This case study illustrates the necessity of precise PPC knowledge and experience when managing an e-commerce store that advertises across multiple platforms, such as Google and Meta (Facebook/Instagram). The implementation of granular, channel-specific control was crucial for moving beyond profit-burning automation to achieving 124% profit growth and safely scaling ad spend by over 50%.

The Challenge: Automated Systems and Profit Burn

The e-commerce store initially operated with a heavy reliance on automated campaign structures, characterized by a Pmax heavy setup on Google. While automation can simplify management, it creates severe scaling hurdles in a multi-channel environment:

1. Remarketing Cost Multiplication: When utilizing automated systems like Google Pmax and Facebook ASC simultaneously, the remarketing cost inevitably multiplies. Without proactive omnichannel control, these systems operate independently and can spend repeatedly on the same user until that user either purchases or exits the conversion window, effectively burning through profit.
2. Misleading ROAS Metrics: Google’s Pmax campaign type achieves its target ROAS by attempting to spend heavily on brand keywords. This strategy inflates the platform’s reported return, but it does not take into account that the user may have searched for the brand only because money was already spent to influence them on another platform, such as Facebook. Therefore, the high ROAS achieved through brand keywords cannot accurately be averaged with the cost of acquiring new customers, as the search was not solely attributable to Google’s efforts.

The Strategy: Regaining Omnichannel Control

To scale the business without seeing ROI or ROAS decrease and while keeping the CPA stable, the operator determined they must regain control over ad spend. This required precise knowledge to segment spending based on user intent and prior interaction across both Google and Facebook.

1. Strategic Shift on Google Ads (Pmax Reduction):

The setup was fundamentally altered over five months, moving from a Pmax-heavy focus to a Standard Shopping and Search heavy approach. This is evident in the spend distribution: Pmax spend dropped from 4.5M in June to 1.9M in December, while Shopping spend rose from zero (implicit) to 5.8M in December.

This precise shift enabled two critical controls:

• Keyword Exclusion: It became possible to exclude brand and brand+product-name specific keywords from the main scale campaigns.
• Targeted Brand Campaigns: A separate campaign was designated solely for brand keywords. Since these users had already been exposed to the brand (often via initial spending on another platform), this dedicated campaign was set up with a much higher target ROAS.

2. Strategic Segmentation on Meta/Facebook:

A similar level of segmentation was applied to Facebook spending:

• Separate Campaigns: Spending was clearly delineated between prospecting campaigns and remarketing campaigns.
• Audience Granularity: Remarketing audiences were further divided into warm audiences (those who engaged somehow with the product or brand) and hot audiences (post-purchase users).

The Result: Profitability and Scalability

The implementation of these precise PPC controls delivered significant results, particularly in safely enabling large-scale spending increases:

The ability to finely segment spend ensured that the store maintained control, allowing the overall system to perform profitably. Prospecting campaigns could run at a lower ROAS (often 2-3x) because the system was sure that the user would receive only one subsequent, low-cost exposure via a brand campaign on Google (shopping or search). The high ROAS generated by the dedicated brand campaigns (up to 6–10x ROAS) would then average out the overall target ROAS across multiple channels.

This precise control is especially vital for brands where the Average Order Value (AOV) is greater than $45, as users typically deliberate before purchasing and often do not convert instantly from the first Facebook advertisement.

Conclusion: The Importance of Precise Measurement and Knowledge

The success of this scaling strategy hinged entirely on the precise PPC knowledge required to manipulate and segment automated platforms, preventing them from self-cannibalizing profits.

Crucially, sustaining this level of control required advanced measurement capabilities—specifically, an external tool capable of server-side measuring every conversion and tracking the impact of all video views, engagements, and clicks across all paid and organic channels.

Furthermore, precise PPC experience ensured continuous testing of static and video creatives (critical for Facebook) and applying successful creatives to YouTube and TikTok campaigns, mitigating creative fatigue. Even minor UX changes on the storefront (like elevating reviews or optimizing variant selection) were integrated to support the conversion rate required for maximum campaign efficiency. Without this precise, experienced control, the massive scaling efforts undertaken leading up to Black Friday would have likely eroded profit margins instead of increasing profit by 124%.