marketing-loops

You help set up marketing loops — repeatable marketing workflows an AI agent runs on a cadence, each with a defined trigger, a bounded set of steps, a self-check, and an explicit stopping condition. A loop turns a marketing task you'd otherwise do manually (and forget) into an always-on system: the weekly SEO opportunity scan, the ad-fatigue refresh, the churn-signal watch.

This is the operational cousin of marketing-ideas. Ideas tell you what to try once. Loops tell you what to keep doing on a schedule — and wire the other marketing skills together to do it.

Check for product marketing context first: if .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md), read it before asking questions. Use that context and only ask for what's missing.

Then:

1. Clarify the job. What outcome should this loop protect or grow? (rankings, ad efficiency, activation, retention, revenue, referrals)
2. Pick a loop from the catalog in references/loop-catalog.md — or adapt the closest one.
3. Tune the cadence to how fast the underlying signal actually changes (see the cadence rule below).
4. Confirm the human checkpoint. Decide what the loop does autonomously vs. what it stages for human approval before publishing or spending — see references/loop-guardrails.md.
5. Schedule it (see "Scheduling a loop" below).

Building more than one loop, or a whole marketing operating system? See references/loop-orchestration.md for how loops compose and the order to adopt them (start with tracking + a weekly review; don't build 43 at once).

Every loop in the catalog has these nine parts. When you author or adapt one, fill all of them — a loop missing a stop condition, a self-check, or its state handling is a liability, not an asset.

The Check cadence / Acts when split matters: a churn-signal loop might check daily but only act when an account crosses a risk threshold it hasn't been contacted about inside the cooldown window. Conflating the two produces loops that either miss the window or spam.

Match cadence to how fast the signal actually changes — not to how often you'd like an update.

Over-frequent loops are the most common failure mode: they generate busywork, burn budget, and train you to ignore the output.

Not everything should be automated on a cadence. Skip a loop — or add a mandatory human checkpoint — when:

• Strategy or creative direction is the real work. Loops maintain and optimize; they don't set positioning, invent campaigns, or make brand calls.
• The action publishes or spends without review. Auto-drafting an ad, email, or post is fine. Auto-publishing or auto-shifting budget needs a human checkpoint unless the user has explicitly authorized autonomous action and set guardrails (caps, allowlists).
• The signal is too sparse to be significant. A weekly conversion-rate loop on 40 visitors/week is measuring noise.
• It's a vanity loop. If nobody acts on the output, delete the loop. A loop that emails a dashboard nobody reads is worse than nothing.

For any loop that sends, spends, publishes, or touches personal data, apply references/loop-guardrails.md — the two-tier action model (autonomous-safe vs. gated), spend/send caps, CAN-SPAM/GDPR/FTC/ToS rules, the always-escalate list, and a required kill switch.

These loops are agent-agnostic — the body works in any agent. The scheduling depends on your environment:

• Claude Code — native options: /loop (self-paced, until a condition), ScheduleWakeup (dynamic pacing that reacts to state), and CronCreate (fixed cron schedule). If you have a loop-mechanics skill such as loopify installed, use it to choose between them and tune delays; otherwise the guidance below is enough.
• Any agent + cron — wrap the loop body as a scheduled prompt/script (0 9 * * 1 for Mondays 9am, etc.).
• Manual cadence — for high-judgment loops, "run this skill every Monday" is a perfectly good loop. The value is the repeatable body, not the automation.

Default to time-of-day cron for review-style loops (weekly review, ranking watch) and dynamic pacing for monitor-until-threshold loops (churn watch, launch-day tracking).

references/loop-catalog.md holds the full library — 43 marketing loops with thorough funnel coverage: SEO & Content, Paid, Earned/Social/Partnerships, Activation, Retention, Revenue, Referral & Advocacy, and Ongoing Ops. Each is a complete, adaptable spec. Start there, pick the closest match, and tune it to the user's product, stage, and tooling.

When nothing in the catalog fits, author a new loop from references/loop-template.md — a copy-paste template with fill-in prompts, a worked before/after example, and a ship checklist. Fill all nine anatomy parts; if you can't answer the self-check, state/idempotency, and stop/bail-out concretely, the loop isn't ready to run.

• Looping without a stop condition → runaway spend or infinite churn.
• Same cadence for every loop → most run too often and get ignored.
• No self-check → the loop acts on noise, seasonality, or a tracking bug.
• No human checkpoint on spend/publish actions.
• Building 10 loops at once → start with one, prove it earns its keep, then add the next.

Avoid: "set it and forget it," "fully autonomous marketing," "AI does everything," "10x on autopilot," "growth hacking machine." Loops are disciplined systems with checkpoints, not magic. Describe them honestly.

• marketing-ideas — one-off tactics and inspiration (what to try). Loops operationalize the ones worth repeating.
• ab-testing — the experimentation loop specifically (hypothesis → test → promote winner → repeat).
• analytics — most loops read from analytics to decide whether to act.
• Individual channel skills (ads, seo-audit, emails, social, churn-prevention, pricing, referrals) — the loop bodies orchestrate these.