See more insights in one place and find out more about each insight on the Einstein Messaging Insights dashboard. Click an insight to access contributing factors that influenced the send’s performance.
Use the Einstein Messaging Insights dashboard to view and analyze anomalous results after a batch send or journey send. The dashboard shows send-related information, such as Job ID, Date Sent, and Total Delivered. It also clearly shows data about each send and the variable that was identified as an anomaly. Batch sends include factors that Einstein determines can influence send results. Contributing factors appear in sentence format and table format.
- Einstein evaluates each journey and each send once each day to produce insights.
- Emails track events, such as opens and clicks, for many days after sending. Einstein uses the events collected for up to 7 days after an email send to reassess whether the send is an anomaly or not.
- The variables that Einstein Messaging Insights measures for Journey Insights and Batch Send Insights are open rate, click rate, and unsubscribe rate.
Journey Insights
- Rather than analyzing a single journey email against that email’s previous performance, Einstein analyzes all email activities in a journey to find anomalies.
- Einstein uses up to 90 days of performance data to measure the rolling average performance of a variable. This average is used as the expected value for the variable that’s measured.
- The upper bound on the dashboard is the anticipated maximum performance that Einstein calculates for the variable that’s measured. The upper bound is set at a 95% confidence interval above the rolling average.
- The lower bound is the anticipated minimum performance of the variable. The lower bound is set at a 95% confidence interval below this rolling average.
- Journey updates such as activating a new version are indicated by dots on the graph. To find out what kind of update each dot indicates, use the key beside the anomaly graph.
- Top Contributing Factors aren’t available for Journey Insights.
Batch Send Insights
- Einstein uses a group of similar sends from within the last 90 days to calculate the average performance of a variable. And Einstein determines the similarity of sends using variables including send size and several other factors.
- The upper bound on the Einstein Messaging Insights dashboard is the anticipated maximum performance that Einstein calculates for the variable that’s measured. The upper bound is set at 95% confidence interval above the average performance of the variable for a send of this size.
- The lower bound is the anticipated minimum performance of the variable. The lower bound is set at a 95% confidence interval below the average performance of the variable for a send of this size.
- When multiple insights are found for a single journey or batch send, a number appears next to the insight’s title. To view each insight, click the insight’s title.