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• 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 catch-all campaign. Example: Campaign #1: Tops Product group: All products
• 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
• 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

The correct answer is: 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

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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 required and optional attributes for apparel in the product feed. Which of these techniques could help them achieve granular reporting?

You work at an agency and manage several retail accounts in Google Ads. One of your clients is new to Shopping Ads and would like to track performance by product category (ex: apparel) and gender. The client is passing the required and optional attributes for apparel in the product feed. Which recommendation would you make to their campaign structure to achieve granular reporting?