For those who don’t know, I operate three different email newsletters. There’s my weekly Almost Timely newsletter, which is my personal newsletter that comes out Sundays. There’s the Trust Insights weekly newsletter, In the Headlights, which comes out Wednesdays. And there’s a weekday newsletter called the Lunchtime Pandemic Reading newsletter, which shares COVID-19 news every weekday (except holidays).
Of the three, Lunchtime Pandemic is my least favorite. Not because it’s a lot of work or because it’s daily rather than weekly, but because it’s one of those things that I wish didn’t need to exist. I live in America and for the first year of the pandemic, the federal government shared incomplete or in some cases, intentionally incorrect information about the pandemic. As a result, regular citizens had to find individual credible experts, read their content, and synthesize that information into action steps. That’s how the newsletter was born – it was (and still is) a roundup of credible information about the pandemic.
I’ve generally ignored until now the email marketing performance of the list because it was an email I created for my own benefit, not a commercial enterprise. Statistics and analytics didn’t matter to me because, well, I would have written the email even if no one had read it. But as we’ve navigated the ebbs and flows of the pandemic, I became curious about something. Each day, when I logged into the Substack platform (the free service I use for the pandemic newsletter), I’d see a quick summary of the previous day’s newsletter:
That got me wondering… did what was happening in the news have any impact on readership? After all, if you deem the pandemic more relevant during any given time period, maybe you might read the newsletter, whereas if what’s happening in your region isn’t so severe, maybe you’d read it less.
So I explored whether there’s a there, there with this line of thinking. I took my email stats and extracted them, then extracted pandemic statistics – cases, hospitalizations, deaths, etc. – and matched the two up. I filtered both datasets for just the United States, and wanted to see what, if any, relationship existed. Did any of the pandemic data have any relationship with my email data?
When we visualize open rates, it looks like this:
We see in the red line a bit of ebb and flow in open rates; the question is, does this pattern have any meaning?
When we do a Spearman correlation of open rates versus various pandemic measures, we see:
To make it more obvious, here’s a look just at read counts versus all the different pandemic measures:
We see the strongest relationship between both increases in hospitalizations and increases in deaths with newsletter readership.
Now, one of the dangers of correlation analysis is that correlation does not prove causation, but we might think it does. However, in this case, I’d say it’s safe to say that causality only runs one way: awareness of news about the pandemic drives readership, not the other way around. There are clearly cases in other domains where a newsletter would be a causal event, like lead generation, but this is not one of them.
Here’s the key takeaway: your email marketing statistics don’t exist in a vacuum. External events could be influencing readership, as awareness of an external situation changes the behavior of people on your list, assuming that your email marketing is relevant to those events.
If my pandemic newsletter were a business, my next steps would be to start surveying members, asking them what encouraged them to read at any given time. I might ask survey questions like “do pandemic statistics in your area encourage you to read more?” and if the answer was yes, I might start developing predictive models for readership. If I knew that hospitalizations severity predicted readership, then I could know in advance what my likely readership would be, and predict my email marketing performance from it.
Marketing doesn’t exist in a vacuum; our customers are part of the world, and the world has an influence on it. If we’re not asking ourselves from time to time what that influence is, we might find our performance suffering for reasons we can’t explain.
You might also enjoy:
- How to Set Your Public Speaking Fee
- Almost Timely: The 2020 Essays
- Transforming People, Process, and Technology, Part 1
- The Evolution of the Data-Driven Company
- How To Start Your Public Speaking Career
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