Two key strategies were employed in this case study:

• A consolidated, gender-focused broad asset group featuring top-performing images, videos, and copy. This enables Google to scale broadly across audiences.
• Highly targeted, gender-focused campaigns with specific in-market or interest segments for particular product types. This allows for flexibility in focusing on trending or well-performing products.

I used targeted signals and focused creative content for specific campaigns while employing broader signals for gender-focused campaigns. Working with a substantial budget, multiple asset groups were tested concurrently to optimize performance.

Additionally, custom customer list asset groups without images or videos were tested to focus on shopping and search campaigns. In this case, shopping campaigns performed well, but required dedicated budget allocation. Testing was conducted on women's products that had already been purchased, leveraging existing customer data.

While results can vary across accounts, testing found that including images and videos generally performed better.

Men's product campaigns aimed for a cost-per-sale of $70, achieving approximately 1x ROAS, which proved effective for retargeting.

Testing involved seven active campaigns and nearly 20 different ads. Professional content featuring prominent influencers demonstrated consistent long-term performance, while short-form videos worked better in shorter bursts.

Cold audience testing for men involved targeting competitor audiences, market segments, and specific custom segments. Matching creative content to targeted demographics remained a key principle. We maintained campaign effectiveness by continually refreshing creative assets and maintaining close collaboration with the client's social media team.

These platforms provided higher-performing creative placements directly controlled by Google, ensuring better quality compared to potentially unreliable third-party website banners.

I observed significantly higher conversion rates with these campaign types. I reviewed top-performing Meta creative content to experiment and scale within the Google ecosystem, allowing them to capture additional sales that Performance Max might have overlooked.

By testing successful Meta creative in Google's environment, the aim was to demonstrate overall conversion potential and consequently boost flagship Performance Max campaigns. Various experiments were conducted using different types of creative within individual campaigns. Those mirrored strategies from Performance Max.

These strategies included:
• Remarketing to re-engage users who previously interacted with brand content
• Targeting specific in-market segments to reach users actively researching relevant products
• Utilizing gender-focused strategies to deliver tailored content

By replicating proven Performance Max strategies in demand generation campaigns while leveraging Google's premium placements, we established a cohesive cross-platform approach. This method maximized ad exposure while maintaining high-quality interactions, ensuring efficient budget allocation and improved overall campaign synergy.