Schedule Shopify changes that undo themselves

Plan Black Friday prices, flash sales, product launches, and seasonal catalog updates across every store. Peak PIM publishes each change at the start time and restores the live values automatically at the end.

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The midnight problem

A campaign should not depend on alarms and cleanup

Starting a catalog event is only half the job. The real risk is applying the right values everywhere, then returning each storefront to the state it was actually in.

The sale starts when your team should be sleeping

Black Friday prices, flash sales, and product launches often mean someone is waiting to publish catalog changes at exactly the right minute.

Ending the sale is another manual job

Every changed price, title, and compare-at price has to be remembered and restored without overwriting work that happened in the meantime.

Each storefront adds another moving part

Regional prices, different launch copy, and local timing turn one campaign into a separate checklist for every Shopify store.

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Set it and forget it

Plan the change and its rollback together

Build the Drop from the workflow you already use, inspect the full plan before it starts, and let Peak handle both scheduled moments.

Schedule

Stage any catalog change

Select products, variants, or collections in bulk edit and choose Schedule, or add one store-specific field change from an item's detail page.

Preview

See the exact live-to-scheduled diff

Review every item, store, field, current value, and scheduled value before the Drop starts. Conflicting overlapping changes are flagged up front.

Apply and restore

Schedule the undo too

Peak snapshots each live value, publishes the Drop to Shopify at the start time, then restores that captured value and republishes at the end.

Built for catalog operations

On time across every store

Drops publish precise catalog changes straight to Shopify, preserve the live values they replace, and make every failure visible.

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Run a sale window or a scheduled launch

Add a start and end time for changes that revert automatically, or set only a start time when the new values should stay live.

Publish different changes to every store

One Drop can change prices on one storefront, titles on another, and hundreds of other item-and-field combinations at the same moment.

Restore the values that were truly live

Peak captures each field immediately before applying the Drop, so rollback returns the catalog to reality instead of an older assumed value.

Surface failures and keep retrying

Failed changes retry automatically. Persistent issues are flagged with Retry, Edit value & retry, Dismiss, and Retry all controls without blocking successful changes.

Schedule the sale and the morning after

Stage every price and product change, publish at the exact minute, and let Peak restore the storefront when the Drop ends.

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Frequently asked questions

Everything you need to know about scheduling Shopify product drops, sale windows, and automatic catalog rollbacks with Peak PIM.

A Drop is a scheduled group of product, variant, or collection changes. It has a name, a start date and time, and an optional end date and time. Peak applies the changes at the start and, when an end is set, restores them automatically.

Yes. A time-boxed Drop has a start and end, which suits sales and temporary catalog changes. An open-ended Drop has only a start, which suits launches or permanent scheduled updates.

Drops use the editable fields available in Peak PIM, including prices, compare-at prices, titles, and other product, variant, or collection fields. Each scheduled change targets one item, one store, one field, and one value.

Yes. A single Drop can contain different changes for different stores and publish them at the same scheduled time. Every row in the preview identifies its target store.

If overlapping Drops try to change the same field on the same item and store, Peak PIM warns you about the conflict while the changes are being scheduled.

At the start time, Peak captures the current value of every field before changing it. At the end time, Peak restores those captured pre-Drop values and republishes them to Shopify.

Yes. Cancel a scheduled Drop and it never applies. Cancel an active Drop and Peak immediately starts restoring the captured values, typically completing the restore within about 30 seconds.

Peak retries failed changes automatically with backoff, up to eight attempts. Persistent failures are shown in a needs-attention state with controls to retry, edit the value and retry, dismiss one change, or retry all.

Start and end times are entered in your own timezone, so the schedule matches the way your team plans each campaign or launch.

Still have questions?

Reach out to our team and we’ll help you find the right setup.

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