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A/B Testing Plan for Stay Hotel's Google Ads Campaign

Designed an A/B testing plan for a hypothetical hotel brand to test the effectiveness of a deal-focused headline. The test aimed to increase the ad’s conversion rate from 2% to 7% based on audience behavior insights.

Project Type

Campaign Optimization — A/B Testing Strategy

Date

July 2025

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Project Overview

This project involved designing a detailed A/B testing plan for Stay Hotel’s Google Ads campaign as part of the Meta Marketing Analytics Professional Certificate. The goal was to apply data-driven marketing principles to improve ad performance by testing two headline variations.
 

Using audience behavior insights that revealed a strong preference for deals, I developed a strategy to compare a value-focused headline with a discount-driven variant. The test aimed to boost the campaign's conversion rate from 2% to 7% by evaluating which message better resonated with budget-conscious travelers.
 

Through this simulation, I gained hands-on experience with real-world testing parameters, like setting confidence levels, identifying key metrics, segmenting audiences, and crafting performance-oriented ad copy.

What I Explored

In this project, I created a comprehensive A/B test plan for Stay Hotel’s direct response Google Ads, aiming to validate whether a discount-based headline would drive higher conversions.

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Here’s what I built:

  • Objective: Boost conversions from 2% to 7%

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  • Hypothesis: A deal-focused headline (e.g., "Save Up to 20%") would better appeal to cost-conscious users

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  • Variant Creation:

    • A (Control): “Stay Hotel – Great Rates & Free Breakfast”

    • B (Test): “Stay Hotel – Save Up to 20% on Your Stay!”

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  • Testing Setup:

    • Channel: Google Ads

    • Duration: 30 Days

    • Audience: 3,000 users per variant

    • Confidence level: 95% minimum

    • Primary metric: Conversion Rate

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Key Takeaways

  • Learned how to turn behavioral insights into a data-backed marketing hypothesis

  • Practiced writing compelling ad copy within 30-character limits for Google Ads

  • Developed a clear handoff strategy to guide team implementation of the test

  • Understood the importance of control groups, confidence levels, and target metrics in campaign testing

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