Journey Analytics
Score CRM provides detailed analytics for every journey, giving you visibility into how customers flow through your automation workflows.
Journey Overview Metrics
The journey detail page shows high-level metrics:
| Metric | Description |
|---|---|
| Total Enrolled | Customers who have entered the journey |
| Currently Active | Customers currently progressing through steps |
| Completed | Customers who reached an exit step |
| Exited Early | Customers who left due to exit rules (unsubscribe, bounce, goal) |
Step-Level Analytics
Each step in the journey displays its own metrics:
Action Steps (Send Email, Update Field, etc.)
| Metric | Description |
|---|---|
| Processed | Number of customers who reached this step |
| Successful | Number of successful executions |
| Failed | Number of failures (e.g., email send error) |
Send Email Steps (Additional Metrics)
| Metric | Description |
|---|---|
| Sent | Emails dispatched |
| Delivered | Emails confirmed delivered |
| Opened | Unique opens |
| Clicked | Unique clicks |
| Bounced | Failed deliveries |
| Open Rate | Opens / Sent |
| Click Rate | Clicks / Sent |
Condition Steps
| Metric | Description |
|---|---|
| Evaluated | Number of customers who reached this condition |
| Yes Path | Customers who met the condition |
| No Path | Customers who did not meet the condition |
| Yes % | Percentage taking the Yes path |
Delay Steps
| Metric | Description |
|---|---|
| Waiting | Customers currently in the delay period |
| Completed | Customers who finished the delay and moved on |
Analyzing Journey Performance
Funnel View
Look at the step-by-step progression to identify drop-off points:
- How many customers entered?
- What percentage opened the first email?
- How many reached the second email?
- Where do customers drop off?
Conversion Tracking
If you've set a journey goal:
- Goal Conversion Rate = Customers who achieved the goal / Total enrolled
- Compare this across journey versions to measure improvements
Engagement Patterns
Review email step metrics to understand:
- Which emails have the highest open/click rates
- Whether engagement drops off over time
- If certain condition branches perform better than others
Using Analytics to Improve
| Finding | Action |
|---|---|
| Low open rate on email step | Revise subject line or send time |
| High drop-off at a condition | Simplify the condition or adjust the criteria |
| Most customers taking "No" path | Re-evaluate the condition logic |
| Long delay causing disengagement | Shorten the delay period |
| High bounce rate on email step | Check your list quality |
Best Practices
- Monitor new journeys closely: Check analytics daily for the first week after publishing
- Compare versions: When you publish a new version, compare its metrics to the previous version
- Watch for bottlenecks: Steps with many waiting customers may indicate a processing issue
- Track goal completion: This is the ultimate measure of journey effectiveness
- Review regularly: Set a recurring schedule to review journey performance and make adjustments