Executive Summary

Vinomofo is one of Australia’s largest online wine retailers. The brand’s strategy focuses on offering highly competitive deals on curated wines, often sold through mixed cases or specific wine collections.

Paid advertising is the brand’s main acquisition channel. While Vinomofo runs campaigns across both Meta and Google Ads, Meta is the primary driver of new customer acquisition, with Google Ads acting as a supporting channel.

BSD began working with Vinomofo in July 2025. Between September 2025 and February 2026, we redesigned the Meta account structure to improve scalability and allow Meta’s optimisation systems to operate more effectively.

Through this consolidation and the introduction of a structured testing framework, the account improved its acquisition efficiency significantly, reducing CAC by 23%.

The Challenge

In September, the Meta account structure was still too segmented, which limited the platform’s ability to optimise efficiently.

Within the multiple campaign setup, each SKU had its own ad set.

While this approach gave the team control over individual products, it restricted the way Meta’s optimisation system could work.

Because each product operated in its own ad set, Meta had limited opportunities to learn which combinations of products and creatives converted best. The algorithm was also less able to sequence multiple offers together in a conversion journey.

In practice, this meant the platform was often serving variations of the same product to the same audiences instead of presenting a broader range of offers.

This segmentation also made it more difficult to scale efficiently. Budget was spread across too many ad sets, preventing the algorithm from concentrating spend on the strongest performers.

As a result, the account struggled to consistently hit acquisition targets while maintaining the desired nCPA.

The Strategy: Account Consolidation

The core strategy to address this issue was Meta account consolidation.

Rather than continuing to separate products across many ad sets, the goal was to create an environment where Meta could optimise across multiple products, creatives, and audiences simultaneously.

By consolidating the account structure, Meta’s algorithm could:

Evaluate performance across a wider set of products
Sequence different offers together
Dynamically allocate budget to the strongest performers

Instead of structuring the account around product segmentation, we redesigned the account around performance tiers.

The New Meta Account Structure

The new structure centred around a single consolidated scaling campaign.

Within that campaign, ad sets were organised according to performance level rather than individual SKUs.

Best Performers

This ad set contained the highest-performing creatives and SKUs across the account. These ads had already proven their ability to acquire customers efficiently and therefore received the majority of campaign spend.

Rising Performers

This ad set contained creatives that showed strong early signals but had not yet reached the same level of efficiency as the best-performing ads.

Dedicated Scaling Ad Sets

For certain high-priority SKUs where additional creative production was expected, dedicated scaling ad sets were created. This allowed those products to scale independently without competing with other SKUs inside the main scaling pools.

Testing Ad Sets

New creatives were introduced through testing ad sets. This allowed the team to evaluate performance before promoting winning creatives into the scaling environment.

Creative Testing Framework

To support the new structure, we introduced a structured testing process.

New creatives were launched in testing ad sets and evaluated over a four to five day testing period. After this window, the best-performing creatives were promoted into the best performer or rising performer scaling ad sets.

This ensured that only proven creatives entered the core scaling environment.

However, because the campaign operated with campaign budget optimisation (CBO), testing ad sets could sometimes divert too much budget away from scaling ad sets. In other situations, testing ad sets received very little spend, making it difficult to evaluate new creatives.

To address this, spend guardrails were introduced for testing ad sets.

Initially, testing ad sets were limited to:

Minimum spend: 5%
Maximum spend: 10%

As the campaign scaled further, these limits were refined to:

Minimum spend: 4%
Maximum spend: 8%

This ensured that new creatives received enough budget to be tested properly while protecting the stability of the scaling ad sets.

🚀 Results

The structural consolidation quickly improved acquisition efficiency.

As the new structure was implemented and optimised, performance improved significantly.

Below is the comparison between Vinomofo’s monthly targets and the results achieved between September 2025 and February 2026.

Month	Relative New Customers	Relative CAC Reduction
September	0%	0%
October	+16%	-22.78%
November	+93%	-37.97%
December	+56%	-26.58%
January	-6%	-30.38%
February	+12%	-22.78%

November and December are traditionally peak demand periods for the wine category due to Black Friday promotions, holiday gifting, and Boxing Day sales.

During November, the account delivered one of its strongest results:

Exceeding target new customers by 37%, achieving a record high.

Equally important was the performance during January and February, which are typically slower months following the holiday period.

Despite the seasonal slowdown, the account still exceeded new customer targets while maintaining efficient acquisition costs.

By the end of the case study period, the average nCPA had stabilised representing a 23% improvement compared to the September baseline.

Why the Strategy Worked

The success of this transformation came down to one core principle: account consolidation.

By reducing unnecessary segmentation, Meta’s algorithm gained access to a much broader set of performance signals. This allowed the platform to allocate budget more effectively, sequence multiple offers together, and identify stronger conversion paths.

At the same time, the volume of creatives increased significantly. While this provided more assets for the algorithm to evaluate, the new account structure ensured that these creatives could also be tested far more efficiently than before. Instead of creatives being siloed within individual SKU ad sets and receiving limited spend, the consolidated structure allowed new assets to be evaluated within a larger optimisation environment.

In addition, the creative mix improved. Previously, the account was heavily indexed toward static formats, whereas the current structure supports a much healthier balance between static and video creatives, giving Meta more diverse signals to optimise delivery.

Together, the consolidated account structure and the improved creative testing framework created a scalable acquisition system capable of maintaining efficient customer acquisition even as spend increased.