Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.abconvert.io/llms.txt

Use this file to discover all available pages before exploring further.

ABConvert is built for Shopify merchants who want to make data-driven decisions about pricing, content, shipping, and more. This page answers the questions that come up most often. If you don’t find what you’re looking for here, reach out to support — contact details are at the bottom of this page.
ABConvert is a Shopify app that lets you run A/B experiments on your store — testing different prices, themes, templates, shipping options, checkout layouts, and URL redirects — and measures which variant converts better.When a visitor lands on your store, ABConvert assigns them to a test group using a seeded random algorithm. That assignment is stored in the visitor’s browser (via localStorage) and in their cart attributes, so they see a consistent experience throughout their session. As they browse, add to cart, check out, and purchase, ABConvert tracks each step using a Shopify web pixel. Your analytics dashboard then shows conversion rates, revenue, and statistical results for each group.Experiments run directly on your live store. No redirects to separate domains, no iframes — just a lightweight script that modifies what the visitor sees.
ABConvert works on all Shopify plans, but some experiment types require specific Shopify subscriptions:
  • Shipping test: Requires Shopify Grow+ for Carrier Service API
  • Checkout UI test: Requires Shopify Plus
ABConvert is compatible with most Shopify themes, including Online Store 2.0 themes and legacy themes. The app uses an embed app in your theme that targets standard Shopify DOM elements (product forms, price selectors, variant inputs).If you’re on a theme with heavy customizations and find the test not loading well on your theme, contact support.
Currently, ABConvert does not support Shopify headless stores.
When you create an experiment, you define test groups and assign a percentage of traffic to each. For example, you might send 50% of visitors to the control group and 50% to a variant, or split traffic three ways at 33%/33%/34%.Each visitor is assigned to a group using a seeded random hash. The seed is derived from a visitor identifier so that the same visitor consistently lands in the same group throughout their session — and on return visits, as long as their localStorage hasn’t been cleared.You can also restrict which visitors enter the experiment using filters. Visitors who don’t match your filters see the default experience and are not counted in experiment analytics.
Yes. ABConvert supports concurrent experiments. Each experiment tracks its own visitors, conversions, and revenue independently.There are a few things to keep in mind when running experiments simultaneously:
  • If two experiments target the same product, a visitor may be assigned to both. Each experiment maintains its own assignment independently.
  • You cannot run more than 1 active test on the same product in price test, or on the same shipping profile in shipping test.
  • Running many experiments at once will divide your traffic, which means each individual experiment collects data more slowly. Fewer daily visitors per group means it takes longer to reach statistical significance.
There is no universal answer — it depends on your traffic volume and the size of the effect you’re trying to detect. As a practical guideline:
  • Run experiments for at least two full weeks to account for day-of-week variation in shopper behavior.
  • Aim for a minimum of 100–200 conversions per group before drawing conclusions. With fewer conversions, results are unlikely to be statistically reliable.
  • Avoid stopping an experiment the moment you see a positive result. Early “wins” often revert as more data comes in — a pattern called “peeking.”
If your store has low traffic, a test that would take weeks to complete may not be worth running. In that case, focus on larger, more impactful changes where even a small sample can show a meaningful difference.
ABConvert does not create separate URLs or pages for test variants, so there is no risk of duplicate content penalties from running experiments.For price tests, the price change is applied to the visitor’s session only — search engine crawlers see your original prices. For theme and template tests, crawlers typically receive the default variant since they do not execute JavaScript in the same way a browser does.
ABConvert uses two complementary methods to attribute orders to experiments:
  1. Web pixel — A Shopify web pixel tracks page_viewed, product_added_to_cart, checkout_started, and checkout_completed events in real time. The pixel reads the visitor’s experiment assignment from cart attributes and sends conversion events to ABConvert’s analytics backend.
  2. Cart attributes — When a visitor is assigned to an experiment group, ABConvert writes a groupInfo attribute to their Shopify cart. This attribute follows the cart through the entire checkout flow, which is how orders are connected to the correct experiment and test group even when a visitor completes checkout in a different browser session.
Both methods work together. If the web pixel fires successfully at checkout completion, the order is recorded via the pixel. The cart attributes provide a fallback and are used for order webhook processing.
If your analytics show 0 views or conversions, the web pixel may not be installed correctly. Go to Settings in ABConvert and check the web pixel status. You may need to reinstall it.
Yes. ABConvert supports audience filtering at the experiment level, so you can limit which visitors are included in an experiment. Visitors who do not meet your filter criteria are excluded from the experiment and see the default experience. They are not counted in your experiment’s analytics.For multi-market stores using Shopify Markets, you can also configure per-country price variants in a price test, so each market sees prices in their local currency.
When you pause an experiment:ABConvert removes the active Shopify resources (scripts, metafields, extensions) that power the experiment. Visitors who were mid-session and had been assigned to a test group will revert to seeing the default experience — they are no longer in the experiment. All data collected up to the pause point is preserved, and you can resume the experiment later.When you end an experiment:Ending an experiment permanently closes it. ABConvert cleans up all Shopify resources, including duplicated variants for V1 price tests. Any visitor mid-session at the moment you end the experiment will revert to the default experience immediately. The experiment data is preserved for analysis, but the experiment cannot be restarted — you would need to create a new one.What about orders placed mid-transition?Orders placed in the brief window during a pause or end operation may not be attributed to the correct experiment group. This is an inherent limitation of the async nature of Shopify API operations. For best results, avoid pausing or ending experiments during peak traffic hours.
Yes, with some nuances depending on the experiment type.For price tests, ABConvert supports multi-market pricing for Scale+ plan. When you create a price test, you can configure test prices per country and currency, stored in a market price map. When a visitor lands on your store, ABConvert detects their country from Shopify’s market context and applies the correct localized price for their test group.For other experiment types (theme, template, content, checkout, URL redirect, shipping), the experiment applies to all visitors regardless of market by default. You can use country filters to restrict an experiment to specific markets if needed.