A Comprehensive List of Email Analytics Metrics

In this article, I will describe 13 important email analytics metrics, what they mean, and how email campaign performance can be improved.

In this article, I will describe different metrics related to evaluating performance of email campaigns and how they can be improved.

Here is a typical funnel of an email campaign – from mailing list to conversion:

Subscription ⇒ Email Send ⇒ Email Delivery ⇒ Email Open ⇒ Email Click Through ⇒ Landing Page Visit ⇒ Conversion Funnel from Email ⇒ Conversion from Email

Let us review a set of email metrics connected with each step of this funnel.

  1. Subscription conversion = subscriptions / visits of the sign-up page. In order to get more people to subscribe, your sign-up form should have a clear call-to-action and ask only for necessary information. Short info on data protection will establish trust and offers of incentives (e.g. a free sample, a whitepaper download, etc.) will motivate more users to share their email address.
  2. Subscriber list growth rate = (new subscribers-old subscribers) / old subscribers. In order to constantly increase your subscriber base, you should both receive sufficient amounts of traffic to your subscription page and have a high subscription conversion rate.
  3. Number of emails sent. This is the starting quantifying point of email campaign funnel analysis. The only way to improve this metric is to increase the size of the mailing list. However, to ensure that the email addresses are valid and to comply with double opt-in procedure, avoid buying email lists.
  4. Delivery rate = number of emails delivered / number of emails sent. Delivery of the emails you send depends on several factors: white- or blacklisting of your IP by email service providers, existing or non-existing (hard bounce) email addresses, how full the recipient’s mailbox is (soft bounce), if a user has moved previous emails to spam, etc. In order to increase the delivery rate, make sure to revise your mailing list often and to remove obsolete or false addresses. In addition, you should always include a clearly visible Unsubscribe link and avoid using HTML-only emails with images.
  5. Open rate = number of emails opened / number of emails sent. This metric is greatly influenced by the subject and the timing/frequency of the emails sent. In order for the email to appear relevant for the user, you can apply segmentation and some degree of personalization to your email campaigns. When comprising the subject of the email, be precise and avoid words and expressions which can cause your email be filtered as spam.
  6. Unsubscribe rate = number of unsubscribe requests / emails sent. Clearly, it is best to keep unsubscribe rate as low as possible. In order to do this, make sure to deliver the message relevant to the recipient. In addition, high mailing frequency (e.g. once per day) will likely cause most users to unsubscribe (see my next post). Ideally, you should let the subscriber choose the mailing frequency optimal for them.
  7. Click-through rate = clicks on the links with the email / emails sent. In order to measure how many times a link in the email was clicked you can apply a campaign ID to the  URL, e.g. https://marketing-to-convert?cid=email&campaign=spring-break&link-id=001. In order to increase the click-through rate, the email CTA should be clearly visible and correspond to the email subject. You may also want to place links in the body of the email and  behind corresponding images. As has been stated above, the offer should be delivered at the right time and to the right user. Thus, factors such as user past activity and interests will play a role.
  8. Unique open and click-through rate. These metrics are basically the same as above however, only one open and click-through is counted per visitor (even if they interacted with the email multiple times).
  9. Landing page visits. Normally, this number will be equal to click-throughs. In case it is not, do review link tagging and check if there are any broken links.
  10. Cost per visit = total cost of a mailing campaign / number of visits to the landing page. Using this metric, you can compare the effectiveness of different campaigns. (The cost of a campaign is the cost you incur for sending an email multiplied by the number of emails sent.) Improving cost per visit can be achieved by generating more visits from your mailing i.e. by offering relevant content and compelling CTA’s.
  11. Landing page bounce rate = bounces / visits to the landing page. In order to decrease bounces on the landing page, make sure that landing page reflects the information in the link user clicks on. E.g. if you are making an email campaign about a particular product, do not send users to Products Overview page.
  12. Pages per visit from email. This metric demonstrates if users found your site engaging enough to move on from the landing page. However, a large number of pages viewed may signify that your site is difficult to navigate. Make it clear to the user where to go next from the landing page by integrating links or offering a small navigation menu.
  13. Conversion from email = number of conversions / emails sent. Bear in mind that conversion is not always a sale. Contact form submission, leaving a review or recommending your product to a friend can be counted as conversion actions. In any case, conversion rate will be the most important measure of your email campaign success. Optimizing conversion rate involves all stages of the funnel: from segmenting the mailing list to streamlining the user journey from the landing page.

This list is by no means an exhausting one but contains some important metrics that can be used to track the performance of email marketing campaigns.

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Author: Elena

I acquired a BA degree in International Business with a specialization in Marketing from Nuremberg Technical School and a parallel degree from Leeds Metropolitan University. In 2013-2014, I worked in the field of performance and conversion optimization with an IT company and then was employed in content marketing. In 2016, I went back to working with Web Analytics and gained additional experience in project management. During this time, I received an Award of Achievement in Digital Analytics from the University of British Columbia (Canada). Currently, I am employed in Online Marketing. My areas of specialization include online marketing strategy, content creation, web analytics, conversion optimization and usability.

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