Email Performance Dashboard

This guide will help you understand:

This use case is part of Engagement’s Plug&Play initiative. Plug&Play offers impactful use cases like this one, which are ready out of the box and require minimum setup on your side. Learn how you can get Plug&Play use cases or contact your Customer Success Manager for more information.

What this use case does and why we developed it

Problem

With collected data scattered all over, locating potential issues and adjusting email campaign strategy is unattainable in real-time, hindering the performance of a set campaign. Afterwards, it is challenging for marketers to evaluate an email campaign without united data.

Solution

An effective way of overcoming this challenge is to store real-time collected email campaigns’ data in one place. This would help marketers optimize email campaigns using real-time insights and allow them to cross-compare campaigns instead of evaluating each campaign on its own.

This use case

To help marketers better understand and improve their email campaigns, we developed the Email Performance Dashboard use case, as a ready-to-use solution. The dashboard provides a collection of reports, including the standard email deliverability report, revenue reports, and ‘negative’ metrics reports. A unified data platform allows marketers to analyze the success of their campaigns in real-time.

What is included in this use case:

  • A custom prebuilt evaluation dashboard including all important emailing metrics

1. Setting up the use case

(1) Check the prerequisites

Prerequisites

The following event tracking is required:

  • 'purchase'
    • purchase_status: success
    • total_price
  • 'consent'
    • action=reject
    • category

Address any discrepancies if needed.

(2) Adjust the created assets and scenarios

1. Customizing the evaluated campaigns

Define which campaigns should be included in the evaluation reports and which ones should be excluded (e.g. test, template etc.) using the event segmentation:

  • Campaign target definition where you name ‘exclude’ all the segments that should not be part of the evaluation and ‘campaign target’ all the segments that should be part of the evaluation.

📘

Do not change the name of segments. Otherwise, new segments need to be chosen in the reports in this dashboard.

2. Customizing the attribution window and purchase definition

The Attribution window is by default 48h after the open/click for email communication. The attribution window is linked to the purchase event. If you need to adjust the attribution window and/or refine the definition of completed purchase (e.g. status ‘successful’), make the changes in this event segmentation:

  • Purchase target definition (event segmentation) - adjust the status and attribution window in hours.
    Conversions according to last click - comparison of emailing with other channels last 60 days - adjust the status of purchase event, no attribution window in hours applies here because we use ‘last click’ attribution.

📘

If the main purchase event is defined differently than ‘purchase’, the segmentation above needs to be created anew together with all of the following expressions:

  • The time between campaign o/c and purchase (hours)

This event segmentation is used within the following assets where it needs to be replaced with new event segmentation, and all purchase events need to be replaced by specific purchase events for the project (e.g. purchase_sap).

Reports

  • Campaign Group results (attribution 48 hours to opened/clicked emails) [last 30 days]
  • Campaign Results (attribution 48 hours to opened/clicked emails) [last 30 days]
  • Conversions according to last click - comparison of emailing with other channels [last 60 days]

3. Segmenting campaign events

Evaluation per campaign group is accessible within the Email Performance Dashboard. The report focuses on drilling down the revenue and emailing metrics by campaign groups that are defined by clients (e.g. newsletters, automated campaigns etc.). Therefore we need to arrange campaign events into categories:

  • Campaign groups to adjust the existing segments or create new ones based on the ‘campaign_name’ in your project.

📘

It is highly recommended to agree on campaign naming principles, e.g. all newsletter campaigns should contain ‘NL’ in the campaign_name, all automated campaigns should contain ‘AE’ in the ‘campaign_name’ etc.

4. Adjusting the time frames for different reports

Some reports would be restricted to a specific timeframe, e.g. ‘[last 90 days]’. If you wish to change the period, go to Edit mode of concerned reports and make the following changes:

  • Set the time filter on the top right corner to your desired value
  • Go to ‘Event Filter’ at the bottom of the report and adjust campaign - sent_timestamp - matches range to your desired value.
  • If the row consists of an aggregate, adjust the time frame of this aggregate to match the above, e.g. Campaign Group results (attribution 48 hours to opened/clicked emails) [last 30 days] report.

📘

Both filters should match the same time frame. The time frame used depends on the expiration of the campaign events in your project.

5. Defining the consent

Unsubscription metrics are defined by the ‘consent’ event with the action ‘reject’. Go to the following reports and select the correct consent ‘category’ for emailing communication:

  • Unsubscriptions [last 90 days] - select ‘category’ in the ‘Event Filter’ at the bottom of the report
  • Unsubscriptions by campaign [last 30 days] - select ‘category’ in the ‘Event Filter’ at the bottom of the report

(3) Evaluate on a regular basis

After successfully setting up all the necessary metrics within your project, the dashboard will serve as an out-of-box evaluating tool. The most important metrics are highlighted in colors, and their definitions are explained in the dashboard notes or this document. There are no further adjustments necessary. Check the evaluation dashboard regularly to spot any need for improvements as soon as possible.

To better understand the metrics and reports included in the dashboard or avoid misinterpretation of the data, please refer to the next section.

2. Suggestions for custom modifications

The Dashboard is ready for any more customization based on what you are tracking and what you deem important in any given moment.

3. Evaluating and interpreting the dashboard

The dictionary below is helpful for understanding metrics in the evaluation dashboard and their calculation. The most important metrics are marked in bold.

Key metrics calculations
The attribution model used for revenue attribution takes into consideration all the purchases made within:

  • 48h since email open or click
    This time frame is called the attribution window.

Benefit/Revenue calculations
Revenue - total value of all purchases made by customers impacted by the campaign (e.g. opened or clicked on the email) that occurred within the attribution window.

Purchases - all purchases made by customers impacted by the campaign (e.g. opened or clicked on the email.) that occurred within the attribution window.

Buyers - all customers impacted by the campaign (e.g. opened or clicked on the email) who made a purchase within the attribution window.

Conversion rate (CR) - Percentage of impressions that converted into a purchase within the attribution window

  • Conversion rate = count all purchases / count of all campaign impressions

Unique Conversion rate (UCR) - The proportion of customers who have seen the campaign and were converted into a purchase within the attribution window

  • Unique Conversion rate = count of all purchases / unique customers with impressions

Average Order Value (AOV) - Average revenue from one purchase/order

  • AOV = total revenue / total number of purchases

Revenue Per Recipient (RPR) - Average revenue per customer that has received the email campaign (tracked status ‘delivered’)

  • RPR = total revenue / all customers with campaign delivered

Revenue Per Buyer (RPB) - average revenue per customer that has at least 1 purchase within the attribution window

  • RPB = total revenue / all buyers

Campaign metrics
There are two types of metrics in the evaluation: non-unique and unique. The non-unique metrics count the number of events that have occurred, and the unique ones count the number of customers that have made the action. Example: one customer will open the email three times. Non unique open metrics = 3, unique open metric = 1.

Ecommerce Benchmark for emailing metrics
Unique Delivery rate - 99% and above
Unique Open rate - 20% and above
Unique Click rate from opened -15% and above

Ecommerce Benchmark for ‘negative’ emailing metrics
Unique Hard Bounce rate - less than 1%; on the long run, you should aim at less than 0.5%
Unique Soft Bounce rate - less than 2%
Unique Unsubscribe rate - less than 0.5%
Unique Complained ‘Spam’ rate - less than 0.1%
Unique Pre Blocked rate - less than 0.01%
Unique Clicked_honeypot rate - less than 1%

For more information, consult different campaign statuses and their meaning and our Emailing metrics guide.


Did this page help you?