> For the complete documentation index, see [llms.txt](https://docs.intelligems.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.intelligems.io/general-features/targeting/targeting-faqs.md).
# Targeting FAQs
When running a price test, what prices do visitors see when they do not match audience targeting or are excluded by a mutually exclusive test group?
When a visitor doesn't match a test's **audience targeting**, they're shown **control group pricing** by default.
At the start of a price test, Intelligems updates product prices in Shopify to the **highest test price**. Visitors who don't match the audience are assigned to the control group, so they see the same pricing experience they would have if the test weren't running. That includes any other changes set up in the control group, such as onsite edits, CSS or JS injections.
Visitors excluded by a **mutually exclusive test group** aren't assigned to any variation, so they see the Shopify price, which is the highest test price. If control isn't your highest price, they see a higher price than control. For details, see the price and shipping caveats in Mutually Exclusive Experiments.
How is audience or page targeting taken into account when it comes to Mutually Exclusive Experiments?
When you set up tests to be **mutually exclusive**, each visitor is assigned to one test within the exclusion group as soon as they land on your site — **before** any targeting conditions are evaluated. They are not assigned to a test group until they meet all targeting conditions.
This means a visitor might be assigned to a test they never actually qualify for. If they don’t meet that test’s targeting rules, they won’t be included in a test group — and they also won’t be eligible for any other mutually exclusive tests. As a result, some of your traffic may not be included in any testing, which can lead to **lower traffic utilization** and **slower learnings**.
This approach helps ensure clean, unbiased test results by preventing targeting rules from influencing which test a visitor is assigned to. However, it’s important to keep in mind that mutually exclusive tests are best used when targeting is broad, or when avoiding test overlap is critical.
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