Newsletter Stats from the Pencilneck CMS

So our CMS, the Pencilneck CMS includes a email newsletter management system. With a little time between finishing one project & starting the next, I took some time to analyze the data we generate – in part out of self-interest, but also as part of a new project to provide additional analytics tools for our clients. Having spent the better part of a morning generating data, I thought I’d share this information with the general public. I’d love to know how this corresponds to the data from other newsletter delivery systems.

All times report are Pacific Time. All hours cited include the entirety of the hour. For instnace, 8AM means all time between 8:00:00 and 8:59:59, inclusive. For time-of-day reporting, I divided up the hours into 4 blocks – unequal in length but useful for business hours:

  • Midnight-7AM: the Pre-work period
  • 8AM – 11AM: the morning at work.
  • Noon-4PM: the afternoon at work.
  • 5pm-11PMt: the evening at home

Number of Newsletter Recipients: 7,956,301

These first few numbers are based on the number of sends, so when our clients decided to send a newsletter.

Most Popular Day to Send a Newsletter: Tuesday (34%), Monday (28%).
Least Popular Day to Send a Newsletter: Saturday(1%), Friday (5%).

Most Popular Time of Day to Send a Newsletter: 8AM-11AM (40%), Midnight-7AM (25%)
Least Popular Time of Day to Send a Newsletter: 5PM-11PM (2%),Noon-4PM(10%)

Most Popular Day & Time to Send: Tuesday Midnight-7AM (34%), Monday 8AM-11AM (30%)
Least Popular Day & Time to Send: Friday 5PM-11PM(1%), Saturday 5PM-11PM (3%)

These next set of numbers are the “best” results based on open rate. The Open rate was calculated by dividing the number of newsletters that were opened vs the number of newsletters received. A newsletter is considered received if our system did not receive any bounce notifications regarding the delivery.

Best Day to Send a newsletter: Sunday (35%), Monday (33%)
Worst Day to Send a newsletter: Saturday (2%), Friday (8%)

Best Time of Day to send a newsletter: Midnight-7AM (40%), 5PM-11PM(35%)
Worst Time of Day to send a newsletter: 8AM-11AM (5%), Noon-4PM (8%)

Best Day & Time to send a newsletter: Monday Midnight-7AM (65%), Sunday 5PM-11PM(45%)
Worst Day & Time to send a newsletter: Saturday Midnight-7AM(1%),Friday Noon-4PM(3%). And worth mention is Wednesday Noon-4PM (4%).

We also, by way of Geolocation via IP address, can track where a recipient opens a Newsletter. For our clients, we group this by Province & State for Canada, US, Mexico & Australia, and the rest of the world simply by Country. I discounted all geo-data with less than 100 total recipients, to single out places like Ghana & its 100% open rate based on 4 recipients. Actually, the same recipient, 4 times.

Best open rate, by Recipient location: Ontario (65%), British Columbia (45%)
Worst open rate, by recipient location: Alberta (4%), Minnesota (5%)

Finally, I looked at links, and where they appear within the source code. To do this, I stripped all the header & styling information from the HTML source, leaving just the body, and divided that into quarters to see which links were the most clicked on. These results are probably not that surprising, but nevertheless. I determined the click rate by calculating the total number of recipients who clicked on a link vs the total number of opened newsletters. I then split that up based on which portion of the newsletter the click was in.

Overall clickthrough rate: 11%.
Average number of links per newsletter: 6
Most links in a newsletter: 104

Clickthrough rate for links in the third quarter of content: 9%
Clickthrough rate for links in the first quarter of content:
19%.
Clickthrough rate for links in the second quarter of content
: 8%
Clickthrough rate for links in the third quarter of content
: 4%
Clickthrough rate for links in the last quarter of content
: 15%

Given these numbers, I then calculated the overall percentage of links per quarter of content:

Links found in the first quarter of content: 14%
Links found in the second quarter of content: 46%
Links found in the third quarter of content: 28%
Links found in the last quarter of content: 12%

I’m not entirely sure what to make of all this. Some other random notes:

