PRODUCT ANALYTICS
A product manager sees the drop in adoption. An engineer sees the spike in errors. Today those are two tools and a meeting. In Axiom, it is one dataset and one query.
HOW IT WORKS
Product teams track events in one tool. Engineering tracks errors in another. When a feature launch underperforms, the answer requires both. Someone exports CSVs, correlates timestamps, and schedules a meeting. The five-minute question takes a day.
Send product events to the same datasets where your logs, traces, and metrics already live. Query across both with APL. No data warehouse, no ETL pipeline, no separate analytics vendor.
When a metric moves, drill into the system telemetry to understand why. The query builder makes this accessible to teams that do not write APL.
Events flow from your backend over HTTP to your datasets. PII stays in your infrastructure. Query-time redaction handles sensitive fields without stripping them from storage.
WHERE IT FITS
Session replay, heatmaps, and marketing attribution still belong in dedicated tools. But when the question is "why did this feature underperform?" and the answer requires both product events and system telemetry, that investigation happens here.
Send product events alongside your operational telemetry. Query both with APL.