> 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/price-experiment-use-cases.md).

# Price Experiment Use Cases

Eight price experiments worth running in Elevate A/B Testing, each with a hypothesis, a setup sketch, and what a win looks like.

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Concrete price experiments worth running, and what you learn from each. Every one includes the hypothesis to record before you launch, how to set it up, and what a win looks like.

Start with the one that matches a question you already argue about internally. Those are worth running first, because you already care about the answer.

### Test a price increase

The most valuable price experiment, and the one almost nobody runs. Most stores assume a higher price costs them sales, and never check whether it costs fewer sales than the extra margin is worth.

**Hypothesis.** Demand for this product is less price sensitive than we assume, so a ten percent increase will reduce conversion by less than ten percent and increase revenue per visitor.

**Setup.** One product with steady traffic. Two variations. Autofill: Price Increase, 10, Percentage. Goal metric: Revenue per visitor.

**A win looks like.** Conversion drops slightly and revenue per visitor rises.

**Watch out for.** Judging this on conversion rate. The variation will convert worse. That is not the question.

### Find the discount depth that actually pays

You discount because it works. The open question is whether it needs to be that deep.

**Hypothesis.** A fifteen percent discount converts nearly as well as twenty five percent, so the shallower discount earns more profit per visitor.

**Setup.** Three variations: current discount, one shallower, one deeper. Goal metric: Profit per visitor. Add [COGs](https://docs.elevateab.com/elevate-helpcenter/experiment-setup/product-costs) first, or profit cannot be calculated.

**A win looks like.** The shallower discount matches or beats the deeper one on profit per visitor. You keep the volume and the margin.

**Watch out for.** Running this during a promotional period. Your baseline is not normal.

### Test the strikethrough

A compare at price sets an anchor. Whether the anchor helps, and how high it should sit, is testable without changing what you charge.

**Hypothesis.** Showing a compare at price alongside the selling price increases perceived value and lifts conversion.

**Setup.** Two variations at the same selling price. Autofill: Compare Increase. Goal metric: Revenue per visitor.

**A win looks like.** Same price, more revenue. Your margin did not move.

**Watch out for.** Compare at prices you cannot substantiate. Check what your market requires before anchoring against a price you never charged.

### Find your charm pricing

Whether prices ending in 99 outperform round numbers is one of the oldest arguments in retail, and cheap to settle on your own store.

**Hypothesis.** Prices ending in 99 convert better than round numbers at the same approximate level.

**Setup.** Two variations a few cents apart, for example 49.99 against 50.00. Autofill rounds up, down, or to nearest, so it will not produce a .99 ending. Across a catalogue, set these by CSV. Goal metric: Revenue per visitor.

**A win looks like.** A measurable difference from a price change too small to affect margin.

**Watch out for.** Expecting a large effect. Run it catalogue wide rather than on one product.

### Price differently by market

If you sell internationally, your prices in each currency are probably a conversion of your home price rather than a decision.

**Hypothesis.** Buyers in this market will accept a higher price than a direct currency conversion produces.

**Setup.** Add the currency to the experiment and set prices for it. Selecting the currency scopes the experiment to that market automatically, so no audience filter is needed. Goal metric: Revenue per visitor. Requires a Premium Elevate plan.

**A win looks like.** A market specific price that earns more than the converted one.

**Watch out for.** Running out of traffic. One market is a fraction of your visitors, so this needs a longer run.

### Close the subscription gap

Subscription pricing is usually set once, as a percentage off the one time price, and never revisited.

**Hypothesis.** A smaller subscription discount will not reduce signups enough to offset the extra revenue per order.

**Setup.** Requires Recharge. Two variations with different subscription prices at the same one time price. Goal metric: Revenue per visitor, with Subscription percentage of orders as a secondary read.

**A win looks like.** Subscription share holds steady while revenue per visitor rises.

**Watch out for.** Reading this on signup rate alone. A cheaper subscription always wins that metric and can still lose money.

### Price a category, not a product

Single product tests answer a narrow question slowly. Category wide tests answer a broader one faster, because more traffic enters.

**Hypothesis.** This entire category is underpriced relative to what buyers will accept.

**Setup.** Filter by collection or tag and select all, up to 500 products. Autofill applies a percentage change across every product at once. Goal metric: Revenue per visitor.

**A win looks like.** A pricing rule you can apply to a whole category, rather than a single product answer you cannot generalize.

**Watch out for.** Mixed margins inside one category. If cost of goods varies widely, use Profit per visitor.

### Test the price and the message together

Sometimes the question is not what the price should be, but how it should be framed.

**Hypothesis.** A lower price presented with an explicit savings message will outperform the same lower price shown on its own.

**Setup.** Three variations: current price, lower price, lower price plus a savings message added through the optional content layer. Goal metric: Revenue per visitor.

**A win looks like.** The message adds lift on top of the price change, which tells you presentation is worth investing in.

**Watch out for.** Two variations that each change two things. Keep one as price only, or you will not know which half did the work.

### Choosing between these

| If you have                                     | Start with                                 |
| ----------------------------------------------- | ------------------------------------------ |
| One high traffic product and a pricing argument | Test a price increase                      |
| A discount you have never questioned            | Find the discount depth that actually pays |
| Low traffic and a full catalogue                | Price a category, not a product            |
| International sales priced by conversion        | Price differently by market                |
| Recharge subscriptions                          | Close the subscription gap                 |

Whichever you choose, record the hypothesis in the experiment before you launch. Results are much easier to act on when you can see what you expected.