Mailchimp remains one of the most popular email marketing platforms in the world, serving millions of businesses from solo entrepreneurs to large enterprises. Whether you're building custom reports, pulling data through the Mailchimp API, or analyzing campaign performance in the dashboard, understanding the full range of available dimensions and metrics is essential for optimizing your email marketing.
This guide provides a complete reference of every major dimension and metric available in Mailchimp as of 2026. We've organized them by functional area, included API field names for developers and analysts, and added practical context on when and how to use each one.
How Mailchimp Data Is Structured
Mailchimp organizes data around four core concepts: audiences (your contact databases), campaigns (email sends), automations (triggered sequences, now called Customer Journeys), and e-commerce stores (connected shop data). Each concept has its own set of dimensions and metrics.
An audience is a self-contained contact database with its own merge fields, signup forms, tags, and segments. Contacts within an audience have a subscription status (subscribed, unsubscribed, non-subscribed, cleaned) and can be organized using tags and segments. Mailchimp recommends maintaining one primary audience per business to avoid duplicate contacts.
Campaigns are individual email sends — newsletters, promotions, announcements — targeted at all or part of an audience. Automations are multi-step sequences triggered by subscriber behavior, dates, or API events. Both generate the same core email metrics but differ in timing and accumulation.
Campaign Dimensions
Campaign dimensions describe the configuration and identity of your email sends. These fields let you organize, filter, and compare campaigns across different types, audiences, and time periods.
| Dimension | API Field | Description |
|---|---|---|
| Campaign ID | id | Unique identifier for the campaign |
| Campaign Title | settings.title | Internal title of the campaign (not shown to recipients) |
| Subject Line | settings.subject_line | Email subject line displayed to recipients |
| Preview Text | settings.preview_text | Preview text shown after the subject in email clients |
| From Name | settings.from_name | Sender name displayed to recipients |
| Reply-To Email | settings.reply_to | Email address that receives replies |
| Campaign Type | type | Type of campaign: regular, plaintext, absplit, variate, rss |
| Status | status | Campaign status: save, paused, schedule, sending, sent |
| Send Time | send_time | Timestamp when the campaign was sent |
| Create Time | create_time | When the campaign was first created |
| Audience ID | recipients.list_id | The audience (list) the campaign was sent to |
| Segment | recipients.segment_text | Description of the audience segment used for targeting |
| Content Type | content_type | How the email was built: template, html, url, multichannel |
| Folder | settings.folder_id | Folder used to organize the campaign |
Audience/List Dimensions
Audience dimensions describe your contact database and the individual subscribers within it. These fields let you segment your audience by demographics, behavior, engagement, and subscription status for targeted campaigns and analysis.
| Dimension | API Field | Description |
|---|---|---|
| Audience ID | id | Unique identifier for the audience |
| Audience Name | name | Display name of the audience |
| Subscriber Email | email_address | Primary email address of the subscriber |
| Subscription Status | status | Contact status: subscribed, unsubscribed, cleaned, pending, transactional |
| Email Client | email_client | Email client used to open emails (Gmail, Outlook, Apple Mail, etc.) |
| Location (Country) | location.country_code | Country derived from IP geolocation |
| Location (Region) | location.region | State or region from geolocation |
| Location (Timezone) | location.timezone | Timezone from geolocation data |
| Tags | tags | Labels applied to the contact for organization and targeting |
| Signup Source | source | How the contact was added: signup form, import, API, admin, integration |
| Signup Timestamp | timestamp_signup | When the contact first signed up |
| Last Changed | last_changed | Most recent profile update timestamp |
| Engagement Level | member_rating | Star rating (1-5) based on subscriber engagement history |
| Language | language | Preferred language of the subscriber |
| VIP Status | vip | Whether the subscriber is marked as VIP |
| Marketing Permission | marketing_permissions | GDPR consent status for different marketing types |
Automation Dimensions
Automation dimensions describe your triggered email sequences — now called Customer Journeys in Mailchimp. These fields identify the automation, its trigger, and its configuration for reporting and optimization.
