How to measure email campaign performance with KPIs
By Article Monster
December 24, 2025
29 min read
How to Measure Email Campaign Performance: Beyond the Basics
Measuring the performance of your email campaigns is crucial for optimizing your strategy and maximizing ROI. While open and click-through rates provide a basic understanding, a deeper analysis is needed to truly understand what resonates with your audience and drives conversions. This article will delve into advanced metrics and techniques, empowering you to gain actionable insights and refine your email marketing efforts for superior results.
Beyond simply sending emails, ensuring they reach the intended inbox is paramount. Delivery and reputation metrics offer insight into the health of your sending infrastructure and the trust your audience (and ISPs) place in your communications. Monitoring these metrics allows you to proactively identify and address issues that might prevent your emails from reaching your subscribers.
Bounce Rate Analysis
Bounce rate represents the percentage of emails that failed to deliver. A high bounce rate indicates problems with your email list or sending infrastructure. There are two types of bounces: hard bounces and soft bounces.
Hard Bounces: Indicate permanent delivery failures, such as invalid email addresses or closed accounts. These should be removed immediately from your list.
Soft Bounces: Indicate temporary delivery issues, such as a full inbox or a server problem. These may resolve themselves, but persistent soft bounces should also be removed after several attempts.
Example 1: Identifying High Bounce Rates
Suppose your email marketing platform (e.g., Mailchimp, SendGrid, Amazon SES) reports a bounce rate of 5% for a recent campaign. This is generally considered high. To investigate, you can typically export the list of bounced emails and categorize them by bounce type (hard or soft) and the reason for the bounce.
Example Output (CSV Extract):
Email Address,Bounce Type,Reason
invalid@example.com,Hard Bounce,Invalid email address
fullinbox@example.com,Soft Bounce,Mailbox full
servererror@example.com,Soft Bounce,Temporary server error
Analyzing this data allows you to identify patterns. For instance, a large number of hard bounces from a specific domain might indicate a data entry error or a problem with that domain’s email server.
Example 2: Using SendGrid’s Event Webhook to Monitor Bounces
SendGrid provides a powerful Event Webhook that allows you to receive real-time notifications about email events, including bounces. You can configure this webhook to send data to your own server, where you can process and analyze it.
First, configure the Event Webhook in your SendGrid account to send bounce events to your server’s endpoint (e.g., `https://yourdomain.com/sendgrid-events`). Then, create a script on your server to handle the incoming data.
# Python (Flask example)
from flask import Flask, request, jsonify
import json
app = Flask(__name__)
@app.route('/sendgrid-events', methods=['POST'])
def sendgrid_events():
data = request.get_json()
for event in data:
if event['event'] == 'bounce':
email = event['email']
reason = event['reason']
# Log the bounce event to a database or file
print(f"Bounce: Email: {email}, Reason: {reason}")
return jsonify(success=True), 200
if __name__ == '__main__':
app.run(debug=True)
This script receives the JSON payload from SendGrid, parses the events, and logs bounce events, including the email address and the reason for the bounce. You can then use this data to automatically remove bounced emails from your list and track bounce trends over time.
Spam Complaint Rate
The spam complaint rate represents the percentage of recipients who mark your emails as spam. A high spam complaint rate is a serious issue that can severely damage your sender reputation and lead to deliverability problems. ISPs actively monitor spam complaint rates and use them to filter incoming emails.
Most email marketing platforms provide data on spam complaints. Aim for a spam complaint rate below 0.1%. Exceeding this threshold can trigger deliverability issues.
Example 1: Monitoring Spam Complaints in Mailchimp
In Mailchimp, navigate to the “Reports” section for a specific campaign. Look for the “Abuse Complaints” metric. This indicates the number of recipients who marked your email as spam. Divide this number by the total number of emails delivered to calculate the spam complaint rate.
Spam Complaint Rate = (Number of Abuse Complaints / Number of Emails Delivered) * 100
If the rate is above 0.1%, investigate potential causes such as:
Failing to provide a clear and easy unsubscribe link.
Sending unsolicited emails (i.e., not obtaining proper consent).
