---
name: build-audience-layers
description: "Choose clear groups for an ad test. Keep the goal, cost and limits easy to check."
category: Dollar a Day Campaigns
stage: Promote
definitive_article: /dad
status: complete
---

# Build audience layers

Your ad needs to reach people who may need your help. This guide helps you choose a few clear groups to test. Start with the place you serve and the problem your post solves.

**The path:** Real buyer need → allowed groups → clear test rows → budget plan.

**Use this when:** Proven content and a goal are ready, and the campaign needs a testable audience plan.

## Inputs
- The actual service area or market, offer, buyer problem and campaign goal.
- Read access to the current platform’s available audience settings, estimates and policy/category requirements.
- Approved first-party audience sources, if used, with the right to use them for advertising; the creative shortlist and total test budget.

## First-run prompt

> Build a small audience plan for this goal and these posts. Name the reason for each group, actual supported settings, size/eligibility evidence and one variable to compare. Distinguish strict controls from suggestions. Do not upload lists, create audiences or launch ads beyond the supplied scope.

## Steps
1. Write the audience in plain terms: who has this need, where the business can serve them, and why this post helps. Begin with actual customer evidence, not a guessed age band such as all homeowners aged 30–65.
2. Read the platform’s current category restrictions for the actual offer. Use supported service-area controls; do not add protected-trait exclusions or work around restrictions on housing, jobs, credit or other restricted ads.
3. Make a broad eligible group inside the real market as one possible baseline. Add only distinct, relevant interest or behavior groups that the account actually offers. Do not force three to five groups if the budget or evidence supports fewer.
4. For warm groups, list the permitted source, time window and current status: website visitors, eligible video viewers or platform engagers. A created audience is not proof it has enough matched people to deliver.
5. Use customer-list or look-alike audiences only when source rights, platform terms and current eligibility are satisfied. Do not scrape or upload private contacts merely because an address is available.
6. Record each setting as a required control, an optional suggestion or unavailable. If an automated audience mode can expand beyond a suggestion, do not label the resulting row an exact interest-only test.
7. Build a table with test ID, audience definition, exclusions actually supported, creative ID, goal, budget and review date. Change one planned variable for a useful comparison, while noting overlap and non-random delivery.
8. Pass the table to the budget task before launch. Keep audience-size estimates dated; they are not guaranteed people reached and cannot be turned into a money budget using an undefined percentage formula.

## Definition of done (QA checklist)

- [ ] Each group has a source-backed reason tied to the offer and service area.
- [ ] Settings reflect actual availability and distinguish controls from suggestions.
- [ ] Warm/list groups have recorded rights and eligibility; missing size is unknown.
- [ ] The table names one comparison variable and overlap limits.
- [ ] The combined budget is checked before any groups are activated.

## Example(s)

**Fictional teaching example:** A repair shop serves one town. Its seat-fix video has earned organic shares. The plan has A: the town with no extra interest suggestion, and B: the same town with an available cycling-interest suggestion. Both use the same post. If the interface can expand B, the report calls it an audience-suggestion test, not delivery only to cyclists. A third row for prior site visitors stays pending because the audience is too small. No emails are uploaded to fill the gap.

## Handoff and Content Factory context

Send the reviewed table to [set 1 day budget per ad set](https://local-service-spotlight.github.io/task-library/?task=set-1-day-budget-per-ad-set#task-set-1-day-budget-per-ad-set). The campaign owner resolves audience-source or service-area gaps before the relevant test is funded.

This task is in Promote within the [Content Factory](https://blitzmetrics.com/content-factory/). Produce gathers real source material; Process makes useful assets; Post places and checks them; Promote distributes suitable work within its own scope. Use the proof and checked posts from earlier stages; a Promote task does not automatically redo all four stages. Use the actual next step above; catalog neighbors are not prerequisites.

## When this runs

Build once for a test plan, then revise when the offer, service area, audience rights or platform options change. Review existing groups as part of the campaign’s agreed check; do not create a separate schedule by default.

