> For the complete documentation index, see [llms.txt](https://docs.elevateab.com/elevate-helpcenter/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.elevateab.com/elevate-helpcenter/price-testing/ending-a-price-experiment.md).

# Ending a Price Experiment

How to end a price experiment in Elevate A/B Testing, implement the winning price, and what happens to visitors and carts when it stops.

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### Before you end

**Export your current prices first.** Implementing a winning price overwrites your existing prices in Shopify, and there is no undo and no stored copy of what they were. Export your product and variant prices from Shopify admin, or use **Download CSV** in the experiment, before you apply anything.

Also confirm you are ready. See the checklist in [Reading Price Experiment Results](https://claude.ai/chat/reading-results.md).

### Ending the experiment

Ending stops the experiment. Your storefront returns to its catalogue prices, no new visitors are assigned, and no further data is collected. Your results remain available.

The experiment moves to **Done**.

### Implementing the winner

When you implement a winning variation, Elevate writes those prices to your products in Shopify, updating both the price and the compare at price for each variant.

Three things to know.

**There is no rollback.** Elevate does not keep a copy of your previous prices. This is why exporting them first matters.

**Market specific prices are not written.** If your experiment tested different prices per currency, implementing the winner sets a single price per variant. Set market specific prices in Shopify afterwards.

**Applying a winner does not stop the experiment.** Ending and implementing are separate actions.

### What happens to visitors and carts

**Visitors mid session.** The page they are currently on keeps the prices it rendered. The next page they load shows catalogue prices.

**Carts already filled.** A cart containing a test price is recalculated at the catalogue price when the experiment ends. If the test price was lower, the price a shopper sees goes up between visits.

This is worth planning around. If a large share of your carts sit unpurchased for days, ending a discount test can raise prices under people who were about to buy. Consider implementing the winner at the same time you end the experiment, so the price they return to is the price you decided on.

### After ending

* Record what you learned, including flat results. A price change that moved nothing tells you where your room to move is.
* If the result was strong, test further in the same direction. A successful ten percent increase invites a test at fifteen.
* If the result varied sharply by segment, consider an [Advanced Pricing Personalization](https://docs.elevateab.com/elevate-helpcenter/personalizations/personalizations-getting-started) rather than a single new price.
* If you plan a follow up test on the same products, wait until this one is fully ended so the two do not overlap.

### Cleanup

Price experiments create no duplicate products and leave nothing behind on your store. There is nothing to remove after ending one.

If you added content or code changes to the experiment, those stop with it.