the email
  • The overall design of the email
  • Mobile-friendliness of your layout
  • Timing

You can improve your conversion rate by making sure that your email content is relevant to your audience and that your CTAs are effective.

You may also want to optimize different elements in your email content and design to see what works best for your audience.

 

What To Do About Email Marketing Analytics & Data

 

In any marketing strategy, whether it’s email marketing or something else, there is always room for improvement. That’s what email analytics and metrics are for.

But how do you really make data-driven decisions with this data?

The key to improving your email marketing campaign is AB testing.

AB testing is when you send two different versions of an email to a small group of people and see which one performs better.

Then, you can apply what you’ve learned from the AB test to your entire email list.

AB testing can be used for a lot of different elements and factors that affect your email marketing campaign’s performance, such as:

  • Subject line
  • Sender name
  • Preview text
  • Email content
  • Email length
  • Email layout
  • CTA button text, design, and placement
  • Personalization
  • Email design
  • Send time
  • Sending frequency

You should always be testing something in your email marketing campaign because there’s always room for improvement. And the only way to really know what works best is to test it out.

 

How To Analyze Email Marketing Data: Final Thoughts

 

When it comes to email marketing, data is key. You need to track the right email marketing metrics in order to see what’s working and what isn’t.

But more importantly, you need to be able to make data-driven decisions in order to improve your email marketing campaign.

That goes for all of your marketing strategies, not just email.

And the only way to really make data-driven decisions is to AB test different elements in your campaign. With it, you can find what works best for your audience and make the necessary changes to improve your conversion rate.

Looking for more guides that can help you take your SaaS business to the next level? Check out our blog here.

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Ken Moo
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