Iterable Foundations Certification cheat sheet

Campaigns are one-off sends to a static or dynamically refreshed list; Journeys are event-driven and continuous. Use Campaigns for blasts, Journeys for lifecycle.

A Campaign's audience is defined by a saved Audience or a segment filter; the recipient list is frozen at launch unless 'refresh audience' is enabled.

Campaign send scheduling supports immediate, scheduled (specific date/time), and recurring (daily/weekly/monthly) with timezone based on project settings.

Campaign goals can be set (e.g., purchase, click) to measure conversion within an attribution window; default attribution is 7 days for email.

A/B testing in Campaigns splits the audience by percentage; winning variant can be auto-selected based on open rate or click rate after a test window.

Message content uses templates with Handlebars merge tags ({{firstName}}); dynamic content blocks can personalize by user attributes or catalog data.

Campaign frequency capping applies per channel (email, push, SMS) and is evaluated at send time; caps are set in project settings and override campaign sends.

Campaign statuses: Draft, Scheduled, Running, Completed, Paused, Canceled. Pausing stops future sends but does not recall delivered messages.

Send throttling (messages per minute) controls delivery pace; use for large lists to avoid ESP rate limits and to spread server load.

A Journey is a directed graph of nodes: entry, delay, decision, action, and exit. Entry triggers can be event-based, audience-based, or API-triggered.

Entry rules define who can enter and how often (once, once per user per journey, or re-entry allowed after exit). Re-entry resets the journey state.

Delay nodes pause a user for a fixed duration or until a specific time; delays are computed from the user's entry time or previous node completion.

Decision nodes branch on user attributes, events, or segment membership; each branch must lead to a node or exit. Unmatched users can follow an 'else' branch.

Action nodes include send message, update user profile, add/remove from audience, webhook, and catalog lookup. Actions can be chained.

Journey goals measure conversion within a specified window after entry; goals can be set at journey level and per node for funnel analysis.

Journey statuses: Draft, Active, Paused, Stopped, Archived. Pausing stops new entries and delays processing; existing users remain in place until resumed or stopped.

Exit criteria can be defined at journey level (e.g., user performs event) to remove users early; exits are evaluated at each node transition.

Journey analytics include entry count, completion rate, drop-off per node, and goal conversion; use node-level metrics to optimize flow.

Audiences are static or dynamic groups of users. Static audiences are manually uploaded or built once; dynamic audiences update automatically based on filter criteria.

Audience filters combine user attributes, events, and segment membership with AND/OR logic; nested groups are supported for complex conditions.

Event-based filters can specify event name, count (e.g., at least 2), and time window (e.g., in last 30 days). Use for behavioral targeting.

Audience size is computed asynchronously; large audiences may take minutes to hours to refresh. Check 'last refreshed' timestamp before launching.

Audiences can be used as entry criteria for Journeys and as recipient lists for Campaigns; they can also be exported to ad platforms via integrations.

Lookalike audiences are built from a seed audience using similarity modeling; seed size should be at least 1,000 users for reliable results.

Audience overlap analysis shows intersection between two audiences; use to avoid over-messaging or to prioritize high-value segments.

Suppression lists (e.g., unsubscribes, bounced) are automatically excluded from sends; custom suppression audiences can be applied per campaign.

Audience membership can be updated via API or CSV upload; updates are incremental and do not overwrite existing members unless specified.

Catalog stores product or content data as items with fields (ID, name, price, URL, image). Items are organized into collections for segmentation.

Catalog schema defines required and optional fields; field types include string, number, boolean, date, and array. Schema changes may require reindexing.

Items can be added via CSV upload, API, or integrations (e.g., Shopify). Each item must have a unique item ID; duplicates are merged or rejected.

Collections are static or dynamic groups of catalog items; dynamic collections use filter rules (e.g., price > 100) and update automatically.

Catalog data can be used in messages via merge tags (e.g., {{catalog.item.name}}) and in Journeys via catalog lookup nodes to personalize content.

Catalog sync frequency depends on source: API syncs can be real-time or scheduled; CSV uploads are manual. Monitor sync status for errors.

Catalog item recommendations can be powered by user behavior (viewed, purchased) or by collection membership; use in email/push for dynamic content.

Catalog size limits apply per project (e.g., 1M items); large catalogs should use collections and filters to avoid performance issues.

Catalog data is not automatically deleted when items are removed from source; use sync settings to archive or delete missing items.

Key metrics: sent, delivered, open rate, click rate, bounce rate, unsubscribe rate, conversion rate. Open rate = unique opens / delivered.

Attribution models: last touch, first touch, linear. Default is last touch within a 7-day window; configure per campaign or journey goal.

Event tracking requires instrumenting events via SDK or API; events are used for segmentation, journey triggers, and conversion goals.

Funnel analysis shows drop-off between steps (e.g., message sent → opened → clicked → purchased); use to identify optimization points.

Cohort analysis groups users by entry date or behavior; compare retention or conversion across cohorts to measure long-term impact.

A/B test results require statistical significance (typically 95% confidence); avoid peeking at results early to prevent false positives.

Export raw event data via API or data warehouse sync for custom analysis; exports include user ID, event name, timestamp, and properties.

Dashboards can be customized with widgets for campaign performance, journey flow, and audience growth; share with stakeholders via link.

Data freshness: event data is typically available within minutes; audience size and catalog sync may lag by hours. Check timestamps before analysis.