Email marketers (myself included) always say; don’t over mail your email list. Whilst this is still good advice, what determines over mailing has changed. We are all used to email now and Spam is pretty well controlled by Outlook (Hotmail), Gmail, Yahoo etc. We also spend a lot more of our lives online and managing our various email accounts is just part of what we do during our day.
This means that our tolerance for email has increased, in fact, if we receive too few emails we are likely to forget about the brands that send them (see here for more about frequency).
So when is the best time to send emails these days? The huge uptake of mobile devices in recent years means most of us check our emails throughout the course of the day so the answer, annoyingly, may seem that there is no best time any more.
The tradition has generally been to send between Tuesday and Thursday and these are still days that perform well in terms of open and click rates. However, it does mean you’re competing with a lot of other marketing emails and if the internet has taught us anything, it’s to break with tradition.
So you need to work out which days and times are the best for your audience and that means analysing previous campaign reports and testing which send times give you the best results, not just for opens and clicks but for enquiries and sales.
The classic open curve for a 7am send time looks something like this:
Later in the day at 5pm it’s more like:
At 8am on Saturday we see:
The first thing these open and click patterns show us is that people start opening the email within minutes of them being sent, highlighting the increasing ‘always on’ mentality we have these days. The second is that, the earlier in the day emails are sent, the flatter the fall off, which isn’t really surprising as the daytime is when most of us are awake. It also appears few of us lie in on a Saturday, or at least not without opening emails first!
However, these timelines are for the same email sent to a single list – so no segmentation or change in the message. To really understand when people like to read your emails you need to break down your data in to smaller groups and test a range of send says and times.
Research from a number of sources show around half of us open emails between 6am and midday, but meaningful decisions, such as purchases are higher in the evenings and at the weekend, suggesting people need some time and thinking space to do the thing you want them to do.
So, what can you do to find out when your audience likes your emails most?
Segment your data by age to check the percentage of opens by device as well as which times work best – the younger age groups are more likely to use their phones more than computers so check their emails later into the evening. Conversely, you may find that the older age groups open their emails in the earlier in the morning, but testing will give you a greater insight.
Segment by email domain, it can take while for emails to appear in Outlook (Hotmail) so you may want to send that earlier and when Gmail finally roll out Grid View you’ll want to be in the top three rows to be seen, so you may want to send to your Gmail data to hit one of the peak opening times of mid-evening, lunchtime and the morning commute.
Group people into the hour they signed up for your emails and send them emails in that hour – the most you’ll get is 24 segments and the smaller ones (between the hours of 10pm and 9am) can probably be merged together.
Split by gender – as equal as we all are in 2014, many of us socialise at different times and can have lives dictated to by children – my local Starbucks is pram city around 10am on weekdays!
Lastly, don’t forget to make your best customers feel special, send them the latest offers, sale notifications and best deals before everybody else.
Review the results from your testing and the work that has gone in to it and make decisions on which areas to continue with, change or discard and where you can be more efficient. As ever, with any additional work to campaigns the gains you see need to outweigh the resource expended.