- What day of the week should you send out your emails on?
What subject lines will get better open rates?
These are all the eternal questions when sending out
emails for marketing campaigns.
And the only way to get answers
is through good old trial and error.
You have to get started sending
in order to test and iterate.
Iteration is the act of repeating a process
to generate a sequence of outcomes with the aim
of approaching a desired goal, target, or result.
In the beginning having a thorough understanding
of your audience will be helpful in what you send and when.
Then as time goes on you'll be able to learn
which emails perform better and why.
One of the best ways to test out specific variables
in your email campaigns is through A/B testing.
A/B testing allows you to send
different versions of the same email
with one changing variable.
Variables such as subject line, content, or send time.
Most email marketing services
like MailChimp have this feature.
And this may be something that you
seek out when choosing one.
A/B testing allows you to send different versions
of the same email with one changing variable.
Things like the subject line, from name,
content, or send time.
You have the option to select the percentage
of subscribers that receive either version A or B
and MailChimp, in this example, will track the entire test.
At the end you'll be able to see clearly
which email performs the best.
Here we are on the MailChimp A/B test option.
You get there by selecting create a campaign
and then selecting A/B test at the top.
So I'm gonna give this a quick campaign name.
I'm gonna call it A/B test campaign.
And that way we can see a little bit clearer
the different options that are available.
The next thing I'm gonna do is I'm gonna choose a list.
This is a list that I want to send the email campaign to.
I'm gonna keep the entire list selected
and choose next.
Now that I'm on the A/B testing dashboard
I am able to choose a variable that I want to test.
So I can test up to three combinations.
In the beginning I suggest sticking to one.
So I can test my subject line, from name,
content, as well as my send time.
So if I select subject line, I can choose two
that I'm going to test.
Below that is the percentage of recipients
that will receive the combinations.
So you can do a 50 50 split,
or you can cater it to your needs.
Below that you're gonna specify how MailChimp
is going to determine a winning combination.
So again, depending on your goals and your objective
you can choose click rate, open rate, revenue,
or something more manual.
And then you can choose whether it's hourly or daily
that you're gonna specify.
I do want you to know that A/B testing only
really works well with a larger list.
We're talking lists of at least 5,000 recipients.
If you are just starting out focus on building your list
and sending valuable content in your emails.
That way you can grow your list up to that 5,000 mark
and you can really start testing out what performs well
with your audience.
After you begin A/B testing you're going to see
some results.
So you're gonna see the subject lines that perform well
you're gonna really understand the send times that get
the highest click rates.
And then you're gonna be able to iterate on those results.
That means that you're going to decide what you wish
to improve upon, test that objective using tools
like A/B testing.
Then you're gonna analyze your finding and improve upon
that result.
Take some time now to take a look at your A/B testing tools.
If you do have enough of an audience,
start testing out different variables.
And if you don't really focus on growing that list.
After you receive your results from your tests
be it A/B or other, your next step
will be to iterate on those results.
That means looking at the variable you chose to test
and determining the clear winner.
Once you have that information
start constructing email campaigns using that new data.
For example, if you determine that afternoons
are better than mornings for open rates,
start sending out emails in the afternoons.
Then watch to see if your overall email open rate improves.
The key is to decide what you wish to improve upon,
test that objective using tools such as A/B testing,
then analyze your findings and improve upon the result.