Repeatability
High
The structure is identical each time: ingest CSV, group by platform/ad type/vertical, compute ROI metrics, rank and flag. This is a templated analytical workflow that runs the same way every reporting cycle.
Ambiguity Tolerance
Medium
ROI calculation is well-defined if revenue/cost columns are present, but 'underperforming' and 'strongest returns' need explicit thresholds or benchmarks. Without those, the agent must make defensible assumptions, which is workable but introduces some subjectivity.
Data & Tool Availability
High
The user has a single CSV with ~2,800 rows covering all three platforms — no live API access required. A data agent with Python/pandas or a code interpreter can execute the full analysis from that file alone.
Error Cost
Low
The output is an analytical report, not a budget reallocation action. Humans review the findings before any money moves, so a calculation error is catchable and correctable before it causes real damage.
Human Judgment Required
Low
The core work is aggregation, ratio computation, and ranking — all mechanical. Strategic interpretation of why a segment outperforms belongs to a human, but the agent can surface the what clearly enough to make that conversation productive.