---
title: Meta Campaign Audit — Advantage Plus Audiences
type: article
created: '2026-04-05'
updated: '2026-04-05'
source_docs:
- raw/2025-10-21-weekly-call-w-sebastian-95649629.md
tags:
- meta-ads
- audit
- didion
- advantage-plus
- ai-tooling
layer: 2
client_source: Didion Milling
industry_context: food-beverage
transferable: false
---

# Meta Campaign Audit — Advantage Plus Audiences

## Overview

During a weekly call on October 21, 2025, Sebastian flagged that Didion's Meta contact had received an email from Meta claiming they were **missing 15% of opportunity** by not enabling Advantage Plus audiences. This prompted an informal audit of Didion's active Meta campaigns.

Related client: [[wiki/clients/current/didion/_index]]

## Trigger

Meta sent Didion a recommendation email suggesting Advantage Plus audience targeting would unlock additional reach. Sebastian's read on this: it's primarily a mechanism for Meta to serve ads in lower-quality placements and generate cheaper (but less valuable) clicks — not necessarily a genuine performance gap.

> "That's just a way for Meta to show your ad in placements you don't want to be at so they can get some more cheap clicks off you." — Sebastian

## Findings

- **Current cost per submit is performing well.** No immediate red flags in the active campaigns.
- The campaigns flagged in the audit included employment-focused website submit campaigns (not standard lead gen).
- No action was taken to enable Advantage Plus audiences at the time of review.

## AI-Assisted Analysis

As part of the audit, Sebastian exported campaign data from Meta Ads Manager and uploaded it to ChatGPT for an AI-driven analysis. Key outputs from that session:

- Traffic is driving efficiently, but **conversion to application has room to grow**
- Suggestions included audience refinement and shifting spend toward weekdays
- Mark noted the weekday targeting suggestion may not apply well to employment campaigns, since job seekers search around the clock

This was a live demonstration of a broader workflow practice: feeding raw ad data to AI as a first-pass analysis step before drawing manual conclusions. See [[wiki/knowledge/ai-tooling/ai-first-campaign-analysis]] for the general pattern.

## Account Context

- **Client:** Didion (Didion Milling — didion.com)
- **Campaign type:** Employment / recruitment (website submits)
- **Audit requested by:** Melissa
- **Audited by:** Sebastian

## Related

- [[wiki/clients/current/didion/_index]]
- [[wiki/knowledge/ai-tooling/proposal-workflow-claude-gamma]]
- [[wiki/meetings/2025-10-21-weekly-call-sebastian]]