Google Performance Max Updates Focus On Planning Media, Custom Assets, Results

Google announced updates on Wednesday to Performance Max to help advertisers further improve their campaigns and drive stronger results, starting with this holiday season.

The Performance Max features announced today meet business goals in three key areas:

  • Plan campaigns more efficiently
  • Customize asset strategy
  • Evaluate results

Among the latest updates announced today, Google has brought Performance Planner to Performance Max campaigns to help advertisers forecast and simulate how campaigns may perform based on changes made. Advertisers can forecast how campaigns may perform and simulate what could happen when campaign budgets and return on ad spend (ROAS) or cost per acquisition (CPA) targets are adjusted.

Performance Planner’s forecasts are adjusted for seasonal events, so marketers can explore potential holiday opportunities when it rolls out in the upcoming weeks. 

Google also increased the number of text headlines advertisers can upload from five to 15, and added the ability to add automated rules to asset groups to help with asset management and quality control. 

Advertisers now have an option to leverage first-party audience insights through adding their own company data segments to audience signals, and use explanations to better understand what drives performance fluctuations. 

Google, which bases its advertising systems on automation and machine learning, estimates that 54% of shoppers used five or more channels — like search, video, and social media — to shop during a two-day holiday period. To manually keep track of all the data is nearly impossible.

Explanations now are available for all Performance Max campaigns, but there are some new explanations specifically in Performance Max campaigns for online sales with a product feed. For example, marketers may see explanations that offer analysis on product status and top-moving products, listing groups, and product types.

Google explains that a retailer could use these to understand the products that saw the biggest changes in performance during the holiday shopping season. 

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