The ContentSherpa Traffic By Prequalification report provides insights into how users interact based on predefined prequalification fields and options. This report breaks down traffic data such as Engaged Sessions, Engaged Visitors, Conversations, Questions, Conversation Saves, Leads, and Repeat Visitors, segmented by each Prequalification Field and its Field Option (e.g., Industries → Banking, Products → Energy).
This allows marketers to analyze which prequalification segments drive higher engagement and conversions, helping in refining targeting strategies.
To access the Traffic By Prequalification report, follow the steps below:
- From the Left Nav Menu, click Reports > ContentSherpa > Traffic By Prequalification.
- The Traffic By Prequalification page is displayed, presenting each Prequalification Field alongside the key performance metrics.
Key Metrics Displayed in the Report:- Prequalification Field - This field is displayed as the Prequalification Statement to the visitor. These are picklist fields created under Setup > Field Management as Asset Custom & Catalog and Lead Custom Field
- Prequalification Field Option - Represents the picklist value selected within that field by the visitor.
- Engaged Sessions - Sessions where users interacted meaningfully with the content.
- Engaged Visitors - Unique users who actively engaged during their visit.
- Conversations - Number of chatbot or experience-based conversations initiated.
- Questions - Total number of questions asked during conversations.
- Conversation Saves - The total number of conversations that were saved.
- Leads - Leads captured from the interactions.
- Repeat Visitors - Visitors who returned after their first visit.
- On the Traffic By Prequalification page, you can search and customize the report table by Date.
- You can filter by the Dimensions available in the drop-down menu. A maximum of three Dimensions can be applied at a time.
- You can filter and apply a sub-filter to refine the data view.
You can read here to learn how to use the report features.
Was this article helpful?
That’s Great!
Thank you for your feedback
Sorry! We couldn't be helpful
Thank you for your feedback
Feedback sent
We appreciate your effort and will try to fix the article