Class ProductAnalyticsApi

Compute a funnel over an ordered sequence of Product Analytics events. Returns the per-step conversion counts, conversion rates, and elapsed times, optionally segmented by group-by facets.

Return the individual sessions that reached, or dropped off at, a given step of the journey. Each row contains the identity join key, the event timestamp, and the columns requested in entity_columns.

Compute scalar results for a journey query, such as the conversion count, the conversion rate, or the time to convert, optionally segmented by group-by facets.

Compute timeseries results for a journey query. Returns one series per group-by combination, bucketed by the requested interval.

List the individual event records matching an analytics query. Use columns to choose the attributes returned on each row, sort to order the rows, and limit to cap how many are returned.

Compute a retention grid, showing how much of each cohort came back over each subsequent period. Rows are cohorts, columns are return periods, and each cell holds the count and rate of entities that returned.

List the individual users or accounts counted in one cell of the retention grid. Set computation_scope to the cohort and return period you want to examine.

Compute retention as a single value per group, suitable for a query value or top list widget.

Compute retention as a series of values over time, using the same query definition as the retention grid.

Compute a Sankey diagram of how sessions flow between the values of two facets, showing where users continue and where they drop off at each step.

Compute scalar analytics results for Product Analytics data. Returns aggregated values (counts, averages, percentiles) optionally grouped by facets.

Compute timeseries analytics results for Product Analytics data. Returns time-bucketed values for charts and trend analysis. The compute.interval field (milliseconds) is required for time bucketing.

Send server-side events to Product Analytics. Server-side events are retained for 15 months.

Server-Side events in Product Analytics are helpful for tracking events that occur on the server, as opposed to client-side events, which are captured by Real User Monitoring (RUM) SDKs. This allows for a more comprehensive view of the user journey by including actions that happen on the server. Typical examples could be checkout.completed or payment.processed.

Ingested server-side events are integrated into Product Analytics to allow users to select and filter these events in the event picker, similar to how views or actions are handled.

Requirements:

• At least one of usr, account, or session must be provided with a valid ID.
• The application.id must reference a Product Analytics-enabled application.

Custom Attributes: Any additional fields in the payload are flattened and searchable as facets. For example, a payload with {"customer": {"tier": "premium"}} is searchable with the syntax @customer.tier:premium in Datadog.

The status codes answered by the HTTP API are:

• 202: Accepted: The request has been accepted for processing
• 400: Bad request (likely an issue in the payload formatting)
• 401: Unauthorized (likely a missing API Key)
• 403: Permission issue (likely using an invalid API Key)
• 408: Request Timeout, request should be retried after some time
• 413: Payload too large (batch is above 5MB uncompressed)
• 429: Too Many Requests, request should be retried after some time
• 500: Internal Server Error, the server encountered an unexpected condition that prevented it from fulfilling the request, request should be retried after some time
• 503: Service Unavailable, the server is not ready to handle the request probably because it is overloaded, request should be retried after some time