Meta Delivery & Audience Review

Review Meta ad-set delivery, audience context, reporting status, and mature outcome trends to identify supported constraints and bounded tests.

Campaign optimizationWorks with exports or live data

When to use it

When Meta ad-set delivery or audience context needs investigation before account changes.

Try asking

“Our Meta ad set delivery is declining. Check whether audience saturation explains it.”

What you get back

A Meta delivery assessment separating actual diagnostics, audience/creative hypotheses, nonadditive reach, and supported next tests.

Fictional example output

Observed Purchase CPA increased from $20 to $40 (+100%). CPM rose from $10 to $12.50 (+25%); link CTR fell from 2.00% to 1.00%. Within-week frequency rose from 2.00 to 4.00, while reach fell from 50,000 to 20,000.

The supplied status changed to Learning limited; its cause is not established by these counts. The creative edit coincides with the change but is not proof that it reset learning or caused the drop. Frequency 4 is not a universal saturation threshold. Weekly reach is nonadditive, so neither 70,000 unique people nor a pooled frequency can be asserted.

Prioritize the actual delivery diagnostics, current event/attribution settings, change history, and matched placement/audience breakdown. Audience expansion and removing exclusions require checking which settings are actual controls in this campaign. Do not switch to an easier event just to clear status or promise a budget increase will resolve it. No targeting, event, or budget change applied.

Fictional data. An illustration of the method, not a customer result.

Where the data comes from

Connected with Orphex Recommended

The skill reads your connected accounts for the right dates. Nothing to export or upload.

Connect free
Input columns 8 required, 2 optional
periodRequired
Matched complete reporting interval
ad_set_idRequired
Stable ad-set scope
delivery_statusRequired
Actual supplied delivery status, not inferred
optimization_eventRequired
Actual optimization event
currencyRequired
ISO currency
spendRequired
Observed spend
impressionsRequired
Observed impressions
reachOptional
Reported unique/estimated reach within this row scope
link_clicksOptional
Named link clicks; not all engagement clicks
resultsRequired
Reported named optimized outcomes
Before you start 2 items
  • Supplied data with the documented task-specific columns, stable scope, and refresh/maturity context
  • Business definitions and constraints relevant to the decision; see the reusable business-context reference

Supply your objectives, conversion definitions, currency, constraints, and approved brand facts once, then reuse the profile across reviews. Leave unknown values explicit.

Open profile source
The method

With an Orphex connection

If an Orphex connector is available, check it before asking for exports. Run capability_search with platform orphex and limit 100; use a read only if that search returns its id, and ask which workspace to use when several are bound. Read controller.catalog then controller.fetch at levels adgroup and audience for dated delivery and outcomes, and insights.read for Meta. Ad-set settings and delivery diagnostics are live reads: run capability_search with platform meta and use ad_set.detail_read and platform_management.opportunities_read only when that search returns them. If playbook.catalog lists the frequency-capping or placement efficiency playbook, run it with playbook.run. Then list guides with skill_catalog (kind guide, topic measurement) and follow a matching one through skill_read; choose by title, never by a stored id.

Source and evaluation v2.1.0 · MIT
View SKILL.md

Orphex Meta Delivery & Audience Review

Review the actual Meta campaign/ad-set delivery context and business outcome. Interpret platform status as a diagnostic signal, not a causal explanation or a reason to change the optimization goal automatically.

With an Orphex connection

If an Orphex connector is available, check it before asking for exports. Run capability_search with platform orphex and limit 100; use a read only if that search returns its id, and ask which workspace to use when several are bound. Read controller.catalog then controller.fetch at levels adgroup and audience for dated delivery and outcomes, and insights.read for Meta. Ad-set settings and delivery diagnostics are live reads: run capability_search with platform meta and use ad_set.detail_read and platform_management.opportunities_read only when that search returns them. If playbook.catalog lists the frequency-capping or placement efficiency playbook, run it with playbook.run. Then list guides with skill_catalog (kind guide, topic measurement) and follow a matching one through skill_read; choose by title, never by a stored id.

If a read is not returned, this connection cannot reach that Orphex data for the workspace: say so, then use the live platform reads it offers or the supplied exports. An absent, refused or empty read is not evidence of zero, none or healthy. Describe each read with capability_describe before run_read, keep date_end no later than yesterday, disclose request adjustments, and name each number's source, workspace and window. This skill's evidence rules still govern any guide, insight or playbook label, and no read authorizes account changes. Ask the user only for what is still missing.

Align evidence

Record account timezone, currency, objective, performance goal, optimization event, attribution setting/date basis, conversion maturity, entity scope, budget owner, actual status/reason, schedule, audience controls/exclusions, placement settings, and material edits. Keep lead, landing-view, link-click, and purchase outcomes distinct. Verify current account/API field definitions and availability before comparing exports; names and supported controls can differ by campaign type.

Calculate outcome CPA, link CTR, CPM, and within-scope frequency only when their exact inputs are supplied. Reach and unique audience measures are nonadditive across ad sets, days, or overlapping audiences. Do not sum reach, average frequency, or infer audience overlap from repeated targeting descriptions. Observed frequency has no universal fatigue threshold and cannot prove saturation or self-competition.

Rank delivery explanations

Separate eligibility/policy or instrumentation problems, supplied learning diagnostics, budget/pacing, bid/cost controls, audience availability, placement mix, creative age/edits, and conversion-path evidence. Do not invent a fixed event-volume requirement or assert that every edit resets learning. Status, event counts, and coincident edits alone do not identify the reason; use the actual diagnostic and current official account documentation. A recent incomplete conversion window can explain apparent deterioration but requires demonstrated lag.

Distinguish optimization suggestions/signals from hard audience constraints for the actual setup. Do not recommend broad expansion, blanket exclusions, switching to an easier goal, or overlapping clone campaigns without a business reason and valid supported controls. Prefer one bounded test tied to the diagnosed constraint with a mature review window and a guardrail.

Deliver observations, supported constraints, unresolved hypotheses, next diagnostic/test, and change scope. Preserve purchase/lead-quality goals and keep all account edits within explicit authorization.

Official references

Portable inputs and examples

State whether the result is complete, partial, or blocked for the requested decision. Link material findings to actual supplied rows/sources and separate observed metrics, hypotheses, and estimates. Lead with a short business conclusion, then evidence, uncertainty, and the next measurable check. A data export or installed skill does not authorize account changes.

View on GitHub Open SKILL.md

How this release was evaluated

See the recorded checks, compared runs, results, and limits for v2.1.0. Example reviews illustrate the method; they do not guarantee account results.

Read the evaluation report