## First-run setup and continuity

Open the supplied task file and its linked source. Verify the project’s real inputs, account, access and output folder before work. This Markdown file is a guide; it does not install an app, connect an account, supply a subscription or create a schedule. Carry out work already authorized; do not ask for the same approval again. Keep any unsupplied destination or new action outside that scope clearly pending.

Save source IDs, versions, decisions, checked outputs and next owner in the project tracker. Before a retry, check the saved state and other workers’ changes. A model name does not guarantee memory or a running timer. Repeated work needs an actual configured trigger and durable state; one-off work can be started by the prompt above.

Keep agent media muted with volume zero before playback. If mute cannot be verified, use captions, metadata or still frames. State the limit: silent visual checks do not prove spoken-word accuracy or audio quality. Do not start sound through the user’s speakers unless explicitly asked.

## Write up the real run

For every actual attempt, [write its meta article](https://blitzmetrics.com/meta-article-prompt/) with this recipe and revision, trigger, steps performed, output evidence, measured result, gaps and next owner. Failed, blocked and partial attempts also get a written record. A draft can satisfy writing; publishing it follows the existing job scope.

Keep one stable execution ID across retries and edits. A separately scoped child task may have its own ID linked to its parent. Writing the parent’s meta record is part of that run, not an endless new chain. The [recipe and meta-article guide](https://localservicespotlight.com/meta-articles/) explains this distinction. Teaching examples are not real executions and must not enter the run count.


<!-- factory-layer:start -->

## Factory chain (do not treat this as isolated)

- **Phase:** Promote
- **Importance:** 5/5 `●●●●●` — frequency 4, revenue 5, gating 4 (runs every factory cycle or weekly; ads/revenue path; gates a phase)
- **Suggested previous station:** —
- **Suggested next station:** —
These stations are generated neighbors, not verified prerequisites or handoffs. Follow the task’s actual Inputs and Handoff sections.
- **Handoff:** Organic metrics CSV (or Ads Manager export), pixel ID, creative filenames, kill/scale log. Next week's ranking starts from this file.

## Model routing (same factory, any engine)

- **This task's lane:** `computer` — Logged-in UI (Meta Ads Manager, Descript, GSC, wp-admin when REST is blocked). Requires a supported browser tool and the right account access.
- **Single-engine path:** Use the capable AI app you already have. Check its required tools and access before starting. Pass the actual result and proof to the next task.
- **Optional multi-engine:** A tested local model may draft; a stronger model may review facts and voice. Use supported tools for approved actions. Pick models from observed quality and cost; a model name does not prove it can run this task.
- **Never** store the working state in one vendor's memory. Files in the Content Library are the bridge.

<!-- factory-layer:end -->
## Definitive article & links

- Maintained method: https://blitzmetrics.com/dollar-a-day/
- Source mapping needs reconciliation: the preserved `definitive_article: /dad` points to the coaching program. The method page above is `/dollar-a-day/`; this record does not certify the coaching page as a task recipe.
- Exact task: [Build audience layers](https://local-service-spotlight.github.io/task-library/?task=build-audience-layers#task-build-audience-layers)
- Writing standard: [Article Guidelines](https://localservicespotlight.com/article-guidelines/)
- [Dollar-a-Day method](https://blitzmetrics.com/dollar-a-day/)
- [Goals, Content, and Targeting](https://blitzmetrics.com/gct-business-strategy/)
- [Meta Advantage+ audience help](https://www.facebook.com/business/ads/meta-advantage-plus/audience)

## Review and evidence still needed

The source contributor status is preserved. It is not certification of this draft or proof of account access, completed work or a live outcome. The worked example teaches the method and is explicitly fictional.
- Meta’s current public audience page was not readable in this check; execution must inspect the supported settings without bypassing access limits.
- No actual customer list, eligible audience or campaign permission is supplied.