You will be able to choose the four or five email metrics worth tracking for your business.
Open the reports in any email tool and you will see dozens of numbers: delivered, opened, clicked, bounced, unsubscribed, forwarded, clicks by link, opens by hour, opens by device. It is tempting to check them all after every send, and it is easy to come away knowing a lot of figures and nothing about whether email is helping the business.
Lesson 8.1 set the open rate aside. This lesson picks the four or five numbers that remain worth tracking, and shows where each one comes from.
The click rate is the share of delivered emails in which someone clicked at least one link. Most tools count each person once per email, often labelled unique clicks. If Priya's example newsletter is delivered to 300 parents and 24 of them click, her click rate is 8 percent. That calculation divides 24 by 300.
Clicks need a person, so they are a far more trustworthy sign of interest than opens. They also tell you about content. Look at which links got clicks and which did not. When Priya's issues about word problems consistently get more clicks than her issues about exam timetables, she learns what her parents value.
Many tools also report click-to-open rate: clicks divided by opens. In principle it shows how many of the people who opened found something worth clicking. In practice, because opens are inflated by privacy features, the click-to-open rate is pulled down by the same amount, so read it only as a pattern over time, comparing issues against each other, not as a true measure.
A click is not a sale. To see what happened after the click, you need two things: links that tell your website analytics where the visitor came from, and analytics that record the action you care about, such as a booking or an order.
The first part is done with UTM parameters: short tags added to the end of a link that tell analytics tools such as Google Analytics the source, medium and campaign of each visit. A link in Mei Ling's December newsletter might be tagged with source newsletter, medium email and campaign december dates. When someone clicks and places an order, her analytics can credit that order to that email. Many email tools can add UTM tags to every link automatically. The course Marketing analytics: GA4, attribution and testing covers the setup in lesson 2.1, What UTM parameters are and why analytics needs them.
With that in place, you can track conversions per email (bookings or orders that came from it) and revenue per email. Dividing a month's email revenue by your list size gives revenue per subscriber, a number that tells you roughly what each subscriber is worth to you in a month. In Mei Ling's example, S$1,800 of orders traced to email in a month, with 180 subscribers, works out to S$10 per subscriber.
Shop integrations often report revenue inside the email tool too. Its figures may not match your analytics exactly, because the two use different rules for giving credit. Pick one source and use it consistently.
The unsubscribe rate and the spam complaint rate are the share of delivered emails that led someone to leave or to report you. Some unsubscribes are normal and healthy, since people's needs change. What matters is the trend.
When these numbers rise, something has changed. Often it is the wrong people, such as a new source of signups that does not match your content, or an import that skipped consent. Or it is the wrong frequency, such as a flow overlap of the kind lesson 7.3 described. Complaints matter most, because inbox providers act on them, as lesson 3.3 explained. Google's Postmaster Tools shows your complaint rate for Gmail when you send enough volume.
List size on its own can mislead. A list can gain fifty new subscribers in a month and still shrink. Track net growth: new subscribers minus unsubscribes, hard bounces, complaints and anyone you removed in cleaning. In Priya's example month, she gained 40 subscribers and lost 12 to unsubscribes, 3 to bounces and 15 to her re-engagement flow. Her net growth was 10. A positive number means the list is building. A negative one means you are losing people faster than you find them, which points you back to module 2.
You will find published industry averages for click rates and other email numbers. Treat them with care. They mix very different businesses, lists and countries, they are often based on open rates now inflated by privacy features, and the method behind them is rarely clear.
The comparison that tells you most is your own numbers, month on month. Is your click rate rising or falling? Did the month you changed your format do better than the three before? That needs the send log from lesson 5.5 and a consistent way of measuring.
In the activity below you will write down the five numbers you will track, where each one comes from in your tools, and what change in each would make you act.
Write down the five email numbers you will track, where each comes from in your tools and what change would make you act.
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