Example 2: Using Feedback Loops (FBLs) to Manage Spam Complaints
Feedback Loops (FBLs) are a mechanism provided by ISPs that allow you to receive reports about users who mark your emails as spam. By registering with FBLs, you can proactively identify and remove these users from your list, preventing future spam complaints.
The process typically involves:
Registering with each ISP’s FBL program (e.g., Gmail, Yahoo, Microsoft).
Adding a special header to your emails that identifies the campaign or sender.
Receiving reports from the ISP containing the email addresses of users who marked your emails as spam.
Automatically removing these users from your mailing list.
The specific implementation varies depending on the ISP. For example, Gmail’s FBL requires you to embed an authentication key in your email headers. You then receive reports containing the Message-ID of the emails that were marked as spam. You can then extract the email address from your logs using the Message-ID.
Here’s a simplified example of adding the required header using PHP:
Sender reputation is a score assigned to your sending IP address or domain by ISPs, reflecting their assessment of your email practices. A good sender reputation is essential for ensuring high deliverability. Factors that influence sender reputation include:
Email volume and consistency.
Bounce rate and spam complaint rate.
Authentication practices (SPF, DKIM, DMARC).
Engagement metrics (opens, clicks).
Blacklist status.
You can monitor your sender reputation using various tools, such as:
Sender Score: A service provided by Validity that assigns a score from 0 to 100, with higher scores indicating a better reputation.
Google Postmaster Tools: Provides insights into your sender reputation for Gmail users, including spam rate, feedback loop data, and authentication status.
ReputationAuthority: Offers comprehensive sender reputation monitoring and alerting.
Example 1: Checking Sender Score
Visit the Sender Score website (senderscore.org) and enter your sending IP address or domain name. The site will provide a score along with details about your reputation, such as your email volume, spam complaints, and other relevant factors.
A score above 80 is generally considered good. If your score is lower, you need to investigate and address the underlying issues, such as high bounce rates or spam complaints.
Example 2: Configuring SPF, DKIM, and DMARC
Implementing SPF, DKIM, and DMARC is crucial for authenticating your emails and improving your sender reputation. These protocols help ISPs verify that your emails are legitimate and not spoofed.
SPF (Sender Policy Framework): Specifies which mail servers are authorized to send emails on behalf of your domain. You create an SPF record in your DNS settings that lists these authorized servers.
DKIM (DomainKeys Identified Mail): Adds a digital signature to your emails, allowing recipients to verify that the email was indeed sent by your domain and has not been tampered with. You generate a DKIM key pair and add the public key to your DNS records.
DMARC (Domain-based Message Authentication, Reporting & Conformance): Builds upon SPF and DKIM by specifying how recipients should handle emails that fail SPF or DKIM checks. You can instruct recipients to reject, quarantine, or accept these emails. DMARC also provides reporting mechanisms to help you monitor your email authentication status.
To configure SPF, add a TXT record to your DNS zone with the following format:
v=spf1 include:sendgrid.net ~all
This example authorizes SendGrid to send emails on behalf of your domain. Replace `sendgrid.net` with the appropriate domain for your email service provider. The `~all` mechanism indicates a soft fail, meaning that emails from other servers will be accepted but marked as suspicious. A `-all` mechanism would indicate a hard fail, meaning that emails from unauthorized servers should be rejected.
To configure DKIM, generate a DKIM key pair in your email service provider’s settings. Then, add the public key to your DNS records. The exact steps vary depending on your provider.
To configure DMARC, add a TXT record to your DNS zone with the following format:
_dmarc.yourdomain.com. IN TXT "v=DMARC1; p=none; rua=mailto:dmarc-reports@yourdomain.com; ruf=mailto:dmarc-reports@yourdomain.com; adkim=r; aspf=r;"
This example sets the policy to “none,” meaning that no action will be taken on emails that fail SPF or DKIM checks. The `rua` and `ruf` tags specify email addresses where aggregate and forensic reports should be sent. The `adkim` and `aspf` tags specify relaxed alignment for DKIM and SPF, respectively. You should start with a policy of “none” and gradually increase the strictness to “quarantine” or “reject” as you gain confidence in your email authentication setup. Be sure to replace `dmarc-reports@yourdomain.com` with a valid email address for receiving DMARC reports.
