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Campaign performance diagnosis for budget changes

Review weekly campaign data, find likely performance causes, and produce ranked changes and budget moves for performance marketing leads.

4 min read

Weekly optimisation goes wrong when the team jumps from a poor headline metric to a budget cut. These prompts give you a repeatable route from the export files to a recorded spend decision. They are for performance marketing leads who own the weekly review, but need channel, creative and analytics work to line up.

Use the prompts in order when the data is messy. If your reporting is already reconciled, start with the diagnosis and return to the audit only when something does not add up.

Key point

Start with the numbers, not the narrative

A budget decision is only as sound as the conversion, spend and comparison data behind it.

1. Check whether the weekly pack can support a decision

Paste the campaign export, conversion data, delivery notes and planned budget into Audit the weekly data pack. Include both the current period and a comparable period. A seven-day export compared with a partial week, for example, can create a false decline before you have considered any campaign change.

The prompt asks for reconciliation rather than a verdict. That matters where platform conversions, analytics events and CRM outcomes differ. It also asks whether the result is safe for a directional move, a limited test, or no move at all.

Do not fill gaps with estimates just to get to a recommendation. Ask the analytics owner for the missing event count, the CRM join, or the dated change log. Product behaviour and available features can vary, so check the current xAI documentation if you need to confirm how your workspace handles uploaded material.

Check

A useful audit names the missing field

You should see the exact metric or comparison that is absent, why it matters, and the next person or report to check.

2. Separate symptoms from likely causes

Run Diagnose campaign underperformance once the audit says the comparison is usable. Give it the campaign brief as well as the results. A higher CPA means something different for an acquisition campaign with a new offer than for a mature retargeting campaign with unchanged settings.

Keep the diagnosis at the level where you can act. If the export shows that conversion rate fell only on mobile landing pages after a page release, that is more useful than “the funnel is weak”. If spend rose but delivery notes show an audience expansion on the same date, retain that as a hypothesis, not a proven cause.

Read the evidence against or missing column carefully. It is the protection against a confident story built from a single metric. A weak CTR, for instance, can point to creative fatigue, but it can also be caused by a placement or audience mix change.

3. Locate the break between ad and outcome

Use Find creative and funnel breaks when ad engagement and downstream outcomes disagree. It works best with consistent creative IDs across the ad report, page analytics and CRM export. Include the ad copy and visual description, not only the creative label. The replacement angle needs to relate to the message actually shown.

The prompt produces actions for each creative: keep, reduce, pause or test a variation. Treat pause as an operational instruction only when its evidence is strong enough and the budget decision permits it. Where a creative has low click-through rate but high-quality leads, the quality outcome should carry more weight than the click metric.

Watch out

Do not optimise to the easiest metric

A cheaper click is not a better campaign if qualified outcomes, purchases or conversion value deteriorate.

4. Make one accountable budget decision

Paste the audited results and diagnosis into Make the budget reallocation decision. Define the total available budget and every constraint before you paste the rows. This prevents a recommendation that increases promising campaigns but silently exceeds the weekly cap.

The output is a change log, not a vague suggestion to “shift budget to winners”. Each row has a current amount, proposed amount, guardrail, owner and reversal trigger. Review the budget accounting section before sending it on. The proposed total must equal the money you can actually allocate, unless the log explicitly records unallocated spend.

Expected impact is deliberately qualitative. The evidence may support a high-confidence reduction in an underperforming unit without supporting a precise forecast of the resulting conversions. Keep those two things separate.

5. Leave a record that can be checked next week

Run Write the weekly optimisation record after the decision is approved. Use the record as the source of truth for channel edits, creative production, page changes and measurement fixes. The rollback condition is important. It tells the operator when a change should be reversed rather than debated after performance has already worsened.

Check

The record is ready when every material change has a measure

Each budget or creative action needs an owner, due date, success measure, guardrail and a stated reversal action.

How to spot a bad answer

Treat an answer as unreliable if it does any of the following:

  • States that one change caused a result when several changes happened in the same period.
  • Treats unavailable CRM quality data as if it confirmed lead quality.
  • Recommends moving spend while leaving the total budget unreconciled.
  • Calls a creative a winner from clicks alone despite downstream conversion data.
  • Uses a target, benchmark or external market explanation that you did not supply.
  • Hides conflicting figures rather than naming the source of each one.

Correct the input first, then rerun only the affected prompt. If the issue is an unresolved tracking conflict or an unjoinable dataset, stop the reallocation. Hold budget where practical, run a limited controlled test where necessary, and assign the data fix in the weekly optimisation record.

Copy-ready prompts

5 prompts. Open one to read it, or take the whole pack.

