Marketing AnalystCampaign AnalyticsIntermediateSingle prompt

A/B Test Analysis for Campaigns AI Prompt

Analyze this marketing A/B test and produce a decision-ready report. Test description: {{test_description}} Variants: Control: {{control}} | Treatment: {{treatment}} Primary met... Copy this prompt template, run it in your AI tool, and use related prompts to continue the workflow.

Prompt text
Analyze this marketing A/B test and produce a decision-ready report.

Test description: {{test_description}}
Variants: Control: {{control}} | Treatment: {{treatment}}
Primary metric: {{primary_metric}}
Test data: {{results_data}}

1. Statistical analysis:
   - Control and treatment values for the primary metric
   - Absolute and relative difference
   - Two-proportion z-test (for conversion rates) or t-test (for continuous metrics)
   - p-value and 95% confidence interval
   - Is the result statistically significant at alpha = 0.05?
   - Statistical power: given the observed sample size and effect, what was the test's power?

2. Practical significance:
   - Effect size: Cohen's h (for proportions) or Cohen's d (for means)
   - Business impact: if this effect persists at scale, what is the annual revenue or cost impact?
   - Minimum detectable effect vs observed effect: did we detect what we expected to detect?

3. Secondary metric analysis:
   - Repeat for all secondary metrics
   - Did any guardrail metrics degrade significantly?

4. Segment analysis:
   - Break results by: device, geography, new vs returning, customer tier
   - Is the effect consistent across segments or driven by one?
   - Heterogeneous treatment effects: does the winner differ by segment?

5. Decision:
   - Implement / Do not implement / Run follow-up test
   - If implementing: rollout plan
   - If running follow-up: what specific question does the next test answer?

6. Learnings for future campaigns:
   - What does this test teach us about our audience or message?
   - Should this insight change any other running campaigns?

Return: statistical analysis, effect size calculation, segment breakdown, decision, and learnings.

When to use this prompt

Use case 01

Use it when you want to begin campaign analytics work without writing the first draft from scratch.

Use case 02

Use it when you want a more consistent structure for AI output across projects or datasets.

Use case 03

Use it when you want prompt-driven work to turn into a reusable notebook or repeatable workflow later.

Use case 04

Use it when you want a clear next step into adjacent prompts in Campaign Analytics or the wider Marketing Analyst library.

What the AI should return

The AI should return a structured result that covers the main requested outputs, such as Statistical analysis:, Control and treatment values for the primary metric, Absolute and relative difference. The final answer should stay clear, actionable, and easy to review inside a campaign analytics workflow for marketing analyst work.

How to use this prompt

1

Open your data context

Load your dataset, notebook, or working environment so the AI can operate on the actual project context.

2

Copy the prompt text

Use the copy button above and paste the prompt into the AI assistant or prompt input area.

3

Review the output critically

Check whether the result matches your data, assumptions, and desired format before moving on.

4

Chain into the next prompt

Once you have the first result, continue deeper with related prompts in Campaign Analytics.

Frequently asked questions

What does the A/B Test Analysis for Campaigns prompt do?+

It gives you a structured campaign analytics starting point for marketing analyst work and helps you move faster without starting from a blank page.

Who is this prompt for?+

It is designed for marketing analyst workflows and marked as intermediate, so it works well as a guided starting point for that level of experience.

What type of prompt is this?+

A/B Test Analysis for Campaigns is a single prompt. You can copy it as-is, adapt it, or use it as one step inside a larger workflow.

Can I use this outside MLJAR Studio?+

Yes. The prompt text works in other AI tools too, but MLJAR Studio is the best fit when you want local execution, visible Python code, and reusable notebooks.

What should I open next?+

Natural next steps from here are Campaign Performance Report, Campaign ROI Analysis, Demand Generation Funnel Analysis.