“Email deliverability is the foundation of any successful email marketing program. Without a strong sender reputation and proper authentication, your messages are unlikely to reach the intended inbox, regardless of how engaging your content is.”
John Smith, Email Marketing Consultant
Engagement and Conversion Metrics
While delivery ensures your email reaches the inbox, engagement metrics reveal how your audience interacts with your message. These metrics provide crucial insights into the effectiveness of your content, subject lines, and calls to action. Understanding engagement helps you refine your messaging and optimize your campaigns for better results. Furthermore, conversion metrics bridge the gap between engagement and business outcomes, demonstrating the direct impact of your email marketing efforts on your bottom line.
Click-Through Rate (CTR) Analysis
CTR measures the percentage of recipients who clicked on a link within your email. It’s a key indicator of how engaging and relevant your content is to your audience. A higher CTR suggests that your subject line, email body, and calls to action are effectively capturing attention and driving action.
Example 1: Tracking CTR by Link
Most email marketing platforms track CTR on a per-link basis. This allows you to identify which links are performing well and which ones are not. For example, you might have multiple calls to action in your email, such as “Learn More,” “Shop Now,” and “Download Free Ebook.” By tracking the CTR for each link, you can determine which call to action resonates most with your audience.
Suppose your email marketing platform reports the following CTRs for each link:
Link
CTR
Learn More
5%
Shop Now
10%
Download Free Ebook
15%
This data suggests that the “Download Free Ebook” call to action is the most effective. You might consider placing this call to action more prominently in future emails or testing different variations of the “Learn More” and “Shop Now” calls to action to improve their performance.
Example 2: Using UTM Parameters for Detailed CTR Analysis
UTM (Urchin Tracking Module) parameters are tags that you add to your URLs to track the source, medium, and campaign that drove traffic to your website. By using UTM parameters in your email links, you can gain a more detailed understanding of which emails and links are driving conversions.
The standard UTM parameters are:
utm_source: Identifies the source of the traffic (e.g., newsletter).
utm_medium: Identifies the marketing medium (e.g., email).
utm_campaign: Identifies the specific campaign (e.g., summer_sale).
utm_term: Identifies the paid keywords (used for paid campaigns).
utm_content: Differentiates ads or links that point to the same URL.
For example, you might add the following UTM parameters to a link in your email:
Then, you can use Google Analytics or other web analytics tools to track the performance of this link and see how many visitors, leads, and customers it generated.
Conversion Rate Tracking
Conversion rate measures the percentage of recipients who completed a desired action after clicking on a link in your email, such as making a purchase, filling out a form, or subscribing to a service. Conversion rate is the ultimate measure of your email campaign’s effectiveness.
Example 1: Tracking Conversions with Google Analytics Goals
Google Analytics Goals allow you to define specific actions that you want to track on your website, such as form submissions or purchases. You can then use UTM parameters in your email links to track which emails are driving these conversions.
To set up a goal in Google Analytics:
Go to the “Admin” section of Google Analytics.
Select “Goals” in the “View” column.
Click “+ New Goal.”
Choose a goal template or create a custom goal.
Define the goal details, such as the destination URL or event that triggers the goal.
For example, you might create a goal that tracks when users reach the “Thank You” page after submitting a form. Then, you can use UTM parameters in your email links to track which emails are driving form submissions.
Example 2: Integrating Email Marketing Platform with CRM
Integrating your email marketing platform (e.g., Mailchimp, SendGrid) with your CRM (Customer Relationship Management) system (e.g., Salesforce, HubSpot) allows you to track conversions and attribute them directly to your email campaigns.
When a recipient clicks on a link in your email, their activity can be tracked in your CRM. If they then complete a desired action, such as making a purchase, the conversion can be attributed to the email campaign that drove the click.
The specific integration process varies depending on the platforms you are using. However, it typically involves:
Configuring the integration between your email marketing platform and your CRM.
