[IMP] Email marketing: Analyze metrics reports
closes odoo/documentation#11448
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Signed-off-by: Zachary Straub (zst) <zst@odoo.com>
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@ -6,8 +6,11 @@ Analyze metrics
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In order to properly understand the success or failure of an email marketing campaign, it is
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necessary to monitor several key metrics. The insights gained from these metrics can then be used to
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optimize future campaigns. Odoo's *Email Marketing* application tracks several :ref:`key metrics
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<email-marketing/key-metrics>`, that can be interpreted to improve future campaigns.
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optimize future campaigns. Odoo's **Email Marketing** application tracks several :ref:`key metrics
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<email-marketing/view-metrics>`, that can be interpreted through :ref:`reports
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<email_marketing/create_reports>` to improve future campaigns.
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.. _email-marketing/view-metrics:
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View metrics
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============
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@ -17,84 +20,182 @@ locations.
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To access the metrics for an individual mailing, navigate to :menuselection:`Email Marketing app
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--> Mailings`. Locate the specific mailing in the list view, and use the column headings to view the
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results for that mailing. Click on one of the mailings in the list to open the record. At the top of
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the record, detailed metrics are displayed as smart buttons.
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results for that mailing. Click on one of the mailings in the list to open the record.
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At the top of the record, detailed metrics are displayed as smart buttons.
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.. image:: analyze_metrics/metric-smart-buttons.png
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:align: center
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:alt: The smart buttons on a mass mailing, displaying the results of the message.
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.. tip::
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Click on the smart buttons to see the recipient records for each metric.
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.. _email-marketing/key-metrics:
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Opened rate
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-----------
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The *Opened* rate measures the percentage of emails opened by recipients against the total number of
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sent emails.
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The percentage of emails opened by recipients, against the total number of sent emails.
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A high open rate may indicate that the subject line was timely, compelling, and successfully
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prompted the recipients to view the message.
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In cases where a reply is expected, such as cold outreach emails, high open rate may indicate the
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subject line was timely, compelling, and successfully prompted the recipients to view the message.
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A low open rate may indicate the subject line failed to capture the recipients' interest. It could
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also indicate the email ended up in a spam or junk folder due to having a poor sender reputation or
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failing to :doc:`configure the proper DNS records <../../general/email_communication/email_domain>`.
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In cases where a reply is not expected, such as promotional emails, it may indicate an issue with
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the email, such as incorrect product links or coupon codes.
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In cases where a reply is expected, a low open rate may indicate the subject
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line failed to capture the recipients' interest or the message ended up in a spam or junk folder. It
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could also indicate the email ended up in a spam or junk folder.
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.. note::
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Emails that consistently land in recipient spam folders could be due to having a poor sender
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reputation (i.e. high unsubscribe rate, high percentage of past emails marked as spam, etc.),
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or failing to :doc:`configure the proper DNS records
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<../../general/email_communication/email_domain>`.
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Replied rate
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------------
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The *Replied* rate measures the percentage of recipients who responded to the email directly against
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the total number of sent emails.
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The percentage of recipients who responded to the email, against the total number of sent emails.
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A high replied rate may indicate the email resonated with recipients, prompting them to take action
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or provide feedback.
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A high replied rate may indicate the email resonated with recipients, prompting them to take
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action or provide feedback.
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A low replied rate may suggest that the message lacked relevance or did not contain a clear call to
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action.
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A low replied rate may suggest the message lacked relevance or did not contain a clear
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call-to-action.
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Clicked rate
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------------
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The *Clicked* through rate (CTR), measures the percentage of recipients who clicked on a link within
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the email against the total number of sent emails.
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This represents the *Clicked through rate (CTR)*, which measures the
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percentage of recipients who clicked on a link within the email, against the total number of sent
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emails.
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A high |CTR| may indicate the email content was relevant and appropriately targeted. Recipients were
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motivated to click the links provided, and likely found the content engaging.
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A high |CTR| may indicate the email content was relevant and appropriately targeted. Recipients
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were motivated to click the links provided, and likely found the content engaging.
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A low |CTR| may indicate issues with either the targeting, or the content itself. Recipients may
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have been unmotivated by the calls to action, if there were any, or the message itself may have been
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directed toward the wrong audience.
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have been unmotivated by the calls-to-action, if there were any, or the message itself may have
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been directed toward the wrong audience.
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Received rate
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-------------
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The *Received* rate measures the percentage of emails that were successfully delivered against the
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total number of sent emails.
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This rate measures the percentage of emails that were **successfully** delivered, against the total
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number of sent emails.
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A high received rate can indicate that the mailing list used is up to date and the sender
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authentication is trusted by email providers.
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A high received rate can indicate the mailing list used is up-to-date, and the sender authentication
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is trusted by email providers.