1Audit the weekly data packUse this before diagnosing a result or moving budget. It identifies missing fields, broken comparisons and tracking issues that could make a sensible-looking…
Audit this weekly campaign performance data pack before any optimisation decision.

**Reporting period:** [start date to end date]
**Comparison period:** [start date to end date]
**Business objective:** [for example: qualified leads, purchases, trials]
**Primary conversion:** [event name and attribution rule]
**Target or guardrail:** [CPA, ROAS, volume, revenue, lead quality, or other]

**Campaign results export:**
[paste campaign, ad set or ad group data with spend, impressions, reach, frequency, clicks, CTR, CPC, conversions, conversion rate, CPA, conversion value, ROAS and pacing]

**Conversion and CRM data:**
[paste event counts, deduplicated conversions, qualified leads, sales, revenue, refund or cancellation data, and offline conversion match data if available]

**Creative and delivery notes:**
[paste new ads, paused ads, audience changes, bid or optimisation changes, landing-page releases, tracking changes, approval delays and known outages]

**Budget plan:**
[paste planned daily budgets, actual spend, campaign caps and any spend constraints]

Return exactly these sections:
1. `Data coverage`, a table with columns `field or comparison`, `available?`, `risk if missing or unreliable`, `what to obtain`.
2. `Calculation checks`, a table that recomputes or reconciles spend, conversion totals, CPA, conversion rate and ROAS where the supplied data permits it. Show the formula used.
3. `Comparison validity`, a bullet list covering period length, weekday mix, attribution-window changes, learning or delivery disruption, audience overlap, and major external events only where evidence is supplied.
4. `Decision status`, choose one: `safe for directional decision`, `safe only for a limited test`, or `do not reallocate yet`. Give no more than five reasons.
5. `Minimum follow-up`, a ranked list of the missing fields or checks that would change the decision most.

Do not infer missing values. If figures conflict, name both figures, identify the source documents and mark the conflict `unresolved`. Treat reported correlations as observations, not causes. Do not recommend a budget move in this response.
2Diagnose campaign underperformanceUse this after the data audit when a campaign, ad set or market is below its agreed target. It separates weak evidence from plausible causes.
Diagnose likely causes of underperformance for this paid campaign. Use only the evidence supplied and distinguish a measured result from a hypothesis.

**Campaign brief:**
[paste objective, offer, target customer, market, channel, optimisation event, target CPA or ROAS, and constraints]

**Current and comparison-period results:**
[paste results by campaign, ad set or ad group, including spend, impressions, reach, frequency, clicks, CTR, CPC, landing-page views, conversions, conversion rate, CPA, conversion value, ROAS and pacing]

**Audience and delivery settings:**
[paste targeting, exclusions, placements, geography, device, bidding, optimisation event, attribution setting and changes made during either period]

**Creative notes and ad-level results:**
[paste creative IDs, format, message, offer, hook, fatigue notes, approvals, ad-level delivery and outcome metrics]

**Landing-page and conversion notes:**
[paste page changes, page speed or error observations, form changes, event changes, CRM lead quality and sales feedback]

Return:
1. A `Performance summary` table with columns `metric`, `current`, `comparison`, `change`, `where the change occurs`, `interpretation`.
2. A `Likely causes` table ranked from strongest to weakest evidence. Use columns `rank`, `hypothesis`, `evidence for`, `evidence against or missing`, `affected segment`, `confidence`, `next check`.
3. A `Cause map` with one bullet each for demand or auction conditions, audience and delivery, creative, landing page, conversion tracking, and sales or lead quality. Write `no evidence supplied` where appropriate.
4. `What not to conclude`, listing causal claims that the data cannot support.

Use `high`, `medium` or `low` confidence only. If several explanations fit the same result, retain them as competing hypotheses. Do not fabricate benchmarks, market conditions or platform behaviour.
3Find creative and funnel breaksUse this where clicks, landing-page visits, conversions or lead quality have moved in different directions.
Review this campaign's creative-to-conversion journey and identify the most likely break points.

