Ecommerce email metrics that still work after Apple MPP

The email metrics that matter for an ecommerce store are the ones tied to money and to your ability to keep sending: delivery rate, click rate, conversion rate, revenue per delivered email, unsubscribes and spam complaints. Open rate, the headline number of email reports for years, stopped being reliable after Apple Mail Privacy Protection and should be treated as a weak signal. Below are the formulas, where each metric misleads, and how to build an honest dashboard for your store.

What Apple MPP changed

Apple describes Protect Mail Activity this way: when it is on, "your IP address is hidden from senders and remote content is privately downloaded in the background" (Apple Mail User Guide). In practice:

• the tracking pixel loads when the message arrives, not when someone reads it;
• Apple Mail users with the protection on show up as "opened", read or not;
• open location and open time are no longer trustworthy.

The result: inflated open rates, subject-line A/B tests that crown the wrong winner, and "didn't open, resend" automations firing at people who already read the email. Keep the number if you like, but stop using it to decide.

The metrics that matter, with formulas

Two notes:

• Divide by delivered, not sent, so a delivery problem never disguises itself as a content problem.
• Unique clicks, not total clicks. One person clicking the same link five times is not five times the interest.

Delivery: the metric before every other metric

If the email didn't arrive, nothing else matters. Watch:

• Delivered: the recipient's server accepted the message. Not a guarantee of the inbox, but the floor.
• Hard bounces: the address doesn't exist. Remove it immediately. More in hard vs. soft bounces.
• Delays (4xx): a spike at a single mailbox provider usually means reputation-based throttling.

On Pidgely these numbers come from delivery webhooks (email.sent, email.delivered, email.delivery_delayed, email.bounced, email.complained), the per-email log and the Metrics page. Hard bounces and complaints go straight to the suppression list, so you never keep mailing people who shouldn't get your email.

Complaints: the metric that decides whether you keep reaching people

Complaint rate is what mailbox providers watch. Google's sender guidelines ask senders to keep the spam rate reported in Postmaster Tools below 0.30% and recommend staying below 0.10%. For a store sending 100,000 emails in one campaign, 0.30% is 300 people pressing "report spam". That's not many.

What pushes complaints up for stores:

• mailing people who bought once two years ago and never clearly agreed to marketing;
• ramping frequency suddenly (Black Friday week is the classic case);
• hiding the unsubscribe link, so people use the spam button instead.

How providers count complaints is covered in feedback loops and complaint rate.

Revenue: attributing sales to email without fooling yourself

Revenue per email is the metric store owners understand. But "attributed revenue" depends on a choice: which window and which model.

• Last click: the sale counts for email if the last click before purchase came from it. Conservative and easy to explain.
• Click window: the sale counts if it happened within X days of an email click. Pick X (many stores use 1 to 7 days) and don't change it mid-season.
• Open-based attribution: avoid it. With MPP, "opened and bought within 5 days" credits email for sales it didn't drive.

The simplest reliable method today is UTM parameters on every link, with conversions read in your store analytics or platform reports:

https://example.com/products/runner-shoe?utm_source=pidgely&utm_medium=email&utm_campaign=bfcm-2026-early-access&utm_content=hero

Standardize utm_medium=email, name utm_campaign so you'll understand it a year from now, and use utm_content to know which block got the click.

Metrics by email type

Not every email should be judged by the same ruler:

For order emails, click rate is irrelevant: arriving within seconds is what counts. For abandoned cart emails, the right number is recovery rate, not opens.

List metrics: the asset behind everything

• Net list growth: new consented contacts minus unsubscribes, bounces and complaints in the month.
• Active base: contacts who clicked or bought in the last 90 or 180 days. Without trustworthy opens, "active" has to mean clicks and purchases.
• Revenue per contact: monthly email-attributed revenue divided by the active base. It tells you whether growing the list is worth paying for.

Segmenting by these behaviors is the subject of purchase behavior segmentation.

Where Pidgely fits (and what it doesn't do)

Plainly:

• Today: delivery, open and click webhooks, a log and timeline for every email, open and click metrics with machine opens and bot clicks flagged, automatic suppression of bounces and complaints, one-click unsubscribe on broadcasts, contacts with properties and segments. You can store purchase data (last order date, total spent) as contact properties, personalize with them and build segments from your own system through the API.
• Store integrations: connect Shopify, WooCommerce, Nuvemshop or VTEX to sync customers, products and orders and send order emails automatically.
• Automations (Scale plan): abandoned cart, unpaid Pix/boleto, post-purchase and win-back for connected stores, with recovered revenue counted once per order within an attribution window.
• Not offered: revenue attribution for broadcasts. For campaign revenue, use UTMs and your store analytics as shown above.

A minimal dashboard for your store

If you only look at six numbers per campaign, make it these:

1. Delivery rate
2. Bounce rate
3. Complaint rate
4. Click rate (via UTMs or your tool)
5. Attributed orders and revenue, with a fixed window
6. Unsubscribes

Compare each campaign with your own recent average, not with generic internet benchmarks: list, niche and frequency change everything. And when revenue rises together with complaints, be suspicious: you are trading today's result for tomorrow's inbox. How to avoid that is in ecommerce campaigns that avoid spam.