Meta ads automation and competitor ad monitoring for apps

Ad accounts produce three kinds of routine work: checking, reporting and reacting. Automation takes over the first two and speeds up the third. A person still decides what changes.

• Budget pacing: a check that compares spend so far with the planned curve for the day and flags overspend or underdelivery.
• Anomaly alerts: spend, CPA, CTR or purchase volume moving outside a range, sent to Slack or email with a line of context.
• Kill and scale logic: written thresholds that propose pausing an ad set or raising a budget, with a person approving the action.
• Reporting: daily and weekly reports generated on a schedule from the ad platform API and your payment data.
• Creative operations: tagging, fatigue flags and test logs, with AI-drafted briefs that a person reviews.

Illustrative thresholds, not benchmarks. Your target CPA is $30. A kill rule flags any ad set that has spent twice the target, $60, with no purchase. A pacing rule flags the account when spend by midday exceeds 70% of a $500 daily budget, which is $350 before noon. A scale rule proposes raising a budget by no more than 20% in a day, so $500 becomes at most $600.

The arithmetic: 2 times $30 is $60. 0.70 times $500 is $350. 1.20 times $500 is $600. Real thresholds come from your economics, which is why the audit comes first. Rules built on borrowed benchmarks tend to kill ads that would have paid back.

An agent can read the dashboards, explain an alert and propose an action, such as pausing one ad set or moving $100 to another campaign. Ad platform APIs and connectors such as MCP servers let the agent see the account. Three guardrails apply: read-only access first, spend caps on anything that can write, and a person approving changes. Each action goes into a log.

The monitor watches sources that are public by design. Typical sources are the Meta Ad Library, the Google Ads Transparency Center, TikTok's Commercial Content Library, and app store listings and pricing pages. Coverage differs by source and region: Meta's Ad Library API returns commercial ads only when they reached the EU, and TikTok's library covers the EEA, Switzerland and the UK. The brief states which sources cover your markets. A scheduled job collects what changed, an LLM summarizes it, and a person reads a one-page brief with a suggested test.

• Official APIs first. The Meta Ad Library has an official API whose scope depends on ad type and region, so the design starts from what current documentation allows.
• Platform terms apply. The monitor does not log in as a user, bypass rate limits or paywalls, or collect unpublished data.
• GDPR applies. Libraries can show advertiser and page names. The monitor stores only what the brief needs and does not profile individuals.
• Limits are stated. For commercial ads the Ad Library shows the ads, platforms and run dates. It does not show competitor spend or results, so the brief makes no such claim.
• Hooks and formats only. The brief records what competitors test and leaves out creative, logos and audio.

Channels used: Meta, TikTok, Google Search and UAC, Apple Search Ads, Snapchat and Pinterest. Market intelligence tools used: Sensor Tower and AppMagic. The automation layer adds scheduled scripts, ad platform APIs, workflow tools such as n8n and LLMs for summaries.