| Dimension | API Field | Description |
|---|---|---|
| Automation ID | id | Unique identifier for the automation |
| Automation Title | settings.title | Name of the automation workflow |
| Trigger Type | trigger_settings.workflow_type | What starts the automation: signup, purchase, date, tag, API, custom event |
| Status | status | Automation status: save, paused, sending |
| Start Time | start_time | When the automation was first activated |
| Email Count | emails_sent | Number of email steps in the automation sequence |
| Audience ID | recipients.list_id | The audience associated with the automation |
| Email Step Subject | settings.subject_line | Subject line for each individual email in the automation |
| Delay | delay | Time delay between automation steps (days, hours) |
Core Email Metrics
These are the fundamental metrics that measure how your emails perform — from delivery through engagement to negative signals. Every Mailchimp user should understand these metrics and their nuances, especially as privacy changes affect tracking accuracy.
| Metric | API Field | Description | Formula / Notes |
|---|---|---|---|
| Emails Sent | emails_sent | Total emails sent in the campaign | Count of all delivery attempts |
| Opens | report.opens.unique_opens | Unique subscribers who opened the email | Deduplicated by subscriber |
| Total Opens | report.opens.opens_total | Total open events including repeat opens | Same person opening 3 times = 3 total opens |
| Open Rate | report.opens.open_rate | Percentage of delivered emails that were opened | (Unique Opens ÷ Delivered) × 100 |
| Clicks | report.clicks.unique_subscriber_clicks | Unique subscribers who clicked a link | Deduplicated by subscriber across all links |
| Total Clicks | report.clicks.clicks_total | Total click events including repeat clicks | Includes multiple clicks on different and same links |
| Click Rate | report.clicks.click_rate | Percentage of delivered emails with a click | (Unique Clicks ÷ Delivered) × 100 |
| Hard Bounces | report.bounces.hard_bounces | Permanent delivery failures — invalid addresses | Contact is automatically cleaned (removed) after hard bounce |
| Soft Bounces | report.bounces.soft_bounces | Temporary delivery failures — inbox full, server issues | Mailchimp retries delivery. After repeated soft bounces, contact is cleaned |
| Total Bounces | report.bounces.bounces_total | Combined hard and soft bounces | Hard Bounces + Soft Bounces |
| Unsubscribes | report.unsubscribed | Subscribers who unsubscribed from the audience | One-click unsubscribe required by most email clients |
| Abuse Reports | report.abuse_reports | Subscribers who reported the email as spam | Critical — high abuse rates damage sender reputation |
| Forwards | report.forwards.forwards_count | Times the email was forwarded using Mailchimp's forward link | Does not capture native email client forwards |
| Forward Opens | report.forwards.forwards_opens | Opens from forwarded emails | New recipients who opened the forwarded version |
| Last Open Date | report.opens.last_open | Timestamp of the most recent open event | Useful for identifying ongoing engagement with older campaigns |
| Last Click Date | report.clicks.last_click | Timestamp of the most recent click event | Useful for tracking delayed engagement |
Revenue Metrics (E-Commerce)
Revenue metrics connect your email campaigns to actual sales through Mailchimp's e-commerce integrations. When connected to Shopify, WooCommerce, BigCommerce, or other platforms, Mailchimp tracks purchases and attributes revenue to campaigns.
| Metric | API Field | Description | Formula / Notes |
|---|---|---|---|
| Total Revenue | report.ecommerce.total_revenue | Total revenue attributed to the campaign | Sum of all order values from campaign recipients |
| Total Orders | report.ecommerce.total_orders | Number of orders attributed to the campaign | Count of purchases from campaign recipients |
| Average Order Value | report.ecommerce.average_order_revenue | Average value per attributed order | Total Revenue ÷ Total Orders |
| Revenue Per Email | calculated | Average revenue generated per email sent | Total Revenue ÷ Emails Sent |
| Products Sold | report.ecommerce.total_products | Total number of products purchased via the campaign | Sum of all line item quantities |
| Top Products | report.ecommerce.product_activity | Products most frequently purchased from the campaign | Ranked by order count or revenue contribution |
Audience Metrics
Audience metrics measure the size, growth, and health of your contact database. Tracking these over time helps you understand acquisition effectiveness, list hygiene, and overall audience quality.