Mapping data fields between the two systems.
Tracking clicks and conversions in your CRM.
For example, you might use the HubSpot integration with Mailchimp to track when recipients click on links in your Mailchimp emails and then convert into leads or customers in HubSpot. This allows you to see which email campaigns are most effective at driving business results.
Time Spent Viewing Emails
While not always directly available as a standard metric, “time spent viewing emails” provides valuable insight into how engaged recipients are with your content. A longer viewing time suggests that the content is relevant and captivating.
Example 1: Using Pixel Tracking to Estimate Viewing Time
While directly measuring “time spent viewing” is challenging, you can use pixel tracking to estimate it. A tracking pixel is a tiny, transparent image (typically 1×1 pixel) embedded in your email. When the email is opened and the images are loaded, the pixel is downloaded from your server, allowing you to track the open event.
You can use multiple tracking pixels placed strategically throughout the email. The time elapsed between the loading of the first pixel and the last pixel provides an approximation of the viewing time.
To implement pixel tracking, you need to:
Create a tracking pixel image (e.g., `tracking.gif`).
Embed the image in your email using an `` tag.
Add unique identifiers to the image URL to track which email and recipient triggered the pixel.
Log the pixel requests on your server, including the timestamp, email ID, and recipient ID.
Analyze the logs to calculate the time elapsed between pixel loads.
Here’s an example of embedding a tracking pixel in your email:
Then, on your server, you would log the requests for `tracking.gif` and analyze the timestamps to estimate the viewing time. This method provides a rough estimate, as users may disable image loading or close the email before all pixels are loaded.
Example 2: Analyzing Scroll Depth (Indirectly)
While not a direct measure of viewing time, analyzing scroll depth on your website after a user clicks through from an email can indirectly indicate engagement. If users scroll further down the page after clicking from an email, it suggests they are more interested in the content.
You can use Google Analytics scroll tracking to measure how far down the page users scroll. This involves adding JavaScript code to your website that tracks scroll events and sends data to Google Analytics.
Here’s an example of using Google Tag Manager to implement scroll tracking:
Create a new tag in Google Tag Manager.
Choose “Custom Event” as the tag type.
Set the event name to “scrollDepth.”
Add a trigger that fires when the user scrolls to a certain percentage of the page (e.g., 25%, 50%, 75%, 100%).
Configure the tag to send data to Google Analytics, including the scroll depth and the UTM parameters from the email link.
Then, in Google Analytics, you can analyze the “scrollDepth” event and see how it correlates with the UTM parameters from your email campaigns. This can give you insights into which emails are driving more engaged traffic to your website.
Segment-Specific Performance Analysis
Treating your entire email list as a homogenous group can lead to suboptimal results. Different segments within your audience have unique preferences, behaviors, and needs. Analyzing campaign performance at the segment level provides valuable insights into what resonates with each group, allowing you to tailor your messaging for maximum impact.
Demographic Segmentation Analysis
Demographic segmentation involves dividing your audience based on characteristics such as age, gender, location, income, and education level. Analyzing campaign performance by demographic segment can reveal valuable insights into how different groups respond to your messaging.
Example 1: Analyzing Open and Click Rates by Location
Suppose you’re running a promotion for a local event. You can segment your email list by geographic location and track the open and click rates for each segment. This will help you determine which geographic areas are most interested in the event.
Location
Open Rate
CTR
New York City
25%
5%
Los Angeles
20%
3%
Chicago
30%
7%
This data suggests that the campaign is performing best in Chicago. You might consider focusing your marketing efforts on this area or analyzing the Chicago segment to identify what’s resonating with them and applying those insights to other segments.
Example 2: Tailoring Content Based on Age Group
If you offer products or services that appeal to different age groups, you can segment your email list by age and tailor the content to each segment. For example, you might use different images, language, and calls to action for younger and older audiences.
You can track the engagement and conversion rates for each age group to see which content is most effective. For example, if you’re promoting a new mobile app, you might use more visual and interactive content for younger audiences and more informative and detailed content for older audiences.
