The Synerise AI Developer Hub

Welcome to the Synerise AI developer hub. You'll find comprehensive guides and documentation to help you start working with Synerise AI API as quickly as possible, as well as support if you get stuck.
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Campaign distribution time optimization

Synerise AI platform is able to gather and analyse data regarding performance of marketing campaigns. Base on that our AI algorithms are able to predict best distrubution moment for each individual customer, including every marketing channel.

Time optimization helps you to select the best moment to distribute your campaigns. Thanks to this tool you are able to send campaign when people are most likely to open it. This option takes the guess work out of choosing the ideal send time, because we calculate this on the basis of data that we collect.
Our solutions offers two types of Time Optimization:

  • Individual - We adjust distribution time to each customer
  • Single Best - We adjust adjust distribution time to all customers

How does it work?

We use machine learning algorithms to analyze customers behavior and identify when they(customers) are most active. The algorithm analyzes new responses for every contact on a daily basis and updates its model accordingly. For new customers, their first emails will be sent at a time calculated on the basis of account's aggregate historical data.

Advantages of using campaign distribution time optimization

If you want to maximize the chances that your emails will engage your customers our Time Optimization tool is the best way to help you achieve that. However 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.

Integration

Our algorithms takes into consideration following events:

  • message.send
  • newsletter.click
  • newsletter.open

In order to upload those events please refer to Events API. We strongly suggest to import at least 3 months history in order to start using this feature. Importing more events will improve performance of predictive algorithms.