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Create a Price Experiment

Step by step walkthrough for building, previewing, and launching a price experiment in Elevate A/B Testing.


Seven setup steps, then preview, then launch. Your first price experiment also goes through a review before it can go live.

Before you start

  • Elevate A/B Testing installed on a Standard or Premium plan.

  • The theme extension enabled on your live theme.

  • COGs added, if you want to measure profit.

  • You know which products you are testing and what prices you want to try.

Allow time for review. Your first price experiment is checked by Elevate's support team before launch, typically 2 to 12 hours.

Step 1: General info

  1. Open Experiments and select Create Experiment on the Advanced Price Experiment card.

  2. Enter an Experiment name. The only required field. Name it so you recognize it later without opening it.

  3. Optionally add a Description and a Hypothesis. The hypothesis is where you record what you expect and why, before you launch.

  4. Optionally attach Assets: mockups, briefs, notes. Images and documents up to 10 MB, videos up to 100 MB.

  5. Under What do you want to measure?, choose your goal metric.

Revenue per visitor is recommended for price experiments. It accounts for both how many people buy and how much they spend, so a cheaper variation that sells more units but earns less will not look like a winner.

Profit per visitor also subtracts cost of goods, shipping, and fees. Requires Product Costs.

Select Browse all metrics for the full list, or Add Custom Metric for something Elevate does not measure by default.

Every other metric is still calculated and shown in your results. The goal metric only decides how the winner is chosen.

  1. Select Continue.

Step 2: Select products

Up to 500 products per experiment, and up to 10,000 product variants.

Search by product title or ID.

Filter by product type, status, collection, or tag. Status defaults to Active, and also offers All, Unlisted, Draft, and Archived.

Select All selects everything matching your current filters. Combine with a collection or tag filter to price a whole category at once.

Upload CSV imports a product list and its prices together. See below.

Select Continue.

Step 3: Add variations

  1. Under Select the number of Variations, choose 2 to 5. They are labelled A through E, where A is always your control.

  2. If you sell in more than one currency, select each currency you want to price for. Requires a Premium plan.

  3. Set prices for each variation.

Each product expands to show its variants. The Control column shows the current price and cannot be edited. Enter test prices in the variation columns.

Apply Autofill

Sets prices across every selected product at once.

Field
Options

Change type

Price Increase, Price Decrease, Compare Increase, Compare Decrease

Amount

The number to apply

Unit

Percentage or Currency

Round value

No round, Up, Down, or Nearest

Price Decrease, 15, Percentage sets every variation price fifteen percent below its control.

Compare Increase and Compare Decrease change the compare at price rather than the selling price. Use these to test a strikethrough without changing what you charge.

Rounding applies after the change and rounds to a whole currency unit. A fifteen percent decrease on 28.50 with Nearest gives 24.00. It will not produce a specific price ending, so for prices ending in .99 or .95, use CSV or set them by hand.

You can adjust individual prices after applying Autofill. Reset All clears everything.

Uploading prices by CSV

Column
Notes

Product ID

Numeric ID or Shopify GID format

Variant ID

Numeric ID or Shopify GID format

Variation ID

A whole number from 1 to 4

Price

The test price

Currency

The currency this price applies to

Compare At Price

Optional

Do not include rows for the control. Elevate generates it from your live Shopify price. Variation IDs run 1 to 4, giving up to five variations including the control.

The CSV becomes your product list. Whatever is in the file replaces your current selection.

Import is all or nothing. If any row fails, nothing imports. Errors are reported per row, with the header counted as row 1, and all errors shown together so you can fix them in one pass.

Select Download Sample CSV in the upload dialog for a correctly formatted file. Download CSV exports your current prices for editing in a spreadsheet.

To find IDs, open a product in Shopify admin and read the Product ID from the URL. Click into a variant and read the Variant ID the same way.

  1. Select Continue.

Step 4: Traffic allocation

How much traffic should each variation receive? defaults to an even split. Leave it there unless you have a reason not to. An even split reaches a trustworthy result fastest.

You might weight the control higher to limit how many visitors see a large price increase, at the cost of a longer run.

Isolate traffic for this experiment is optional and off by default. It reserves a share of your total store traffic for this experiment alone. Turn it on if another running experiment includes the same products. See Traffic Isolation.

Select Continue.

Step 5: Audiences

Every visitor is eligible by default. Narrow it only when the question is about a specific group.

Quick filters cover device type, visitor type, UTM parameters, traffic source, and country. Select Create Custom Audience for more specific rules.

If you are testing prices in specific currencies, you do not need a market filter here. The currencies you priced in step 3 already scope the experiment to visitors shopping in those currencies.

Every filter shrinks the pool entering the experiment, which lengthens the run. See Audience Targeting.

Select Continue.

Step 6: Enhance your variations

Optional. Your variations are complete without this step.

Option
What it adds

Content Editing Changes

Edit headlines, copy, or images per variation

Custom Code

Apply JavaScript or CSS per variation

Click-Through Rate Tracking

Track clicks on specific buttons or links, with click rates per variation in your results

For click tracking, turn the toggle on and select Add Element for each button or link.

Adding content or code makes this a multivariate experiment. Keep one variation as a price only change if you want to separate the effect of the price from the effect of the presentation.

Select Continue.

Step 7: Preview

Preview before the experiment goes near real traffic. You can also preview at any point during setup using the Preview button next to any product in step 3.

  1. Choose a version under Select Variation to Preview. Every variation is available, including the control.

  2. If you sell in more than one market, choose one under Select Market to Preview.

  3. Select Preview to open it on desktop.

  4. Scan the QR code to check the same variation on your phone.

You can add a previewed product to the cart and go through to checkout to confirm the price a customer is charged. Two things to know:

  • Preview in an incognito window. The preview pins you to the chosen variation for a year, which will skew your own view of the store.

  • A test order placed from a preview counts in your experiment results. Cancel or refund it, and account for it when you read the numbers.

For the full checklist, see Preview and QA a Price Experiment.

Submit for review and launch

The review flow has three stages:

  1. Overview. A summary of what you built.

  2. Theme Extension. Confirms the extension is enabled on your live theme. Enable it here if not.

  3. Elevate Review. Select Submit for review.

Elevate's technical support team confirms your prices update consistently everywhere they appear on your store. If anything is off, the team corrects it. They will be in touch through the chat widget in the app.

Review typically takes 2 to 12 hours. Once complete, Launch Experiment becomes available.

Only the first price experiment on your store goes through review. Later ones launch straight away.

After launch

The experiment moves to Running and starts collecting data.

Do not stop it early, and do not edit variations while it runs. Editing mid experiment mixes two different tests into one dataset.

See Launching a Price Experiment for what to expect, and Reading Price Experiment Results for what the numbers mean.

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