| Metric | API Field | Description | Formula / Notes |
|---|---|---|---|
| Total Subscribers | stats.member_count | Total subscribed contacts in the audience | Active subscribers who can receive campaigns |
| Unsubscribed Count | stats.unsubscribe_count | Total contacts who have unsubscribed | Cumulative count of all-time unsubscribes |
| Cleaned Count | stats.cleaned_count | Contacts removed due to hard bounces | Automatically cleaned by Mailchimp |
| Subscriber Growth | growth_history | Net subscriber changes over time | New subscribers minus unsubscribes and cleans per period |
| Average Subscription Rate | stats.avg_sub_rate | Average number of new subscribers per month | Monthly average over the audience lifetime |
| Average Unsubscribe Rate | stats.avg_unsub_rate | Average number of unsubscribes per campaign | Average across all campaigns sent to this audience |
| Average Open Rate | stats.open_rate | Average open rate across all campaigns to this audience | Historical average — influenced by MPP inflation |
| Average Click Rate | stats.click_rate | Average click rate across all campaigns to this audience | More reliable than open rate for measuring engagement trends |
| Campaign Count | stats.campaign_count | Total campaigns sent to this audience | Cumulative count across the audience lifetime |
A/B Test Metrics
A/B test metrics let you compare the performance of different email variations to determine winning content, subject lines, send times, and sender names. These metrics are specific to campaigns created as A/B split tests.
| Metric | Description | Formula / Notes |
|---|---|---|
| Variant A/B/C Open Rate | Open rate for each test variation | Per-variant: (Unique Opens ÷ Delivered) × 100 |
| Variant A/B/C Click Rate | Click rate for each test variation | Per-variant: (Unique Clicks ÷ Delivered) × 100 |
| Variant A/B/C Revenue | Revenue attributed to each test variation | Requires e-commerce integration |
| Winning Variation | Which variant won based on the selected metric | Determined after the test waiting period expires |
| Test Group Size | Percentage of audience used for the test phase | Remaining audience receives the winning variant |
| Wait Time | Duration between test send and winner determination | Minimum 4 hours, up to 24 hours |
| Test Variable | What was tested: subject line, from name, content, or send time | Only one variable can be tested per A/B test |
Social Stats
Social metrics track how your email content performs when shared on social media. Mailchimp tracks social sharing through its built-in share buttons and connected social accounts.
| Metric | Description | Formula / Notes |
|---|---|---|
| Facebook Likes | Likes on the campaign when shared to Facebook | Via Mailchimp's Facebook share integration |
| Facebook Shares | Times the campaign was shared on Facebook | Through Mailchimp's social sharing buttons |
| Twitter Tweets | Times the campaign was tweeted | Through Mailchimp's social sharing buttons |
| Social Shares Total | Combined shares across all social platforms | Sum of all social sharing events |
| Recipient Shares | Subscribers who used the social share button in the email | Unique subscribers who clicked a social share link |
Comparative Metrics (Industry Benchmarks)
Mailchimp provides industry benchmark data that lets you compare your email performance against aggregated data from similar businesses. These benchmarks are based on data from millions of campaigns across the Mailchimp platform.
| Benchmark Metric | API Field | Description |
|---|---|---|
| Industry Open Rate | industry_stats.open_rate | Average open rate for your industry category |
| Industry Click Rate | industry_stats.click_rate | Average click rate for your industry category |
| Industry Bounce Rate | industry_stats.bounce_rate | Average bounce rate for your industry category |
| Industry Unsubscribe Rate | industry_stats.unopen_rate | Average unsubscribe rate for your industry category |
| Industry Abuse Rate | industry_stats.abuse_rate | Average spam complaint rate for your industry category |
| Industry Type | industry_stats.type | Your selected industry classification for benchmarking |
How to use benchmarks: Compare your click rate, bounce rate, and unsubscribe rate against industry averages to identify areas for improvement. If your click rate is above the benchmark, your content is performing well. If your bounce rate is above the benchmark, you need to improve list hygiene. Note that benchmarks are averages — top-performing senders consistently outperform them.
How to Use Mailchimp Metrics for Optimization
Having access to dozens of metrics is powerful, but knowing which ones matter for your specific goals is essential. Here is a practical framework for selecting the right metrics at each stage.
For campaign performance
Focus on click rate as your primary engagement metric — it's more reliable than open rate due to Apple MPP. Track click-to-open rate to measure content relevance separately from subject line effectiveness. Monitor unsubscribe rate and abuse reports as health indicators. Use revenue per email to measure direct business impact.
For audience health
Track subscriber growth (net new per month), engagement level distribution (how many 4-5 star vs. 1-2 star subscribers), and cleaned contacts as a percentage of total sends. A healthy audience has consistent positive growth, high engagement distribution, and minimal cleans.
For automation optimization
Compare per-step engagement (open and click rates for each email in the sequence) to identify where subscribers drop off. Track total automation revenue and revenue per automation email to measure business impact. Monitor queue size to ensure automations are processing without delays.
