THE SHORT ANSWER
Choose refresh frequency from the rate at which important facts change, the destination’s delivery contract and the time needed to process a complete release. Measure actual source-to-destination delay before increasing job frequency. More frequent runs do not fix stale sources or unsafe transformations.
Start with the freshness requirement
List the fields whose age matters most: stock, price, promotion periods and withdrawn offers often need more attention than descriptive copy. Ask how long a disagreement can reasonably persist before it creates a customer or operational problem.
Then read the destination’s current delivery guidance. For example, OpenAI’s file-upload guidance describes predictable full-snapshot updates with at least a daily cadence. That requirement is one input to your schedule, not a universal freshness guarantee for every field or channel.
Measure the complete delay
Record when the source changes, when your job reads it, when the export finishes and when the destination reports processing. A fifteen-minute schedule can still produce old information if it reads an overnight cache. Measure the whole path instead of advertising the shortest interval in the system.
Include normal duration and exceptional duration. A job that usually takes ten minutes but sometimes takes an hour needs a policy for overlapping runs. Two jobs writing the same output simultaneously can create an incomplete or confusing release.
Choose a schedule the workflow can sustain
Estimate import volume, validation work, review queues and delivery limits. Stable descriptive changes may tolerate a slower reviewed release, while commercial facts may need a separate supported update path. Use the destination’s actual interfaces and constraints when designing that separation.
Avoid scheduling more manual review than the team can perform. If every refresh reopens unchanged approvals, a faster schedule simply produces a larger backlog. Focus review on changed evidence and maintain clear rules for fields that cannot safely wait.
Monitor missed runs and stale results
A timer firing is not proof that a useful release completed. Alert on failures, unusually long processing, unexpected product-count changes and age of the last accepted result. Assign an owner and a recovery action to each meaningful alert.
Reassess the schedule when catalog size, promotion activity or source behavior changes. Use actual incident evidence to decide whether the next improvement should be frequency, source reliability or a better change-detection rule. The cheapest run is not useful if it repeatedly misses the information customers need.
ILLUSTRATIVE WORKED EXAMPLE
Make it concrete.
Illustrative example: a merchant runs every hour but reads a source refreshed once overnight. Moving the timer to fifteen minutes adds work without improving freshness. The team first connects the current source, then measures the remaining delivery delay before choosing the new schedule.
Your practical checklist
- Define acceptable age for important commercial facts.
- Read the destination’s current delivery requirements.
- Measure source, export and processing timestamps.
- Prevent overlapping or incomplete releases.
- Alert on stale accepted results, not just failed timers.
Common questions
Is hourly refresh always better than daily?
Only if the source changes, the destination supports the cadence and the workflow can process reliable updates.
Does Feedaptor guarantee downstream processing time?
Do not assume that. Separate your export completion from the receiving channel’s observable acceptance and processing.
Sources & scope
Official references checked 29 October 2026. Examples are illustrative, not customer results. Platform requirements can change; use current destination documentation for implementation decisions.
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