Change response and recovery analysis

Use this reference only when a recent intervention or suspected change point matters: budget/bid scaling, rollback, targeting or word-pack changes, creative replacement, Ad Group restructuring, a sudden deterioration, a new “black horse,” or a request to rescue a previously successful entity.

1. Reconstruct the timeline before assigning cause

Create a compact event timeline from the report and intervention log. Split relevant history into:

Pre-change control: the last sufficiently stable configuration and its mature KPI cohorts.
Transition: delivery dates whose outcomes are immature or mix old and new configuration effects.
Post-change: only cohorts mature enough for each KPI.

Compare like-for-like phases at the lowest trustworthy entity. Show exact dates, spend, sample, KPI results, and configuration when known. Rolling 7D/14D windows remain useful context, but must not blur a sharp phase break.

Timing is not causality. Use language such as 与变更时间一致 until competing explanations are checked. If deterioration began before restructuring, say so: the restructure may have amplified or failed to fix the problem, but is not the sole demonstrated cause.

2. Separate expansion shock from organic deterioration

Call an expansion-related deterioration plausible only when a confirmed budget, bid, reach, allocation, or traffic-mix change precedes the mature decline. Observed spend alone is not budget history.

If budget/delivery increased and downstream quality fell after the change, test an expansion or traffic-mix hypothesis.
If spend stayed broadly stable while acquisition remained efficient but retention, revenue, or another downstream KPI fell, classify it first as downstream quality deterioration. Investigate audience, inventory, placement, cohort concentration, tracking, and mix shifts; do not label it a budget shock.
If acquisition and downstream quality both worsen, keep creative fatigue, targeting saturation, competition, and structural changes in the hypothesis set.

Never invent a causal mechanism from aggregate metrics. State the breakdown needed to confirm it, such as placement, device, audience, search term, keyword/match type, geo, frequency, or auction diagnostics.

3. Decide rollback, containment, or pause

Prefer a controlled rollback/recovery test when all are true:

a dated intervention plausibly precedes the mature deterioration;
a prior configuration is known and operationally restorable;
that prior phase has credible evidence, not merely one good day;
the rollback does not destroy a currently verified child winner or introduce a broader structural risk.

Rollback is not recovery. If the prior configuration also missed current KPI, label the rollback 止损/风险收敛, not 恢复到有效状态. Compare it against both the damaged phase and the current KPI contract.

During the recovery test, hold other controllable variables fixed. Use the operator's configured maturity/sample rule. If none exists, a small run of multiple mature cohorts may serve as a provisional checkpoint, followed by a complete recent-window validation; clearly label this as a default evidence rule, not a universal truth.

Define exits in advance:

Recover: multiple mature cohorts return to target without a guardrail breach;
Continue cautiously: directional improvement exists but sample is insufficient;
Escalate/retest: results remain poor or mixed and a clean hypothesis is testable;
Pause/reduce: persistent mature failure continues with meaningful exposure and no unresolved data issue.

Avoid daily edits during an observation window unless a hard loss, compliance, or tracking guardrail is breached.

4. Validate a new or apparent “black horse”

Early averages can be dominated by one cohort. Separate:

launch/early cohorts;
the standout cohort or event;
subsequent mature cohorts;
immature cohorts, which must not be treated as zeros.

Show how much of the retained outcomes, revenue, or other success measure comes from the best day/segment. One strong cohort or one to two good days supports promising, not durable winner. Require the configured minimum sample and multi-cohort consistency before scale.

When an early winner weakens but has not accumulated persistent failure, prefer hold/protect at a stable test level over immediate scale or pause. Specify the next mature checkpoint and the failure condition.

5. Rescue a restructured Campaign or Ad Group

Do not decide replace everything or abandon the Campaign from its aggregate. Build a comparison across:

the prior clean control structure;
copied/reused groups;
new word packs, audiences, creatives, or match types;
current child winners worth protecting.

Measure whether weakness is broad or concentrated and whether the decline started before or after each structure change. Historical success is context, but reassess it against the current KPI contract; a phase that met acquisition KPI but failed downstream quality is not an all-KPI control.

A clean rescue design should:

preserve one interpretable control;
isolate one material hypothesis per test group;
reduce duplicate/overlapping audiences, keywords, or creatives where evidence supports overlap risk;
protect verified child winners from being reset or drowned by the test;
use mature, predeclared success and stop conditions.

Do not recommend swapping a whole word pack without keyword/search-term and match-type evidence when those are the real levers. Request deeper dimensions only when they can change the decision.

6. Report the change decision

For an explicitly requested named-Ad follow-up, the optional presentation template is:

<Ad名称>近7日专项判断
近7日消耗 | 安装 / 成熟结果 | 主要KPI | 下游KPI | 达标天数
趋势：<量级、KPI和变更前后走势>
结论：<保持、回退、低量观察、制作新变体、暂停或扩量判断>

Populate it only from the current source and confirmed context. This is a follow-up template, not a standard daily-brief section. Never preserve an example Ad name or example metrics as default content.

For each change-related recommendation include:

entity path and stable ID;
declared or inferred change and timestamp;
pre-change, transition, and post-change mature evidence;
observed fact versus causal hypothesis;
action state: rollback/recovery, hold/protect, clean-control retest, pause/reduce, or scale candidate;
variables to hold fixed;
pacing impact, including the spend gap created by rollback/pause;
next mature review point and explicit recover/escalate/exit condition.

Never claim the intervention was executed. This skill remains analysis-only.

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