Initial Daily Campaign Agent release

2026-09-16 21:00:13 +08:00
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+# Learning-period and stable-period ranking
+
+Apply this two-pool method in every daily brief. The purpose is to prevent fresh tests
+from being judged by mature-entity standards while still pruning obvious failures
+quickly.
+
+## 1. Define age and comparable peers
+
+Use confirmed launch/effective dates when available. Otherwise infer launch from the
+first eligible delivery date and label it as inferred.
+
+- Use calendar age since confirmed launch to detect zero-delivery problems.
+- Use delivered days and KPI-mature cohort days to judge performance.
+- A lagged KPI may have fewer mature cohorts than the entity's calendar age; never
+  count immature values as failures.
+- A major reset to creative, targeting, bid, word pack, or structure may re-enter the
+  affected entity into a learning cohort when it materially changes traffic.
+
+Rank peers only within a comparable scope: same entity level, objective/KPI contract,
+currency, attribution regime, and sufficiently similar launch cohort. Rank sibling Ads
+launched together within their parent before comparing them portfolio-wide.
+
+## 2. Rule one — learning-period pool
+
+Treat a new or materially reset Ad as learning-period through the day-7 checkpoint
+unless the operator configures another window.
+
+### Day 3: early selection
+
+Rank simultaneous tests by this ordered evidence, without inventing a composite score:
+
+1. no hard-guardrail breach;
+2. primary KPI result on mature data;
+3. number of confirmed KPIs meeting target;
+4. distance from target and direction of trend;
+5. mature sample and result concentration;
+6. delivery/budget fill and spend impact.
+
+Actions:
+
+- Confirmed launch with zero spend through three calendar days: label `无投放学习失败`;
+  inspect review/status/bid/audience/data issues and recommend pause/rebuild if no
+  correctable delivery block exists.
+- Spend exists, every mature KPI fails, and sample is adequate: rank last and recommend
+  pause or reduction at day 3. If sample is inadequate, state the exact day-5 sample or
+  spend stop condition rather than treating missing outcomes as proof.
+- Some KPIs meet target and delivery/budget is filling: keep stable through day 5–7;
+  specify which KPI must mature and what failure would stop the test.
+- A peer clearly leads on mature KPIs: label `学习期扩量素材候选`, but do not call it a
+  durable winner yet.
+
+### Day 5: confirmation
+
+- Eliminate persistent bottom-ranked peers when mature evidence and sample support it.
+- Continue mixed but improving or partially compliant entities to day 7 with variables
+  fixed.
+- Promote consistent leaders to a bounded scale-test candidate only when downstream
+  guardrails are mature enough; otherwise keep the candidate label.
+
+### Day 7: graduate or stop
+
+- Graduate to the stable pool when the entity has adequate mature sample and an
+  interpretable run.
+- Mark as a scale candidate when multi-day KPI support, downstream guardrails, and
+  headroom are credible.
+- Pause/reduce or redesign persistent failures. Do not extend `learning` indefinitely
+  to avoid a decision.
+
+At each checkpoint, show rank movement where earlier checkpoints are available.
+
+## 3. Rule two — stable-period pool
+
+Classify entities that graduated from learning or have an established run into one of
+four tiers:
+
+### S-优质
+
+Recent 7D exceeds the confirmed KPI targets with multi-day stability, adequate sample,
+and no severe concentration or recent deterioration. Rank the strongest durable Ads
+first.
+
+### A-稳定
+
+The confirmed KPIs meet target with adequate sample and acceptable multi-day
+consistency. Protect or consider bounded scaling subject to creative age and headroom.
+
+### B-波动待优化
+
+Results fluctuate, only some KPIs meet target, or performance hovers near thresholds,
+but there is still a specific optimization or controlled-retest path. Keep, cap,
+reduce, or test one bounded improvement hypothesis with an exit condition.
+
+### C-劣质
+
+The primary KPI or multiple core KPIs seriously or persistently fail on mature data
+with meaningful exposure, or performance sharply deteriorates without credible
+recovery. Treat these as risk Ads and rank by avoidable loss and confidence for
+pause/reduction review.
+
+Within each tier use the same ordered evidence as the learning pool, then use spend
+impact to prioritize operator attention. Every stable-pool row must include a concrete
+`决定` column.
+
+## 4. Historical winner deterioration and new-material alert
+
+Flag a creative/material alert when an established Ad has a credible strong historical
+control but recent mature performance deteriorates materially and persistently. Show:
+
+- total run age and historically strong window;
+- exact recent 7D versus prior 7D or pre-change evidence;
+- which funnel stage worsened;
+- whether spend, budget, targeting, placement, or audience mix changed;
+- fatigue as a hypothesis only when frequency/CPM/CTR/CVR or creative-age evidence
+  supports it.
+
+Recommend preparing or testing new material when the decline is not explained by data
+lag or an easily reversible traffic change. Protect any still-performing sibling Ads.
+
+## 5. Ranking output invariants
+
+- Show an ordinal rank and the decisive reason; do not present a fake precise score.
+- Rank Ads only; do not output Campaign or Ad Group leaderboards.
+- Show KPI pass count only alongside the primary KPI and hard guardrails; KPI counts
+  alone do not determine quality.
+- State whether budget fill uses configured budget or a delivery proxy.
+- Recompute rank when mature cohorts arrive; do not retroactively treat immature zeros
+  as valid evidence.