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A low received rate may indicate issues either with the mailing list used for the mailing or with
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A low received rate may indicate issues, either with the mailing list used for the mailing, or with
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the sender authentication. View the :ref:`email-marketing/deliverability-issues` section for more
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information.
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Bounced rate
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------------
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The *Bounced* rate measures the percentage of emails that were unsuccessfully delivered, against the
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total number of sent emails.
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This rate measures the percentage of emails that were **unsuccessfully** delivered, and did not
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enter a recipient's inbox, against the total number of sent emails.
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A high bounce rate could indicate issues either with the mailing list used for the mailing or with
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A high bounce rate could indicate issues, either with the mailing list used for the mailing, or with
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the sender authentication.
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A low bounce rate may indicate that the mailing list used is up to date and the sender
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A low bounce rate may indicate that the mailing list used is up-to-date, and the sender
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authentication is trusted by email providers. View the :ref:`email-marketing/deliverability-issues`
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section for more information.
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.. tip::
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Click on the respective smart buttons to see all the corresponding recipient records that are
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attributed to each metric. When these filtered records are in view, multiple types of reports can
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be run for further analysis.
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.. _email_marketing/create_reports:
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Create metrics reports
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======================
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Individual metrics can be analyzed by creating a report. To begin, click on the smart button of the
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desired metric.
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Next, click the :icon:`fa-caret-down` :guilabel:`(down arrow)` to the right of the search bar to see
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a drop-down menu of filtering and grouping parameters.
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:guilabel:`Filters`, located in the left column of the search options, can be used to keep only the
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results that fit the filter. For example, selecting the *Bounced* filter only shows emails
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that could not be delivered.
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:guilabel:`Group By`, found in the middle column, is used to organize the results into groups, and
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can be used with or without filters.
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.. note::
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Setting multiple :guilabel:`Group By` options creates nested groups, according to which option
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is selected first. For example, selecting :guilabel:`Sent Period`, followed by
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:guilabel:`Add Custom Group --> Responsible`, in the :guilabel:`Group By` column, sorts all
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results *first* by the sent period, *then* by the team member responsible. This is a useful
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metric for analyzing who on the team is sending in volume or quantity over a set time period.
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This can be verified by looking at the direction, and order, of the selections in the group tile
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that appears in the search bar after the selections are made.
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.. example::
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A monthly newsletter has been sent out, and 6.9% of the sent emails were bounced.
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.. image:: analyze_metrics/newsletter-metrics.png
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:align: center
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:alt: The metrics smart buttons of the newsletter.
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To see what these bounced recipients have in common, the records are grouped using a custom group
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targeting :guilabel:`Mailing Lists`, which groups all records by the mailing lists they are on.
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The records are then filtered using a custom filter with the rule `Created on >= 07/01/2024
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00:00:00`, to filter by when the mailing list was last checked. This filter only includes
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recipients that have been created on, or after, July 1st, 2024, in the report.
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.. image:: analyze_metrics/metrics-filter.png
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:align: center
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:alt: The custom filter creation form.
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Using these configurations, it is evident that all the recipients with bounced emails were added
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after the list was last checked. Looking closer at the domains, it is evident that each
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recipient has a malformed email domain (i.e: @yaoo.com instead of @yahoo.com), likely due to a
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manual entry error while updating the database.
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.. image:: analyze_metrics/malformed-addresses.png
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:align: center
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:alt: A list of bounced email addresses with malformed email domains.
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.. seealso::
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View :doc:`../../essentials/search` for more information about making custom groups and
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filters.
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.. _email-marketing/deliverability-issues:
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Mass mailing analysis
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=====================
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It is also possible to analyze the success between mailing campaigns by creating a *Mass Mailing
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Analysis* report. To begin, navigate to :menuselection:`Email Marketing app --> Reporting --> Mass
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Mailing Analysis`.
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A dashboard appears displaying a bar chart containing each mailing campaign. By default,
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:guilabel:`Sent` is selected, displaying the number of sent records on the y-axis. To change the
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measure, click the :guilabel:`Measures` button, and select the desired measure from the drop-down
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menu.
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.. example::
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The following chart displays the number of opened emails from two different mass mailings.
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In this view, it can be seen that the first mass mailing led to a higher opened rate than the
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second. Because a lower opened rate can sometimes be attributed to a subject line that failed to
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capture readers' attention, the subject line of each mass mailing can be a good place to begin
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looking.
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.. image:: analyze_metrics/mma-opened.png
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:align: center
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:alt: A bar chart displaying the different opened rate between two mass mailing campaigns.
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Comparing the two subject lines, it is clear the newsletter's subject line was less engaging,
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which may have led to the lower opened rate, when compared to the other mass mailing.
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.. image:: analyze_metrics/mailing-comparison.png
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:align: center
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:alt: alt text
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Deliverability issues
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=====================
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