Connecting product events to their search context.
Connect product questions with meaningful measurements.
Where this work fits
Once AI features were in use, a disappointing result could come from several places. A model call, a search result, and a dashboard count each needed different evidence before the team could decide what to fix.
I instrumented recruiting actions such as reviewing a candidate, changing search criteria, and starting a conversation. Keeping search context with those events made the activity more useful for analysis than unrelated counts of clicks.
Understand what the measurement counts
The denominator matters.
Different questions deserve different measures.
40 applications submitted in total.
This total counts submissions. It does not tell us how many people started an application and finished it.
Capture the right context without blocking the user.
The review team needed the result the user actually saw. I worked on carrying that context into the review handoff while keeping a delivery failure from interrupting search. For metrics, I checked what each count represented and kept incomplete periods from distorting comparisons.
The skills behind the work
- TypeScript
- Make data shapes and code boundaries explicit while building product behavior.
- Event design
- Represent an action accurately so another part of the product can respond or measure it.
- Product measurement
- Connect user behavior with a product question rather than count events without context.
Engineers could inspect model failures and timing. Reviewers received search context to investigate, and product reporting used clearer definitions for the activity being measured.