analyst-revenue-analytics

To analyze Braze purchase data for revenue trends, you query time-series endpoints like purchases/revenue_series using parameters such as length, ending_at, and unit. This reveals revenue fluctuations across defined time windows and specific apps.

Evaluating product performance with Braze purchases involves querying the purchases/product_list endpoint. This identifies top-performing items and tail products by analyzing product-level metrics within your specified time windows.

Yes, you can track purchase frequency and quantity by using the purchases/quantity_series endpoint. It allows you to measure purchasing velocity and customer engagement by specifying parameters like app_id and unit across set time periods.

A limitation when retrieving Braze revenue time-series data is the maximum query length of up to 100 days per request. You must segment longer historical analyses into multiple queries using the ending_at parameter.

Yes, Braze revenue analytics supports filtering by specific apps and products using the app_id and product parameters. This allows targeted analysis of transaction data for individual product lines or application environments.