Behavioral Segmentation Analysis
Behavioral segmentation involves dividing your audience based on their past interactions with your emails, website, and products. This is often a more powerful predictor of future behavior than demographic segmentation.
Example 1: Re-engaging Inactive Subscribers
Segment your list based on inactivity. Define “inactive” as subscribers who haven’t opened or clicked on an email in a certain period (e.g., 6 months). Send a targeted re-engagement campaign to this segment. This campaign should have a different tone and offer compared to your regular emails.
Here’s an example of a re-engagement email subject line: “We miss you! Here’s a special offer just for you.” The email body might include a discount, a free gift, or a request for feedback.
Track the open and click rates for the re-engagement campaign. If a significant portion of the inactive subscribers engage with the campaign, it indicates that they are still interested in your brand. If they remain inactive, you should consider removing them from your list to improve your deliverability.
Example 2: Targeting Customers Based on Purchase History
Segment your list based on past purchases. For example, you can segment customers who have purchased a specific product and send them targeted emails about related products or accessories.
If a customer has purchased a camera, you might send them emails about camera lenses, tripods, or memory cards. You can also segment customers who haven’t made a purchase in a certain period and send them a special offer to encourage them to buy again.
Custom Segmentation Strategies
Beyond demographic and behavioral segmentation, you can create custom segmentation strategies based on your specific business needs and goals.
Example 1: Segmenting Based on Survey Responses
Conduct a survey to gather information about your subscribers’ preferences, interests, and needs. You can then use the survey responses to segment your list and send them targeted emails based on their answers.
For example, you might ask subscribers about their favorite product categories, their preferred communication frequency, or their willingness to participate in loyalty programs. You can then use this information to create highly targeted email campaigns that are more likely to resonate with your audience.
Example 2: Segmenting Based on Website Activity
Track your subscribers’ activity on your website, such as pages visited, products viewed, and items added to their shopping cart. You can then use this information to segment your list and send them targeted emails based on their browsing behavior.
For example, if a subscriber has viewed a specific product page but hasn’t added the product to their cart, you might send them an email with a reminder and a special offer to encourage them to purchase the product. If a subscriber has added items to their cart but hasn’t completed the checkout process, you might send them a cart abandonment email with a reminder and a free shipping offer. This often requires integrating your email platform with your website’s analytics.
A/B Testing and Iterative Optimization
A/B testing, also known as split testing, is a powerful technique for optimizing your email campaigns. It involves creating two versions of an email (A and B) with one element varied between them, and then sending each version to a random subset of your audience. By tracking the performance of each version, you can determine which variation performs better and use that information to improve your future campaigns. Iterative optimization builds upon A/B testing by continuously refining your email strategy based on data-driven insights.
Testing Subject Lines
The subject line is the first thing recipients see, so it plays a crucial role in determining whether they open your email. Testing different subject lines can significantly improve your open rates.
Example 1: Testing Different Subject Line Lengths
Create two versions of your email with different subject line lengths. For example, version A might have a short subject line (e.g., “Summer Sale!”) and version B might have a longer, more descriptive subject line (e.g., “Summer Sale – Up to 50% Off!”).
Send each version to a random subset of your audience and track the open rates. Analyze the results to determine which subject line length performs better. Consider the context of your audience and industry when interpreting the results.
Subject Line
Open Rate
Summer Sale! (Short)
20%
Summer Sale – Up to 50% Off! (Long)
25%
In this example, the longer subject line performs better. However, it’s important to note that this might not always be the case. Short subject lines can be effective if they are concise and intriguing.
Example 2: Testing Different Subject Line Styles
Create two versions of your email with different subject line styles. For example, version A might use a question (e.g., “Are You Ready for Summer?”) and version B might use a statement (e.g., “Summer is Here!”).
Send each version to a random subset of your audience and track the open rates. Analyze the results to determine which subject line style performs better.
Subject Line
Open Rate
Are You Ready for Summer? (Question)
28%
Summer is Here! (Statement)
22%
In this example, the question-based subject line performs better. Questions can be effective at piquing curiosity and encouraging recipients to open the email.
Testing Email Content
Testing different elements of your email content, such as headlines, images,
