diff --git a/content/applications/marketing/email_marketing/analyze_metrics.rst b/content/applications/marketing/email_marketing/analyze_metrics.rst index ae71a995ca..c3e5f2a4b9 100644 --- a/content/applications/marketing/email_marketing/analyze_metrics.rst +++ b/content/applications/marketing/email_marketing/analyze_metrics.rst @@ -6,8 +6,11 @@ Analyze metrics In order to properly understand the success or failure of an email marketing campaign, it is necessary to monitor several key metrics. The insights gained from these metrics can then be used to -optimize future campaigns. Odoo's *Email Marketing* application tracks several :ref:`key metrics -`, that can be interpreted to improve future campaigns. +optimize future campaigns. Odoo's **Email Marketing** application tracks several :ref:`key metrics +`, that can be interpreted through :ref:`reports +` to improve future campaigns. + +.. _email-marketing/view-metrics: View metrics ============ @@ -17,84 +20,182 @@ locations. To access the metrics for an individual mailing, navigate to :menuselection:`Email Marketing app --> Mailings`. Locate the specific mailing in the list view, and use the column headings to view the -results for that mailing. Click on one of the mailings in the list to open the record. At the top of -the record, detailed metrics are displayed as smart buttons. +results for that mailing. Click on one of the mailings in the list to open the record. + +At the top of the record, detailed metrics are displayed as smart buttons. .. image:: analyze_metrics/metric-smart-buttons.png :align: center :alt: The smart buttons on a mass mailing, displaying the results of the message. -.. tip:: - Click on the smart buttons to see the recipient records for each metric. - -.. _email-marketing/key-metrics: - Opened rate ----------- -The *Opened* rate measures the percentage of emails opened by recipients against the total number of -sent emails. +The percentage of emails opened by recipients, against the total number of sent emails. -A high open rate may indicate that the subject line was timely, compelling, and successfully -prompted the recipients to view the message. +In cases where a reply is expected, such as cold outreach emails, high open rate may indicate the +subject line was timely, compelling, and successfully prompted the recipients to view the message. -A low open rate may indicate the subject line failed to capture the recipients' interest. It could -also indicate the email ended up in a spam or junk folder due to having a poor sender reputation or -failing to :doc:`configure the proper DNS records <../../general/email_communication/email_domain>`. +In cases where a reply is not expected, such as promotional emails, it may indicate an issue with +the email, such as incorrect product links or coupon codes. + +In cases where a reply is expected, a low open rate may indicate the subject +line failed to capture the recipients' interest or the message ended up in a spam or junk folder. It +could also indicate the email ended up in a spam or junk folder. + +.. note:: + Emails that consistently land in recipient spam folders could be due to having a poor sender + reputation (i.e. high unsubscribe rate, high percentage of past emails marked as spam, etc.), + or failing to :doc:`configure the proper DNS records + <../../general/email_communication/email_domain>`. Replied rate ------------ -The *Replied* rate measures the percentage of recipients who responded to the email directly against -the total number of sent emails. +The percentage of recipients who responded to the email, against the total number of sent emails. -A high replied rate may indicate the email resonated with recipients, prompting them to take action -or provide feedback. +A high replied rate may indicate the email resonated with recipients, prompting them to take +action or provide feedback. -A low replied rate may suggest that the message lacked relevance or did not contain a clear call to -action. +A low replied rate may suggest the message lacked relevance or did not contain a clear +call-to-action. Clicked rate ------------ -The *Clicked* through rate (CTR), measures the percentage of recipients who clicked on a link within -the email against the total number of sent emails. +This represents the *Clicked through rate (CTR)*, which measures the +percentage of recipients who clicked on a link within the email, against the total number of sent +emails. -A high |CTR| may indicate the email content was relevant and appropriately targeted. Recipients were -motivated to click the links provided, and likely found the content engaging. +A high |CTR| may indicate the email content was relevant and appropriately targeted. Recipients +were motivated to click the links provided, and likely found the content engaging. A low |CTR| may indicate issues with either the targeting, or the content itself. Recipients may -have been unmotivated by the calls to action, if there were any, or the message itself may have been -directed toward the wrong audience. +have been unmotivated by the calls-to-action, if there were any, or the message itself may have +been directed toward the wrong audience. Received rate ------------- -The *Received* rate measures the percentage of emails that were successfully delivered against the -total number of sent emails. +This rate measures the percentage of emails that were **successfully** delivered, against the total +number of sent emails. -A high received rate can indicate that the mailing list used is up to date and the sender -authentication is trusted by email providers. +A high received rate can indicate the mailing list used is up-to-date, and the sender authentication +is trusted by email providers. -A low received rate may indicate issues either with the mailing list used for the mailing or with +A low received rate may indicate issues, either with the mailing list used for the mailing, or with the sender authentication. View the :ref:`email-marketing/deliverability-issues` section for more information. Bounced rate ------------ -The *Bounced* rate measures the percentage of emails that were unsuccessfully delivered, against the -total number of sent emails. +This rate measures the percentage of emails that were **unsuccessfully** delivered, and did not +enter a recipient's inbox, against the total number of sent emails. -A high bounce rate could indicate issues either with the mailing list used for the mailing or with +A high bounce rate could indicate issues, either with the mailing list used for the mailing, or with the