Send Time Optimization staggers email campaign launches over 24 hours and sends each email at a time after which the recipient is most likely to open it.

 The improvements made to specific STO components, boost the engagement rates of launched email campaigns.

STO uses machine learning to analyze your contacts’ behavior and identify the times when they are most responsive. This is independent of time zone, language or region. The contacts are then divided among 12 child campaigns, sent on the hour at two-hour intervals.

The improved algorithm has a more sophisticated way of using account-level information to optimize sending times for contacts with scarce behavior data. It is more likely to quickly learn the actual preferences of these contacts (and the new patterns in contact behavior) and consequently it tends to have a better performance in the long run.

Note that limited behavior history includes those cases when there is a solid amount of engagement data for a contact but email sends are limited to only a few send times.

For new contacts with no behavior history, their first emails will be sent at a time calculated on the basis of your account’s aggregate historical data on open times. But the algorithm analyzes new responses for every contact on a daily basis and updates its model accordingly. This means that we will have more accurate data over time. Our research shows that, after sending send time optimized campaigns, with the new algorithm, it generated an average 4.3% uplift in terms of click rates. It is nearly twice as large as the relative click-rate uplift (2.3%) that the original algorithm achieved. Note that the overall performance improvement and account-level results vary depending on multiple factors. 

In order to measure the benefits of STO, a control group of 10% of the launch list is also created for each campaign. The engagement results of this control group are used as benchmarks against which STO results are compared. This is done completely automatically, so you do not need to devote time and effort to performing A/B testing on your own.

• Send Time Optimization can currently only be enabled for batch email campaigns and for batch email nodes in Automation Center programs that do not start with a transactional entry node.
• Currently, the option Do not send to duplicate email addresses, which you can select in the Email Settings step when creating your campaign, does not apply to STO campaigns.
• Send Time Optimization can handle user lists that contain maximum 10 million contacts: the target segment or the Automation Center list of participants cannot contain more users. If the user list is bigger, sending will be canceled and the account owner will be notified via Emarsys Support.
• We do not recommend using segments or personalization based on Relational Data with STO because any changes to the data during the course of the STO campaign launch will cause errors. If you are using any Relational Data assets, then do not enable STO in the Send email nodes as it will cause contacts to be excluded from the launches.

You want to maximize the chances that your emails will engage your customers. Send Time Optimization is designed to help you achieve just that. For your customers, this is one more example of how you are treating them as an individual, strengthening their loyalty to your brand and improving their experience.
The new algorithm is even more likely to quickly learn the new patterns in contact behavior than the old algorithm was.

• Enable STO on a campaign-by-campaign basis.
• Use STO in Automation Center programs.
• Compare results against an automatically generated control group.
• Dashboard widget showing results over the last 30 days.
• Compare individual launch responses side-by-side.
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