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Metrics beyond the vanity trifecta of subscribers, open rate and click rate

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Hey newsletter friends,
Lots of great feedback again last week - keep it coming ↩️
I try to send a brief personal email to all new subscribers asking which topics they are most interested in. Many readers reply with a few topics and often we end up having great email conversations. If you haven’t replied yet, you should. And if I forgot to send you a message, you should send me one to complain. Anything to get engagement 😉
But jokes aside, I really appreciate the input and “metrics” is one of the most frequently requested topics. So today’s issue is all about metrics, not just the vanity trifecta of subscribers, open rate and click rate, but real metrics.
Hope you enjoy the issue - if you do, please share it by email, Twitter, LinkedIn or just mention it in a conversation IRL 💌
Thanks, Mark.

Real metrics
Three metrics have dominated email measurements for a long time: Subscribers, open rate and click rate.
These metrics provide a good starting point of measuring how a newsletter is performing: How many people signed up for the list? How many of those actually read the emails? And which percentage of the readers takes action?
Revue provides these metrics just as any other email provider. Here’s what they look like for The week in newsletters:
But what can you do with these metrics? You can add a timeline to these metrics and compare them with the past. Is the list growing? Are open and click rates holding up? Or try to compare them with industry benchmarks or other newsletters of the same publication.
But that’s about it. They provide a high level snapshot but are shallow and lack context. They are shallow in the sense that they do not tell you why certain newsletters or issue are performing well or not. They lack context in the sense that they measure how your newsletter is doing from a technical perspective rather than in the context of your business objectives.
So which newsletter metrics can take us further?
One metric I quite liked and that delves deeper into the subscriber stat, is list composition. Jacque Boltik wrote an in-depth article on this and other metrics, complete with Python code to calculate it and generate charts.
Shifting the focus from aggregate list size to list composition means examining the current state of all email addresses acquired over the lifetime of the list, rather than a snapshot of the current moment’s total number of subscribers.
The Basic List Composition records the total number of unique email addresses contained in the entire list and breaks them into percentages. In this case, the entire list refers to all email addresses ever acquired, both currently and formerly subscribed.
List composition does a nice job of showing how many subscribers are still on the list versus how many have unsubscribed or had to be cleaned due to deliverability issues or lack of engagement. If these percentages are unhealthy, action needs to be taken.
Another metric that provides more depth is the percentage of readers who open 50% of newsletters per month. Dan Oshinsky does a great job of pointing out the importance of this metric:
This metric can help you see what percentage of your readers are making a habit of opening your emails. And those habits matter, particularly if you’re working on newsletters for a news organization. One new study found that building habit is key to acquiring and retaining subscribers.
Readers with more than 50% (or a different percentage) opens per month is interesting because we get a feel for which percentage of readers get enough value from our newsletter and is likely to keep reading or even ready for further action such as selling a subscription.
Which brings us to the second challenge - more context in newsletter metrics. We need statistics that show how the newsletter is contributing to our business objectives.
For example, recent research shows that for organizations selling subscriptions a key metric is loyalty. Emily Roseman translated loyalty into an actionable metric called “regularity” in an article for the Membership Puzzle Project:
I found that “loyalty” is often measured through “regularity” metrics — or the process of measuring the people who return again and again to take an action or use your product. 
Across data provided by 15 metro area publishers, they noted that only nine percent (9%) of users were “regular readers,” who view more than five articles in a thirty-day period.
For newsletters, that means tracking the number of readers that open the newsletter consistently and click through to articles for further reading regularly. And then optimizing the newsletter to grow this group even if that means slower overall list growth.
Community publisher WhereBy.Us has a different business model, a combination of donations, sponsoring and events. While “regularity” matters to them, it’s not the main focus. To be successful, WhereBy.Us instead needs to grow its newsletters in an effective way.
Anika Anand shared what that means in this article for OpenNews.
Step 1: List all the ways a new user can sign up for your product
Step 2: Choose metrics to measure the effectiveness of your growth sources. We decided that we needed to measure and compare three data points for each user acquisition strategy: the total number of new users that were acquired through the strategy, the time invested in acquiring those new users through that strategy, the engagement of those users
Step 3: Collate and analyze all the data
The effectiveness metric lets WhereBy.Us compare acquisition strategies. By doing so they added context to the shallow list size metric, and identified valuable list growth opportunities.
The week in newsletters
Enough metrics for today. If you’re here, you definitely count as an “open”. Did you click any links already? If not, here are three more articles to make it into the “click” category of our most loyal readers 👪
Indie authors saving local news
Factors for sender reputation
Newsletters to boost retention
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