Moana Glass is a handcrafted blown glass and giftware brand based in the United States. The business runs online advertising to drive bookings and sales, but performance was uneven and return on ad spend (ROAS) fluctuated over time. While traffic and inquiry volume were present, the connection between ad spend and confirmed bookings needed improvement in both consistency and efficiency.

CausalFunnel improved ad account performance by adopting a structured optimization cycle focused on data-driven adjustments, refined tracking, and strategic budget shifts. This helped increase ROAS month over month, strengthen campaign learning, and deliver the highest levels of efficiency late in the year.

Background & Problem

Moana Glass was investing in online advertising, but results were inconsistent and lacked a clear improvement. Although traffic and interest were present, revenue from confirmed bookings did not align with advertising costs, making it difficult to scale spend confidently.

The business needed a clearer picture of how advertising translated into real bookings, and how ad investments could be shifted toward what was genuinely driving revenue. Without this clarity, patterns of spend and return were hard to predict, and the efficiency of ad dollars varied across the months.

Case Study

The work began with a full performance review to understand overall trends and identify areas that could benefit most from systematic improvement. A structured cycle of testing and optimization was established, where adjustments were guided by historical change data and real performance insights.

New campaign assets were segmented to help clarify which audiences and messaging drove stronger interest. Budgets were regularly shifted toward areas showing higher return, and bid strategies were refined based on observed patterns of conversions and revenue outcomes.

A booking confirmation tracking setup was implemented using FareHarbor booking data, ensuring Google Ads could measure which ad clicks turned into real confirmed bookings rather than just website visits or low intent actions. 

This improved attribution accuracy and gave a clearer view of what was actually generating revenue. With confirmed booking data feeding into optimization, budget decisions became more precise and the account was able to scale what was working while steadily improving ROAS over time. From August onward, stronger performance became visible, culminating in the highest efficiency levels achieved in December.

How CausalFunnel AI Solved the Problem

CausalFunnel’s optimization framework centered on improving the quality and consistency of performance outcomes rather than just increasing traffic. By structuring regular tests, refining how assets were grouped, and reallocating budget to top performing areas, the account responded with greater consistency and stronger returns.

Improved tracking of confirmed bookings allowed the system to more accurately connect ad spend with revenue outcomes, which helped every adjustment make a stronger impact on performance. As reliable data improved, so did the ability of the system to build on prior gains and support steady growth.

Key Takeaway :

Moana Glass improved return on ad spend by structuring ongoing testing and optimization, refining conversion measurement, and shifting investment toward the highest returning activity. This approach delivered steadier performance improvement and stronger ROAS over time, with peak results late in the year.

Conclusion

For brands like Moana Glass, consistent growth requires clarity on how advertising connects to real revenue. By adopting a disciplined optimization cycle, improving tracking of confirmed bookings, and aligning spend with revenue-driving actions, CausalFunnel helped Moana Glass increase ROAS consistently and build a more reliable foundation for scaling future ad investments.