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Einstein and Analytics in Marketing Cloud Engagement
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          Einstein Send Time Optimization

          Einstein Send Time Optimization

          Einstein Send Time Optimization (STO) in Marketing Cloud Engagement determines the best time to send a message. Using machine learning, Einstein predicts optimal send times so that a user is more likely to engage with your message.

          Einstein Send Time Optimization helps marketers increase email and push notification engagement. Using automated analysis, Einstein determines the best time to send a message to each individual contact. Each week, Einstein uses each contact’s latest commercial engagement data to recreate the sending model. The dashboard send count reflects both commercial and transactional sends, although modeling is based only on commercial event data and doesn't include transactional email sends.

          The Einstein STO Journey Builder activity sends messages to each contact at the time when that contact is most likely to engage with the message. When Einstein doesn’t have enough data to create a model for a contact, the contact receives messages according to a generalized model. The generalized model is derived from sending data in your Enterprise. The Einstein Send Time Optimization dashboard displays analytics that predict future message engagement.

          You can use Einstein STO in Automation Studio in a Send Email activity. Einstein gathers data for about 20 factors. It uses machine learning and 90 days of engagement data to determine the best time within the next 24 hours to send an email message to each contact. If your data isn’t processing, verify that the required sends are marketing email sends, not operational email sends.

          To use this activity, activate Einstein Send Time Optimization for your business unit.

          Note
          Note Einstein Send Time Optimization is included with Corporate and Enterprise Edition or available as an add-on purchase to Pro Edition. Einstein Send Time Optimization is also available as an add-on to customers with Pro Edition who have Journey Builder. For customers who have purchased a Corporate or Enterprise Edition before 10/27/2017, Einstein Send Time Optimization is available at no additional charge upon execution of an Order Form with Additional Terms. Contact your account representative for details.
          • Activate Einstein Send Time Optimization
            To find out how sending works for subscribers with low data, turn on Einstein Send Time Optimization (STO) in Marketing Cloud Engagement Setup.
          • Preview Optimal Send Times
            Review potential times that Einstein can send messages to the contacts in a data extension. If a data extension has numerous rows, previews are based on sampling data.
          • Einstein Send Time Optimization Dashboard
            Visualize optimal predicted send times for email addresses or contacts in a Marketing Cloud Engagement tenant or for all contacts in a business unit. Find out when subscribers are most likely to engage with your messages and insight about your Enterprise’s data quality, which fuels Einstein’s predictions.
          • Gauge Your Einstein Send Time Optimization Data Quality
            Check your Enterprise’s data quality score for insight about the engagement data that Einstein uses to predict optimal send times. Data quality scores for Einstein Send Time Optimization are generated at the Enterprise level only.
          • Einstein Send Time Optimization for Email Model Card
            The model in this card analyzes the optimal time to send an email to a subscriber to maximize the probability of the subscriber opening the email.
          • Einstein Send Time Optimization for Mobile Model Card
            The model in this card analyzes the optimal time to send a mobile message to maximize a contact’s probability of interacting with it. In Marketing Cloud Engagement, Einstein Send Time Optimization for Mobile optimizes notification push time to maximize the overall engagement of mobile apps.
           
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