The 4 Key Datapoints To Focus On For Newsletter Success (And How To Analyze Changes)
While many creators dislike the idea of newsletters, they are essential for scaling any side hustle into a profitable small business.
Newsletters give you a direct line to your audience without needing to rely on the whims of social media algorithms. Just like social media though, without careful treatment, any newsletter can stall growth and feel like it's not worth the time. "What gets measured gets improved," is a common rephrasing of a Peter Drucker, but is still true, so to improve a newsletter, we need data.
Instead of wading into all the analytics options, I've narrowed it down to 4 that will not only help identify where we can make improvements, but how to test those improvements.
Datapoint 1: Opt-In
The newsletter opt-in is the entry to a newsletter and measured by the number of site visits divided by number of people who join.
Opt-in rates are usually low—less than 1%—for most websites, but that can get as high as 40% with the right lead magnet. To test an opt-in, all you need is 2 separate webpages and offers so you can track page views and opt-ins from those pages.
My recommendation is to A/B test the type of opt-in and only work on fine-tuning once you know you have the right type.
Datapoint 2: Open Rate
If emails are not being opened, they can never be effective.
Ideally, at least half of your emails are being opened, but unopened emails come down to people either consciously not reading them or people not seeing them because they are being filtered out of their inbox automatically. We'll focus on subject lines for simplicity today. If you're trying to be clever in your subject lines, just stop and be clear instead.
We can also A/B test subject lines by sending half the email list one subject line and half another, but keeping 100% of the content inside the email identical.
Datapoint 3: Click-Through
People are reading your emails, but now we need to understand how they behave when we ask them to do something.
For click-through, we're not as worried about whether someone decides to make a purchase or subscribe to something, but that they at least clicked the link in the newsletter to get more information. Trackable links are an amazing tool to have at your disposal and we can use them in the newsletter to help test. Use a separate link for each email flavor sent to keep the data consistent.
Test by keeping the body of the email the same except for your call to action and send one version to half your list and an alternate to the other half.
Datapoint 4: Bounce
Finally, the dreaded unsubscribe metric for people who decide they no longer want to get emails.
First, if the newsletter's message aligns with the company's vision, then it's better for people to unsubscribe than to simply stop reading or flag the list as spam. So I am not overly concerned with the bounce unless it is so high that the list is not consistently growing. Start by identifying the general types of emails that are sent (product plugs, value, watch this, etc) and see if there are general trends for types.
Segment the bounce rate analysis by those categories and see if segmenting the list so readers can opt-in or out of those specific segments helps (drop low performing categories or rework the content of the emails with A/B testing).
