You work at an agency and one of your clients wants to track performance by product category (ex: apparel) and gender. They already passed the optional and required attributes for apparel in the product feed. How could they achieve granular reporting?
- Create a catch-all campaign. Example: Campaign #1: Tops Product group: All products
- Create a campaign by product category and gender, and use product groups. Example: Campaign #1: Women’s Top Product group #1: Sweater Product group #2: Short Sleeves
- Create a campaign for each gender, then set up product groups by apparel type. Example: Campaign #1: Women Product group #1: Tops Product group #2: Shoes
- Create a campaign by product category, then set up product groups by gender. Example: Campaign #1: Tops Product group #1: Women’s Top Product group #2: Men’s Top
Explanation:
The correct answer is to **Create a campaign by product category and gender, and use product groups**. By creating a campaign for each product category and gender and utilizing product groups within each campaign, the client can achieve granular reporting tailored to their specific tracking needs. This approach allows the client to segment their products by both category (e.g., apparel) and gender (e.g., women) within individual campaigns, enabling them to track performance metrics such as impressions, clicks, and conversions at a more detailed level. For example, within the ‘Women’s Top’ campaign, the client can create product groups for different types of tops (e.g., sweaters, short sleeves) to further refine their reporting and analyze the performance of each product segment. This granular reporting structure provides valuable insights into the effectiveness of marketing efforts for specific product categories and audience segments, facilitating data-driven decision-making and optimization strategies to improve overall campaign performance. Therefore, selecting **Create a campaign by product category and gender, and use product groups** accurately reflects the approach that allows the client to achieve the desired level of granularity in reporting while leveraging the existing product feed attributes for apparel.