Google Ads Campaign Structure Analysis | Optimize ROI with Data-Driven Changes

Enhanced Prompt:

Objective:
Conduct a comprehensive analysis of historical data on Google Ads campaign structure changes to identify which structural adjustments have led to improved ROI. The goal is to provide actionable insights and recommendations for optimizing campaign performance.

Deliverables:

1. A detailed report outlining key metrics, trends, and insights from the analysis.
2. A structured list of recommended changes to the campaign structure, supported by data-driven evidence.
3. A clear, actionable plan for implementing the recommended changes.
4. A presentation of the findings, including visual aids like charts and graphs.

Industry Best Practices and Standards:

• Adhering to Google Ads best practices, including A/B testing, data-driven decision-making, and performance optimization.
• Incorporating Google Ads best practices, such as testing hypotheses, monitoring performance, and adjusting strategies based on data.
• Following Google’s Ad Quality Guidelines and Ad Performance Recommendations.

Quality Expectations:

• The analysis must be thorough, using historical data spanning at least the past 12 months.
• The analysis should include a mix of quantitative and qualitative data, such as campaign performance metrics, A/B test results, and user feedback.
• The recommendations must be specific, actionable, and aligned with the organization’s business objectives.

Technical Considerations:

• Data collection: Use Google Analytics, Google Ads API, and other relevant tools to gather data.
• Data privacy: Ensure compliance with data protection regulations (e.g., GDPR, CCPA).
• Performance metrics: Focus on key performance indicators (KPIs) such as Click-Through Rate (CTR), Cost Per Click (CPC), Return on Ad Spend (ROAS), and conversion rates.

Scalability and Future Maintenance:

• Design the analysis process to be scalable, allowing for continuous monitoring and ad