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Hubspot’s Dan Zarrella doesn’t spew “unicorn and rainbow” advice. In his webinar, The Science of E-mail Marketing, he used raw data to compile a comprehensive list of best practices for e-mail marketers. His counterintuitive findings are relevant to e-mail communication with your donors. Below are the three top takeaways from his presentation:
Timing
What day of the week should you send your e-mail blast? The best days may seem to be Tuesday, Wednesday and Thursday. But based on a study of nearly 10 billion of MailChimp’s records, e-mails read on Saturday or Sunday have the highest click-through rates. And what’s even more surprising, Tuesday has the highest unsubscribe rate. So why not try sending your next newsletter early (between 6 a.m. and 7 a.m.) on a Saturday?
Links, Links and More Links
The best way to boost your click-through rates is to include lots of links. There is a correlation between the number of links in an e-mail and the click-through rate. This tip becomes particularly important is when you want to push your donors to one specific page. Don’t make the mistake of including the link once, thinking that you are focusing your readers’ attention. Instead, use that one link throughout the email with language that will resonate with your readers in different ways.
Frequency
If you’re already e-mailing your database once a month, you can send your readers more messages without risking an increase to your unsubscribe rate. In fact, increased frequency is correlated to lower unsubscribe rates, so don’t be afraid to increase the frequency with which you e-mail your donors. However, there is a catch. Be sure that you are providing useful, relevant and interesting content in your blasts.
Is the Saturday Sunday revelation true for business/work email addresses too. hard to imagine. or must we segregate by personal v work emails and have separate strategies for each. Is there a best day for work emails?
Posted by Brad, 24/03/2011 6:37pm (1 year ago)
Nice to see people looking at real-world data instead of hypothesizing and believing it as fact. But correlation is not causation! Frequency, for example: could it be that organizations have a good grasp of how often to email their membership, and don't email them too much? And so advising them to increase their frequency actually would create a negative correlation between frequency and unsubscribe rates? Better to do a randomized test: randomly split your list, email one half more often, and see what happens to unsubscribe rates.
Posted by Michael Kaiser-Nyman, 24/02/2011 6:28pm (1 year ago)
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