  • In general, Ontario & BC have a vastly higher open rate than anywhere else in Canada.
  • For the US, the 2 coasts open a rate about twice as much as middle America.
  • Germans are the most diligent European newsletter recipients.
  • It seems fairly clear that the best way to get someone to read your newsletter is to have it arrive before they get to their desk, but not so early as to have a lot of mail arrive between it arriving and the recipient checking their mail. Monday mornings are definitely the best for this.
  • Wednesday shows a general dipping in all stats. It really is hump day.
  • People skim newsletters: That’s why the top & bottom of your newsletter have the best click-through rates. This is likely partially explained by “Click here to view online” & Logos at the top & Unsubscribe links at the bottom of newsletters.
  • I’d love to do some signal-vs-noise analysis of newsletter – that, the clickthrough rates based on % of content that IS as link vs % of content that is NOT a link. My belief is that briefer newsletters do better.

I’ve stored all this data, along with the queries used to generate it all so I can now do this semi-regularly. Ideally, I’ll find some time to craft a simple API on this so that anyone could pull this anonymous, aggregate data to use, but I suspect that will be a long-term back-burner sort of project.

The power of Twitter & the “Ellen Effect”

So, on Thursday, one of my clients, the Vancouver Orphan Kitten Rescue Association (VOKRA) was linked to from the Ellen DeGeneres Show’s Blog, after being mentioned on the show. At the same time, a tweet was sent from the @TheEllenShow twitter account (As an aside, the reason for all of this is that Anna Torv, who is the star of the Vancouver-filmed show Fringe, fosters kittens for VOKRA, so she’s now much cooler in my books than she was before I knew this). Because of this one-time spike, I thought it would be interesting to have a look at VOKRA stats to see what sort of effect this had on their site, particularly as I had been worried a huge flood of traffic might down our servers (for the record, they passed with nary even a flinch. The charts below will show why).

The Ellen Bump
The Ellen Bump

As you can see, traffic generated from Ellen gave VOKRA a huge, but very brief, jump in traffic, from an average of 300 visitors a day to 3900 visitors. Which is nice to see. But, given Ellen’s reach (she’s the 4th-most influential woman in media & has over 3 million followers on twitter), I had been expecting a larger bump from it.

What’s particularly interesting, however, is how that traffic arrived at VOKRA:

How Ellen Viewers reached VOKRA
How Ellen Viewers reached VOKRA

Twitter blew the link on Ellen’s blog out of the water, driving 3 times more traffic to it than the links on the blog. Of the twitter traffic, all but 100 of those clicks came either from the individual tweet or the main page of Ellen’s account – the split is about 50/50 (of those 100 remaining visitors, all but 3 came from my own tweet – thanks, followers!). Being mentioned on the show was nearly as powerful as the tweet. Breaking down those Google searches, the most common was “kitten rescue vancouver ellen“, which suggests to me that comes from people watching the show and searching. A mere 839 visitors clicked through from the blog post itself. Although, perhaps not that surprising: It takes far more investment in the topic to do that, as likely, you’ll

  1. Watch the show & become interested in the topic
  2. THEN go to the Ellen show’s website and read more
  3. AND FINALLY, click through to the end point.

Which is yes, only one extra step, but in terms of buy-in, seems much, much more to me.

A final analysis. What VOKRA wants more than anything when you go to their site is one of 2 things:

  1. Apply to adopt a kitten
  2. Donate to them

What’s disappointing is that all this traffic had almost no effect on either of those 2 goals. There were a few more applications than usual over the past couple of days – a total of 14, vs, I believe, 8 for same period the previous week. And there was no effect on donations – no increase in either number of donations or amount over the previous week (given the increase in visitors, their donations-per-visitor ratio in fact just took a huge hit).

My conclusions to the above? VOKRA’s homepage is not as effective as it should be in communicating those 2 goals, and should be looked at (hopefully this analysis will mean that I get the chance to do). Analyzing what visitors did at the site, nearly every visitor clicked on the big cat banner picture – and then nothing else. The 2nd most popular click was to the blog post about being on Ellen – and then nothing else. In fact, the links to adopt & donate did not see a similar-sized jump in clicks, whereas the blog, gallery¬† & about us pages all did.