Understanding the Data Sources on DISPL Platform

Key Features: 

Readable Format: The data is slightly rounded for better readability. 

Ideal for high-level insights and quick decisions. 

Perfect for presentations or reporting to stakeholders who don’t require detailed raw data.  

Dashboard specifics: 

Including/Excluding Staff: Data tagged as "staff" is filtered out by default. You can see the whole data with staff or only staff data.Choose the needed perception in Filters. 

Unique Visitor Count: The Total Visitors metric represents the count of unique visitors detected by the sensor on a specific day. 

Contact Count: The Total Contacts metric shows the total number of interactions visitors had with the camera, whether it’s the same individual or different people. 

Read more about the Dashboard and how each graph can be used here: Guide - Audience Analytics data application guide.pdf 

Visitors Tab: 

Shows the total unique visitors detected during the selected period. 

Correlates with the Total Visitors metric on the Dashboard. 

Contacts Tab: 

Displays the total contacts (not unique visitors), representing the number of times visitors interacted with the camera. 

Correlates with the Total Contacts metric on the Dashboard. 

Content Tab: 

Provides data about content shown on your screens, including: 

Who viewed the content. 

How long they engaged with the content. 

Helps you evaluate the effectiveness of displayed content. 

When to Use: 

For offline processing or advanced visualization in external tools. 

When you need to cross-reference visitor counts, engagement, and campaign effectiveness. 

Note on Comparison with Raw Data: 

If you compare Dashboard data with raw data, ensure you exclude IDs tagged as "staff" from the raw data to match the Dashboard metrics. 

Key Features: 

Granular Data Access: Retrieve raw records with extensive metadata like face_quality, demographics, and engagement. 

Pagination Support: Handles large datasets with limit and offset parameters for batch processing. 

Data Filtering: Use filter face_quality to exclude low-value data. 

Ideal for custom integrations with BI tools or systems. 

When you need to automate reporting. 

Example Workflow: 

Use the API query to fetch data (e.g., visitor sessions). A request of this type will return 1,000 sessions within the specified time frame: 

If the total exceeds 1000 records, query the remaining data using the offset parameter: 

Combine the queries into a single dataset for analysis. 

Filter out low-value data such as records with "face_quality": null. 

How API Data Corresponds to Other Sources: 

The Dashboard and raw data exclude records with face_quality marked as null and any tagged as "staff." 

The API provides full access, including dropped records, if needed.