Choose the four or five email metrics worth tracking for your business.
Open any email tool after a send and you'll find a long report: delivered, opened, clicked, bounced, unsubscribed, forwarded, clicks by link, opens by hour, opens by device. Going through all of those after each newsletter takes time, and at the end you can still be unsure whether email is doing anything for the business. Lesson 8.1 dropped the open rate from the list of things to watch. What remains is a short set of four or five numbers, and each of them sits in a particular report or screen in your tools.
Click rate measures how many of your delivered emails produced at least one click. You calculate it by dividing the number of people who clicked at least one link by the number of emails delivered. Use the unique clicks figure, where the tool counts a person once per email however many links they click. Most tools work this way by default.
Priya writes a newsletter for parents. One issue reaches 300 parents, and 24 of them click something. 24 / 300 = 8 percent, so her click rate for that issue is 8 percent.
Opens can be recorded without anyone reading, but a click only happens when a real person acts. That makes clicks a far more dependable signal of interest than opens. They also show you which parts of an email worked. After each send, look at the clicks for each link side by side and note which ones people chose and which they ignored. Over several issues a pattern forms around topics. For Priya, issues about word problems draw more clicks than issues about exam timetables, every time, so she can conclude that parents care more about word problems.
Some tools also show click-to-open rate, which is clicks divided by opens. The idea is that it tells you what share of the people who opened found something they wanted to click. Privacy features now inflate the open count, and a bigger number underneath pulls the rate down by the same amount. Use it only to compare one issue with another over time, as a pattern, and don't read it as an accurate measure.
A click is not a sale, and to find out what happened after it you need two things set up. The first is links that tell your website analytics where each visitor came from. The second is analytics that records the action you care about, such as a booking or an order.
UTM parameters take care of the links. These are short tags on the end of a link that pass the source, medium and campaign of each visit to analytics tools such as Google Analytics. You can type them onto each link yourself, or let your email tool add them to every link automatically if it offers that setting. The course "Marketing analytics: GA4, attribution and testing" walks through setup in lesson 2.1 "What UTM parameters are and why analytics needs them".
Mei Ling (an invented example) runs a newsletter that leads readers to place orders. On a link in her December newsletter she sets the source to newsletter, the medium to email and the campaign to december dates. If a reader clicks that link and then orders, her analytics gives the credit for the order to that email.
Once the links carry tags and analytics is recording the booking or order, each email gives you two more figures. Conversions per email is the count of bookings or orders that came from it. Revenue per email is the money those orders brought in. For a monthly view, take the month's email revenue and divide it by the size of your list. The result is revenue per subscriber, a rough guide to what one subscriber is worth to you in a month. Mei Ling traces S$1,800 of orders to her emails in one month, and her list has 180 subscribers. S$1,800 / 180 = S$10 per subscriber.
If you've connected your shop to your email tool, the tool may show a revenue figure of its own. Expect it to differ a little from analytics, since each uses its own rules for deciding which email gets credit for a sale. Choose one of the two sources and use it every month so the figures stay comparable.
Unsubscribe rate is the share of delivered emails that led someone to leave your list. Spam complaint rate is the share of delivered emails that led someone to mark you as spam. A few unsubscribes after each send are normal and healthy, since people's needs change over time. Look at how the rate moves across many sends and don't react to one.
A rise in either rate means something has changed, and there are usually two places to look. Start with who you are reaching: a new signup source that doesn't fit your content, or an import that skipped consent, can bring in the wrong people. Then look at how often and when you send. A flow overlap like the one described in lesson 7.3 can mean some people get too many emails, or get them at the wrong times.
Of the two rates, complaints matter more, because inbox providers act on them (lesson 3.3 explained how). You can see your Gmail complaint rate in Google's Postmaster Tools once your sending volume is high enough for it to report.
The total number of subscribers can hide what is happening. A list can pick up fifty new subscribers in a month and still end the month smaller. Net growth shows the actual change. Start with new subscribers for the period. From that, subtract unsubscribes, hard bounces, complaints and anyone you removed while cleaning the list.
In a sample month, Priya gains 40 subscribers. 12 people unsubscribe, 3 addresses bounce and her re-engagement flow removes 15. 40 - 12 - 3 - 15 = 10, so her net growth for the month is 10.
When the figure is above zero, your list is building. When it's below zero, you're losing people faster than you gain them, and module 2 is where to go back to and work on finding subscribers.
Published industry averages for click rates and other email numbers need care, for three reasons. They blend very different businesses, lists and countries into one figure. Many are calculated from open rates, which privacy features now inflate. And the method behind them is rarely explained.
Your own month-on-month numbers are a better guide. You can see whether your click rate is going up or down, or whether a month in which you changed the format did better than the three months before it. That kind of comparison needs the send log from lesson 5.5 and a method of measuring that you apply the same way each time.
In the activity below, 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 you find each one in your tools, and what change in each would make you act.
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