Batch Job
Also known as: Scheduled Job, Cron Job, Background Job
An automation that processes a large group of records at once on a schedule, rather than one record at a time in response to events.
Definition
A batch job is an automated process that operates on a large group of records simultaneously on a scheduled cadence — every hour, every night, every week — rather than processing records one at a time in response to individual events. The term comes from mainframe-era computing where 'batch processing' contrasted with 'real-time processing.'
Common marketing-ops batch jobs include: nightly list-cleaning (removing hard-bounced addresses), weekly engagement-scoring updates (recalculating scores across all contacts), monthly database-hygiene sweeps (deduplicating contacts), and quarterly suppression-list reviews. Each runs on a schedule against the full dataset, not in response to individual triggers.
Batch jobs are increasingly being replaced by event-driven streaming in modern systems — the same scoring update can fire immediately when behavior occurs rather than once a night. But batch processing remains the right choice for operations that don't need real-time response and that benefit from running on consistent snapshots.
Why It Matters
Batch jobs handle the heavy maintenance work that keeps marketing operations clean. Manual list cleanup, manual score updates, and manual deduplication don't scale beyond small databases. Batch jobs do the work consistently without consuming team time.
The biggest mistake is running batch jobs without monitoring. A nightly job that silently fails for 3 weeks leaves you with stale scores, dirty lists, and confused downstream automation. Every batch job needs success/failure alerting.
Examples in Practice
A SaaS marketing-ops team runs nightly batch jobs: hard-bounce suppression (moves the day's bounces to the global suppression list), score recalculation (updates lead scores based on the day's behavior), list refresh (rebuilds dynamic-list membership based on updated data). The next morning's campaigns operate against clean data.
A B2B agency runs a weekly batch job that updates company firmographic data via enrichment API. Each Sunday night, all active contacts get refreshed firmographic data; segmentation reports the following week reflect current company state.
An ecommerce brand runs a monthly batch job that recalculates customer lifetime value scores based on the past quarter's purchase patterns. The updated scores drive segmentation for upcoming retention campaigns.