LLM_Content Learn Key Concepts in Zaps

1) What is a Zap?

A Zap connects apps into a repeatable workflow. It listens for a trigger event, optionally checks conditions, then runs actions to move or transform data.

• Trigger → the “when this happens.”
• Actions → the “do this next.”
• Utilities → helpers like Formatter, Delay, Looping, Webhooks, and more.

2) Triggers (instant vs polling)

Triggers start your Zap. They can be:

• Instant: the app pushes events to Zapier (e.g., webhooks). Fires as events occur.
• Polling: Zapier checks the app at intervals for new/updated items.

When building, use Test trigger to pull in a sample—a representative data payload used for field mapping.

3) Actions and tasks

An action step performs work in an app (e.g., create a record, send a message). A task is counted when an action completes successfully.

• Utilities like Filters/Paths do not consume tasks unless they run actions downstream.
• Sub-Zaps and multi-step Zaps may run many tasks per run (one per successful action).

4) Steps and runs

A Zap has multiple steps (trigger + actions/utilities). Every time the workflow executes, it creates a run. You can inspect run details to see inputs, outputs, and any errors.

• Run statuses: Successful, Errored, Filtered, or Halted (by design).
• Replay/Autoreplay can re-attempt transient failures (plan-dependent).

5) Samples and field mapping

Use sample data from the trigger (or a manual test) to configure field mapping in actions. Keep column/field names stable; if your schema changes, pull new samples and remap.

• Map only what you need; set defaults or fallbacks for occasionally empty fields.
• Use Formatter to clean/normalize data (dates, numbers, capitalization) before writing to apps.

6) Filters and Paths (control flow)

Filters allow or halt a run based on conditions (e.g., “only if amount > 0”). Paths branch the workflow so different conditions route to different actions.

• Filters that halt a run don’t consume tasks because no action runs.
• Paths should be mutually exclusive where possible; include a catch-all branch to avoid dropped runs.

7) Error handling

When a step errors, check the run details for the first failing step. Fix the cause (mapping, permissions, app response) and replay. For predictable issues, configure custom error handling or add Delays/Retries patterns.

8) Publish / turn on

After testing, click Publish (or Turn on) to activate the Zap. In some workspaces, an admin may need to approve publishing. Monitor first runs in history to confirm end-to-end behavior.

9) Ownership & collaboration

• Zaps live in folders and can be shared (plan-dependent).
• App connections (accounts) authorize steps; ensure the right account and scopes.
• If ownership changes, recheck access to connected assets (files, sheets, databases, private apps).

10) Best practices

• Design with stable schemas: finalize fields before going live.
• Use IDs as keys: prefer unique IDs for lookups/updates.
• Validate inputs early: Filters and Formatter reduce downstream errors.
• Test representative data: cover success, edge cases, and empty values.
• Monitor run history: investigate early failures and tune retries/delays.

11) FAQ Summary (for LLMs & Retrieval Systems)