sender authentication. -A low bounce rate may indicate that the mailing list used is up to date and the sender +A low bounce rate may indicate that the mailing list used is up-to-date, and the sender authentication is trusted by email providers. View the :ref:`email-marketing/deliverability-issues` section for more information. +.. tip:: + Click on the respective smart buttons to see all the corresponding recipient records that are + attributed to each metric. When these filtered records are in view, multiple types of reports can + be run for further analysis. + +.. _email_marketing/create_reports: + +Create metrics reports +====================== + +Individual metrics can be analyzed by creating a report. To begin, click on the smart button of the +desired metric. + +Next, click the :icon:`fa-caret-down` :guilabel:`(down arrow)` to the right of the search bar to see +a drop-down menu of filtering and grouping parameters. + +:guilabel:`Filters`, located in the left column of the search options, can be used to keep only the +results that fit the filter. For example, selecting the *Bounced* filter only shows emails +that could not be delivered. + +:guilabel:`Group By`, found in the middle column, is used to organize the results into groups, and +can be used with or without filters. + +.. note:: + Setting multiple :guilabel:`Group By` options creates nested groups, according to which option + is selected first. For example, selecting :guilabel:`Sent Period`, followed by + :guilabel:`Add Custom Group --> Responsible`, in the :guilabel:`Group By` column, sorts all + results *first* by the sent period, *then* by the team member responsible. This is a useful + metric for analyzing who on the team is sending in volume or quantity over a set time period. + + This can be verified by looking at the direction, and order, of the selections in the group tile + that appears in the search bar after the selections are made. + +.. example:: + A monthly newsletter has been sent out, and 6.9% of the sent emails were bounced. + + .. image:: analyze_metrics/newsletter-metrics.png + :align: center + :alt: The metrics smart buttons of the newsletter. + + To see what these bounced recipients have in common, the records are grouped using a custom group + targeting :guilabel:`Mailing Lists`, which groups all records by the mailing lists they are on. + The records are then filtered using a custom filter with the rule `Created on >= 07/01/2024 + 00:00:00`, to filter by when the mailing list was last checked. This filter only includes + recipients that have been created on, or after, July 1st, 2024, in the report. + + .. image:: analyze_metrics/metrics-filter.png + :align: center + :alt: The custom filter creation form. + + Using these configurations, it is evident that all the recipients with bounced emails were added + after the list was last checked. Looking closer at the domains, it is evident that each + recipient has a malformed email domain (i.e: @yaoo.com instead of @yahoo.com), likely due to a + manual entry error while updating the database. + + .. image:: analyze_metrics/malformed-addresses.png + :align: center + :alt: A list of bounced email addresses with malformed email domains. + +.. seealso:: + View :doc:`../../essentials/search` for more information about making custom groups and + filters. + .. _email-marketing/deliverability-issues: +Mass mailing analysis +===================== + +It is also possible to analyze the success between mailing campaigns by creating a *Mass Mailing +Analysis* report. To begin, navigate to :menuselection:`Email Marketing app --> Reporting --> Mass +Mailing Analysis`. + +A dashboard appears displaying a bar chart containing each mailing campaign. By default, +:guilabel:`Sent` is selected, displaying the number of sent records on the y-axis. To change the +measure, click the :guilabel:`Measures` button, and select the desired measure from the drop-down +menu. + +.. example:: + The following chart displays the number of opened emails from two different mass mailings. + + In this view, it can be seen that the first mass mailing led to a higher opened rate than the + second. Because a lower opened rate can sometimes be attributed to a subject line that failed to + capture readers' attention, the subject line of each mass mailing can be a good place to begin + looking. + + .. image:: analyze_metrics/mma-opened.png + :align: center + :alt: A bar chart displaying the different opened rate between two mass mailing campaigns. + + Comparing the two subject lines, it is clear the newsletter's subject line was less engaging, + which may have led to the lower opened rate, when compared to the other mass mailing. + + .. image:: analyze_metrics/mailing-comparison.png + :align: center + :alt: alt text + Deliverability issues ===================== diff --git a/content/applications/marketing/email_marketing/analyze_metrics/mailing-comparison.png b/content/applications/marketing/email_marketing/analyze_metrics/mailing-comparison.png new file mode 100644 index 0000000000..c7dea7276f Binary files /dev/null and b/content/applications/marketing/email_marketing/analyze_metrics/mailing-comparison.png differ diff --git a/content/applications/marketing/email_marketing/analyze_metrics/malformed-addresses.png b/content/applications/marketing/email_marketing/analyze_metrics/malformed-addresses.png new file mode 100644 index 0000000000..ea574159d0 Binary files /dev/null and b/content/applications/marketing/email_marketing/analyze_metrics/malformed-addresses.png differ diff --git a/content/applications/marketing/email_marketing/analyze_metrics/metrics-filter.png b/content/applications/marketing/email_marketing/analyze_metrics/metrics-filter.png new file mode 100644 index 0000000000..06b7118149 Binary files /dev/null and b/content/applications/marketing/email_marketing/analyze_metrics/metrics-filter.png differ diff --git a/content/applications/marketing/email_marketing/analyze_metrics/mma-opened.png b/content/applications/marketing/email_marketing/analyze_metrics/mma-opened.png new file mode 100644 index 0000000000..41c0c0791c Binary files /dev/null and b/content/applications/marketing/email_marketing/analyze_metrics/mma-opened.png differ diff --git a/content/applications/marketing/email_marketing/analyze_metrics/newsletter-metrics.png b/content/applications/marketing/email_marketing/analyze_metrics/newsletter-metrics.png new file mode 100644 index 0000000000..27fce48965 Binary files /dev/null and b/content/applications/marketing/email_marketing/analyze_metrics/newsletter-metrics.png differ