Manage Experiments with AI

Use this page to run the full experiment lifecycle (create, edit, start, stop, and read results) through an AI assistant like Claude or ChatGPT, without touching the dashboard.

It uses the MCP Server to manage the same experiments documented elsewhere in this section. It is the preferred authoring path for always-on personalization.

Open Experiments in app

Note: This page covers making changes from your own AI client. For answers inside the dashboard, such as how an experiment is performing, use the built-in AI Assistant.

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Before You Start

1. Connect your AI tool to the Ours Privacy MCP server. See MCP Server (platform).
2. Install experimentation on your site if you haven't already. See Installation.

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Create an Experiment

Ask your assistant in plain language. Example prompt:

"Create a draft content experiment named Pricing CTA v2 targeting /pricing. Add two variants: control (no change) and treatment (button text: Try it free)."

The new experiment appears in Experiments in your dashboard as a draft.

A primary metric event and at least two variants are required before an A/B or multivariate experiment can start, so include the goal event in your prompt, for example, "...with primary metric signup_completed."

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Create Personalization

Ask for the behavior signal first when the target depends on an event:

"When a visitor views /pricing, store visited_pricing: true. Then create an always-on personalization named Pricing follow-up for visitors with visited_pricing, replace .hero h1 with Ready to compare plans?, and publish it."

Personalization needs no primary metric; every visitor matching the targeting gets the treatment.

Property rules begin accumulating from the next matching event and are available on the visitor's next full page load.

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Edit an Experiment

Once a draft exists, you can edit it the same way:

"Update the Pricing CTA v2 experiment to target visitors with UTM source google only. Set traffic allocation to 50%."

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Start an Experiment

When you're ready to ship:

"Start the Pricing CTA v2 experiment."

Assignment begins immediately; impressions and your existing conversion events flow into the same analytics you already use.

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Read Live Results

Ask for the current numbers anytime:

"How is Pricing CTA v2 performing? Which variant is winning?"

The assistant summarizes the Bayesian probability-to-be-best for each variant. For trends over time, ask for "results over the last 14 days".

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Stop an Experiment

When you've seen enough:

"Stop Pricing CTA v2 and lock in the treatment."

To apply the winning variant permanently, use the rollout option in the stop dialog or see Declaring a Winner.

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Next Steps

• Headless Experiments: render variant UI in your own application code
• Content Experiments: modify DOM elements per variant
• Experiment Settings: targeting and allocation

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Need Help?

Reach out to support@oursprivacy.com if you have questions about running experiments through AI.