Case1. Low click rate (Increase click rate)

There are several reasons for the low click-rate which can be identified by this tool:

1. Email is long. It can be uncovered by the next metrics:

• % of scrolled > 50% metric is low
• module with CTA has low scrolled % or read %

2. The whole email content is not interesting for the user:

• the median number of scrolled or read modules is a low
• % of scrolled> 50% is high, but % of read >50% is low.

3. The interesting part of an email is hard to be reached.
Calculate the next ratio for each module: module clicks (provided by ESP)/ read numbers. Find modules with the best ratio. If scrolled % for these the most engaged modules is low it means that the interesting part of an email is hard to be reached.

4. Part of the content is boring or makes a user close an email.
A particular module has a high read %, but the next modules have a dramatically low read %. Also, you can check it with recordings.

5. Content in email is enough for users, no need for clicks
% of read >50% is high and the average duration of a session is high

Case2. Low conversion rate, while click rate is not bad

The reason for such a case may be the fact that an important message was not read.
To check this hypothesis you may check the read % for important modules in the module metrics report.

Case3. Open rate is becoming lower (Low open rate)

The reason for this issue may be the fact that the engagement level is decreasing: the problem is not in the subject line, but in the content of previous emails.
To check this hypothesis you may check the dynamics of % of scrolled > 50% or % of read> 50% for the last emails.

Case 4. Launch of a new type of email

During the preparation of the new type of email, it is good to test different options and see how people react to these emails (recordings, scrolling, reading behavior, etc.).

For example, when you launch an automated welcome email you may check whether an email should contain one message or several messages. Make a/b test and compare % of scrolled > 50% and % of read > 50% metrics for both options.

Case 5. Identification of high and low converting content in email

The tool helps to uncover which parts of emails were interesting for users and which not so much. One of the ways is to calculate the next ratio for each module: module clicks (provided by ESP)/ read numbers. Find modules with the best and worst ratios.

For example, you may identify the most interesting articles in the newsletter and use this information for future content preparation.

Case 6. Understanding how to place content in email, which order should be, how long it should be

Track and optimize % of scrolled > 50% and % of read > 50% metrics by changing the length of the email. Choose the best content and put it at the top of the email, use module metrics for it. One of the ways is to calculate the next ratio for each module: module clicks (provided by ESP)/ read numbers. Find modules with the best and worst ratios.

Case 7. Identification of the overall engagement level

In 2021 the main goal of email marketers is to make email they will highly engage with. But currently, marketers mostly track open and click rates, which don't show the level of engagement with email content. Our metrics help to track such engagement on a constant basis. Check all available engagement metrics here.