**Campaign and audience brief:**
[paste objective, audience, offer, channel, market and primary conversion]

**Creative inventory and results:**
[paste each creative ID, format, copy, visual description, call to action, launch date, spend, impressions, frequency, CTR, CPC, landing-page views, conversions, CPA and conversion value]

**Landing-page evidence:**
[paste page URL labels or page names, headline, offer, form or checkout steps, page changes, analytics by device, landing-page views, form starts, form completions, purchases or leads, and known technical issues]

**Post-conversion quality:**
[paste qualified lead rate, sales accepted rate, purchase completion, revenue, refund or cancellation data by campaign or creative where available]

**Change history:**
[paste changes to creative, audience, landing page, tracking, offer and sales follow-up, with dates]

Return:
1. A `Journey diagnostic` table with rows `ad delivery`, `ad engagement`, `landing-page arrival`, `form or checkout start`, `conversion`, `qualified outcome`. Include `signal`, `likely issue`, `evidence`, `confidence` and `recommended test`.
2. A `Creative decisions` table with columns `creative ID`, `action` (`keep`, `reduce`, `pause`, `test variation`), `reason`, `replacement angle or element`, `risk`.
3. Up to five test briefs. Each must state `hypothesis`, `change`, `audience or traffic split`, `primary measure`, `guardrail`, `decision rule` and `what would invalidate the test`.
4. A short `Tracking caveats` section.

Do not declare a creative winner from CTR alone when downstream data is available. If identifiers cannot be joined across ad, landing-page and CRM data, state exactly which join is missing and limit the conclusion.
4Make the budget reallocation decisionUse this when you need a documented weekly spend move, not just a diagnosis. Run it after reviewing data quality and likely causes.
Make a weekly budget reallocation recommendation from this campaign evidence. The aim is to improve the stated business outcome while protecting volume and measurement quality.

**Decision period:** [dates]
**Next budget period:** [dates]
**Total available budget:** [amount and currency]
**Business objective and primary conversion:** [state both]
**Target and guardrails:** [CPA or ROAS target, minimum volume, lead quality requirement, pacing limits, contractual or brand constraints]

**Current budget and performance by allocatable unit:**
[paste one row per campaign, ad set, ad group, market or creative group with current budget, spend, conversions, CPA, conversion value, ROAS, qualified outcomes, delivery status, and data completeness]

**Diagnosis evidence:**
[paste ranked likely causes, confidence, creative findings, funnel findings and tracking caveats]

**Operational constraints:**
[paste minimum spends, launch commitments, audience exclusions, approval lead times, experiment requirements and any units that cannot be changed]

Return exactly:
1. `Decision`, one of `reallocate now`, `reallocate only through a controlled test`, or `hold budget pending evidence`.
2. A `Budget change log` table with columns `priority`, `allocatable unit`, `current budget`, `proposed budget`, `change`, `action`, `expected impact`, `confidence`, `evidence`, `guardrail`, `owner`.
3. `Budget accounting`, showing current total, proposed total and any unallocated amount. Confirm whether the proposed total equals the available budget.
4. `Rationale by move`, with one concise bullet per increase, reduction, pause or hold.
5. `Review triggers`, stating the metric, threshold, review date and reversal action for each material move.

Rank changes by expected impact first, then confidence. Use qualitative expected-impact bands only: `high`, `medium` or `low`. Do not invent projected revenue, conversion volume or efficiency. If the data cannot isolate performance from tracking, seasonality or a recent change, recommend a controlled test or hold rather than a firm reallocation.
5Write the weekly optimisation recordUse this after deciding the changes. It creates the record your team needs to execute, monitor and reverse the decision.
Create a weekly campaign optimisation record from the materials below. It must be suitable for the performance marketing lead, channel operator, creative owner and analytics owner.

**Weekly performance summary:**
[paste audited results and the diagnosis]

**Approved budget decision:**
[paste the budget change log and any constraints]

**Creative and landing-page actions:**
[paste approved pauses, new variants, page changes and test briefs]

**Measurement issues:**
[paste tracking gaps, unresolved data conflicts and validation tasks]

**Owners and review date:**
[paste names or roles, plus the next review date]

Return these sections:
1. `Weekly decision summary`, no more than 120 words. State what changed, why, and what remains uncertain.
2. `Change log`, a table with columns `priority`, `change`, `unit affected`, `owner`, `due date`, `expected impact`, `success measure`, `guardrail`, `rollback condition`, `status`.
3. `Execution checklist`, ordered by the sequence needed to avoid measurement errors. Include budget edits, creative actions, landing-page actions, naming or tracking checks, and stakeholder notification only when supplied.
4. `Monitoring plan`, a table with columns `check date`, `metric`, `expected signal`, `warning signal`, `action if warning appears`.
5. `Open questions`, grouped into `data`, `creative`, `audience`, `funnel` and `operations`.

Keep dates, owners and amounts exactly as supplied. Where any is absent, write `unassigned`, `date not supplied` or `amount not supplied`. Do not convert a hypothesis into a completed fact.

Last checked against xAI’s own pages on 2026-08-21. Grok changes quickly; anything version-specific should be confirmed upstream before you rely on it.

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