Determining the best send times for email newsletters

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Determining the optimal time to send your organisation’s newsletter can be challenging. There is no one size fits all method. Rather, your engagement goals, audience and industry will all play a role in determining your optimal timing.

Commence with testing

Testing what works and what doesn’t work for your audience in every aspect is the basis of perfecting email engagement. This involves testing the time of day the email is sent, subject lines, copy, and other essential features.

Note that this may vary based on target demographic, product, and email kind (e.g. feature announcement versus welcome email). It may seem daunting to test so many things with multiple segments, but there is a methodical way to conduct email tests that will make identifying trends easier: A/B evaluation.

Segment your subscriber list

To segment your subscriber list, break your email list into smaller lists based on essential factors such as demographics, business type, purchasing habits, and location. You will be able to determine what has the greatest influence on your audience and deliver better-targeted email marketing in the future through the use of segments.

Your email marketing platform should ideally have a segmentation feature that simplifies the process.

Develop a hypothesis

Once you have segmented your lists, construct a hypothesis. To create your hypothesis, select a subset of your list to focus on, and then select a single factor to test that is essential for that subset.

For instance, you may make an educated assumption regarding the impact of modifying the time at which you send welcome emails. Similar to goal-setting, your hypothesis should be SMART (Specific, Measurable, Achievable, Relevant, and Timebound). In this scenario, your hypothesis may be “sending welcome emails within 150 minutes of a person joining will increase email open rates by 8% within the new user group over the next three months.”

Divide each segment into test groups “A” and “B”

After forming your hypothesis, divide the subscriber segment into two groups: “A” for your control group and “B” for your test group.

Ensure that the results are not skewed in one direction by randomly dividing the segment into equal parts. Using an email service provider (ESP) with in-built A/B testing is the simplest method for achieving random group selection.

Determine if each group is sufficiently large to yield statistically significant findings to collect the most accurate data. If the groups are too small or insufficiently diverse, the test will likely reflect random outcomes. In contrast, a larger group will improve the accuracy of the results by decreasing the likelihood of randomness.

A statistically significant group is decided by a handful of factors and extensive mathematics. If you are not a statistician, you can easily determine the optimal size by utilising an A/B calculator. A reasonable beginning size is typically at least one thousand subscribers, however, this can be smaller depending on the test and subscriber list.

Develop A and B test assets

To test a specific element of your email, generate two variants of the identical email with only the element you wish to test altered to reflect your hypothesis, such as the timing of a welcome email.

To achieve this, you would produce two identical welcome emails, but send one at the average hour and the other at the time suggested by your hypothesis. If you generally send welcome emails two days after a user’s registration, send the control email at this time. Your test group email might be issued ten minutes after the new user joins to compare its effectiveness to the control group’s baseline results.

The only difference between the two emails should be the time at which they were sent. Testing many variables is referred to as multivariate testing. A multivariate test would be used, for instance, if you were evaluating both the time the email is sent and several subject lines. Multivariate testing should only be used when testing combinations of different factors. And it is preferable to only perform multivariate testing after testing each element individually.

After testing and determining the optimal time to send your email, for instance, you may combine it with winning subject lines to determine the combined impact. If you attempt to test every part of an email simultaneously, it can be tough to discern which contributes positively or negatively to the overall result.

Analyse the data

It is now time to evaluate the results and determine whether your hypothesis was accurate or not. Examine the open rates of each email segment while evaluating the aforementioned hypothesis, for instance, to determine the impact of send time. The group with the highest open rate would be deemed the “winner.”

If you are utilising an ESP with built-in A/B testing, the platform should handle the majority of the labour.

In addition to examining the results as they pertain to the particular test, evaluate the results in the context of the overall performance of your email newsletter. This will allow you to acquire a deeper understanding of its possible impact on other email categories. Consider conducting the same test with other list segments if, for example, a customised subject line increases open rates among new customers.

Optimise based on outcomes

The collected and analysed data will only be as useful as its implementation. The key to long-term success is implementing the test result recommended improvements and continuously refining them. Your audience’s demands will certainly evolve, and as a result, your email marketing campaigns must be flexible. A/B testing should be a continuous exercise conducted to make adjustments effectively.

Consider that how you optimise your email will have varied effects. Before making any modifications to your email marketing, it is vital to have a key objective. Remember that the optimal day and time to send an email depends on your industry and your objectives.

Personalising your adjustments to each audience segment is crucial, as the audience is a major factor in email optimisation. Large-scale, global modifications to your email marketing are often less effective. To have the best impact, they must be personalised and tailored to the requirements of each target segment. 

Optimise your organisation’s newsletter with Resonate

How effective is your organisation’s newsletter currently? Is it achieving your objectives?

Is your newsletter effectively and continuously being optimised?

If you feel that your organisation does not realise the maximum benefits of an optimised newsletter, Resonate can help. Please get in touch to discuss precisely how we can help your organisation succeed in the area of newsletter optimisation.

Girish is the CMO & Co-Founder of Resonate.

GV is our Marketing and Delivery head. He keeps our clients’ marketing strategy on track and leads the Resonate team to deliver commercial outcomes.

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