For e-commerce performance
Prioritize total revenue, orders, average order value, and revenue per email. Compare these across campaign types (promotional vs. informational) and audience segments to identify which combinations drive the most sales. Use top products data to inform future campaign content and product recommendations.
Link Performance Metrics
Link performance metrics show you exactly which links in your emails get clicked, how many times, and by how many unique subscribers. This data is essential for understanding which content, CTAs, and offers resonate most with your audience.
| Metric | API Field | Description | Formula / Notes |
|---|---|---|---|
| URL Clicks | report.clicks.clicks_by_url | Click count for each individual URL in the email | Shows which links attract the most engagement |
| Unique URL Clicks | report.clicks.unique_url_clicks | Unique subscribers who clicked each specific URL | Deduplicated by subscriber per URL |
| Top Clicked Links | report.clicks.top_links | Links ranked by total click volume | Helps identify most engaging content and offers |
| Click Map Data | report.clicks.click_map | Visual heatmap of clicks within the email layout | Available in the Mailchimp dashboard click map view |
Subscriber Activity Metrics
Subscriber activity metrics track individual subscriber behavior across campaigns, enabling you to build engagement profiles and identify your most (and least) active contacts over time.
| Metric | API Field | Description | Formula / Notes |
|---|---|---|---|
| Last Open Date | stats.last_open | Date of the subscriber's most recent email open | Used for engagement-based segmentation |
| Last Click Date | stats.last_click | Date of the subscriber's most recent link click | More reliable than last open for engagement scoring |
| Campaigns Received | stats.campaigns_received | Total number of campaigns sent to the subscriber | Cumulative count across the subscriber lifetime |
| Campaigns Opened | stats.campaigns_opened | Number of campaigns the subscriber has opened | Affected by Apple MPP — use click data for accuracy |
| Campaigns Clicked | stats.campaigns_clicked | Number of campaigns the subscriber clicked a link in | Most reliable individual engagement metric |
| Average Open Rate | stats.avg_open_rate | Subscriber's personal average open rate across all campaigns | Feeds into the star engagement rating (1-5) |
| Average Click Rate | stats.avg_click_rate | Subscriber's personal average click rate across all campaigns | Key input for engagement-based segmentation |
Apple Mail Privacy Protection Impact
Since September 2021, Apple Mail Privacy Protection has affected open tracking for a significant portion of email recipients. When MPP is enabled, Apple pre-fetches email content (including tracking pixels) regardless of whether the user actually opens the email. This inflates open rates and makes open-based metrics unreliable.
What to do: Shift your primary engagement metric from open rate to click rate. Use open rate only for relative comparisons (A/B tests where both variants are equally affected). Do not use open-based re-engagement campaigns to clean your list — you may remove engaged subscribers who use Apple Mail. Instead, use click-based engagement criteria for list hygiene.
Common Mistakes When Analyzing Mailchimp Data
Even experienced email marketers make these mistakes when working with Mailchimp metrics. Avoiding them will lead to more accurate reporting and better decisions.
1. Using open rate as the primary success metric
With Apple MPP inflating opens, open rate is no longer a reliable absolute measure of engagement. Use click rate as your primary KPI and open rate only for directional trends and A/B test comparisons.
2. Ignoring the subscriber engagement rating
Mailchimp's star rating (1-5) provides a quick engagement snapshot for each subscriber. Sending campaigns to your entire audience without considering engagement levels hurts deliverability. Regularly segment by engagement and create re-engagement campaigns for low-rated subscribers.
3. Comparing campaign metrics without context
A promotional campaign to your full audience will naturally have lower click rates than a targeted campaign to your most engaged segment. Always compare campaigns with similar audience sizes, segments, and goals for meaningful analysis.
4. Not connecting e-commerce for revenue tracking
Without an e-commerce integration, you have no visibility into how emails drive sales. Connect your store to Mailchimp to track revenue attribution — it's the most important metric for justifying email marketing investment and optimizing for business outcomes.
5. Maintaining multiple audiences
Multiple audiences in Mailchimp create duplicate contacts, fragmented data, and billing inefficiency (you pay for the same contact in each audience). Use one primary audience with tags and segments for organization. This gives you a unified view of each contact's engagement across all campaigns.
6. Treating industry benchmarks as targets
Industry benchmarks are averages that include both excellent and poor performers. They are useful as a baseline sanity check, not as performance targets. Set your goals based on your own historical data and aim for consistent improvement over your previous metrics.
