> For the complete documentation index, see [llms.txt](https://docs.hackle.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.hackle.io/en/ab-test/data-analysis/analyze-ab-funnel-data.md).

# Funnel

Once the A/B Test is correctly implemented and traffic is allocated so that users are exposed to the A/B Test, you can view the test results within 1 hour.

After that, results are updated approximately every 1 hour, and you can view data from the A/B Test start date up to a maximum of 30 days.

### Analyzing Funnel Results

![2408](/files/vQdzrv0y7Z3IQXIK5Mqw)

1. **Step**: You can view the step name, configured event, and filter information.\
   Hovering over a step shows more detailed information.
2. **Data Table**: A table showing conversion rate, user count, and improvement rate vs. Group A by step and by group.
   1. **Conversion Rate**: The proportion of users in Step 0 of the test group who triggered the event at each step.
   2. **User Count**: The number of users (Unique Users) who triggered the event at each step.
   3. **Improvement Rate vs. Group A**: The relative difference between Group A's user conversion rate and that test group's user conversion rate.\
      In particular, when the p-value is less than 0.05, it is considered statistically significant and displayed in green.
3. **Graph**: A line graph showing the conversion rate per step. Each test group is represented as a separate line. Hovering over the graph shows detailed information for that step.
   1. **Conversion Rate from Step 0**: The proportion of users in Step 0 of the test group who triggered the event at each step.
   2. **Conversion Rate from Previous Step**: The proportion of users in the immediately preceding step of the test group who triggered the event at each step.
   3. **Improvement Rate vs. Group A**: The relative difference between Group A's user conversion rate and that test group's user conversion rate.
   4. **p-value**: A value that expresses the reliability of A/B Test results. A lower p-value indicates higher reliability.\
      In particular, when less than 0.05, it is considered statistically significant and a Significant badge is displayed.


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