Analyzing Ad Performance for an Online Gadget Shop

Executive Summary

This case study investigates the performance of ad campaigns for an online retailer specializing in consumer goods, focusing on fitness tracker products. Using SQL for business intelligence, the analysis identifies top-performing ad types and product categories that maximize Return on Ad Spend (ROAS). Key findings reveal the most profitable product and ad type combinations, providing actionable insights for optimizing ad spending and refining campaign strategies.

Problem Statement

The retailer seeks to optimize ad spending across various product categories and ad types to achieve higher ROAS and more efficient budget allocation. By analyzing historical ad campaign data, the retailer can identify which ad types and products yield the best performance, enabling data-driven decisions for future campaigns.

Approach

Data Collection & Preparation: The dataset includes ad campaign details such as product category, ad type, total ad spend, click-through rate (CTR), and ROAS. This data was organized for efficient SQL querying and analysis.

Descriptive Analytics: SQL was used to aggregate ROAS by product category and ad type, and to compute key performance indicators (KPIs) such as CTR, total ad spend, and conversion rate for each campaign.

Customer Segmentation & Performance Metrics: The data was segmented by ad type and product, allowing for an in-depth analysis of which segments generated the highest ROAS. Individual product performance was assessed by ROAS to identify the most effective ad strategies by product category.

Results

Product & Ad Type Performance

Top Product by ROAS: Air Purifier, with a ROAS of 69.53

Revenue Leader: Fitness Trackers, generating $91,895.31 and a ROAS of 64.47

Ad Type Performance:

• Search Ads: Highest ROAS at 58.88 and $236,138.60 in revenue, indicating strong intent from search-driven customers.
• Display Ads: Slightly lower ROAS at 54.58, but substantial revenue generation at $191,373.20.

Product-Level Analysis for Fitness Trackers

High Performers:

• Mi Smart Band 5: ROAS of 98.73, showing high ad efficiency.
• Mi Band 7: ROAS of 92.14, also a strong performer.

Low Performers:

• Mi Band 3: ROAS of 49.34, indicating low ad spend effectiveness.

Visualization

Take a closer look at the data visualizations below:

Strategic Insights

• Ad Spend Optimization: Reallocate the ad budget to prioritize top-performing products (Air Purifiers, Fitness Trackers) and focus on ad types that yield the highest ROAS. For example, prioritize Search Ads for Mi Smart Band 5 and Display Ads for Mi Band 6.
• Product Strategy: Invest more in high-ROAS products, like Mi Smart Band 5 and Mi Band 7, and reassess ad spending for lower ROAS items like Mi Band 3. This strategy will maximize the effectiveness of ad campaigns.
• Campaign Targeting: Focus Search Ads on products with higher conversion rates, leveraging customer intent. Use Display Ads for products with high margins, aligning ad format with performance metrics.

Recommendations

• Budget Reallocation: Concentrate the ad budget on Air Purifier and Fitness Tracker categories, as these products have the highest ROAS, suggesting a better return on investment.
• Enhanced Ad Strategy: Emphasize Search Ads for Mi Smart Band 5 and Display Ads for Mi Band 6 to drive higher returns and maximize margins.
• Ongoing Evaluation: Regularly monitor product performance using ROAS and conversion metrics, allowing for dynamic budget adjustments to sustain efficient ad spending.

Conclusion

By implementing these strategies, the retailer can optimize ad spending, enhance campaign effectiveness, and drive profitability through data-informed decisions. Prioritizing high-ROAS products and ad types will lead to more efficient marketing investments, ultimately increasing the return on each advertising dollar spent.