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?
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
Explanation
Analysis of Correct Answer(s)
The recommended structure, creating a campaign by product category and gender (e.g., Campaign: "Women's Top"), provides the highest level of control and the most granular reporting.
- Dedicated Budgets and Settings: By creating a specific campaign for "Women's Top," you can set a unique budget, location targeting, and campaign-level negative keywords that are only relevant to that specific segment. This is more effective than grouping all tops into one campaign.
- Maximum Granularity: This approach allows for the most detailed performance analysis. You can easily compare the overall performance of "Women's Tops" against "Men's Tops" because they are in separate campaigns.
- Further Subdivision: Within this highly specific campaign, you can then use product groups to subdivide even further by attributes like product type ("Sweater," "Short Sleeves"), brand, or custom labels for precise bid management.
Analysis of Incorrect Options
- Create a campaign by product category, then set up product groups by gender: While this structure allows for reporting by gender within the "Tops" category, both men's and women's tops would share the same campaign budget and settings. This offers less control than creating separate campaigns.
- Create a campaign for each gender, then set up product groups by apparel type: This is similar to the previous incorrect option. It allows for reporting but forces different product categories (e.g., "Tops" and "Shoes") to share the same budget and settings within the "Women" campaign, which is not ideal.
- Create a catch-all campaign: This is the least effective strategy. Grouping all products into a single product group within one campaign makes it impossible to set different bids or analyze performance by category or gender, directly contradicting the client's goal for granular reporting.