Australian regulated beverage e-commerce retailer

Platform

Google Ads

Focus

Performance Max, Search, Shopping, policy-restricted advertising, conversion signal building, ROAS growth

The challenge

An Australian e-commerce retailer came into Google Ads with a common but frustrating problem: they were struggling to get the account above a 3x ROAS.

The business had strong products and a clear market, but the ad account was not consistently producing the level of return needed to scale confidently.

There was another layer of complexity.

The client operated in a tightly controlled advertising category. That meant Google Ads policies were not just a small technical hurdle. They directly affected campaign approvals, asset eligibility, targeting, and the ability to scale.

The account needed more than basic campaign management.

It needed a strategy that could work within policy restrictions, build stronger conversion data, and train Google’s algorithm with enough purchase signals to make Performance Max more effective.

The strategy

The strategy started before launching the strongest Performance Max campaign.

The account first needed enough conversion volume to give Google better data. Before relying heavily on Performance Max, the goal was to get the account to a minimum of 30 conversions in a 30-day window.

That step mattered because Performance Max is highly dependent on conversion signals. Without enough clean purchase data, it can struggle to understand who to target, which products to prioritize, and which users are most likely to buy.

Once the account had stronger conversion volume, Performance Max was introduced and refined over multiple campaign builds.

The current top-performing campaign was the third Performance Max campaign built for the account. Each version helped improve the next one by giving the account more data, clearer product signals, and stronger performance history.

The campaign strategy focused on:

1. Building enough conversion volume before scaling Performance Max

2. Using previous campaign data to train future campaigns

3. Prioritizing top-performing product categories

4. Navigating policy restrictions inside a regulated ad account

5. Testing promotional offers around key seasonal moments

6. Using product and category performance to guide budget decisions

The top product categories became mixed red and white case offers, with additional holiday-focused red wine promotions supporting performance during key shopping periods.

The results

For the January 1–June 9 year-over-year comparison window, the Google Ads account showed strong performance growth.

At the total account level, Google Ads reported:

A$216,328.10 in revenue

1,236.02 website purchases

11.09x conversion value over cost

556.87 new customers

5.29% conversion rate

84.39% increase in website purchases year over year

90.32% increase in revenue year over year

The strongest Performance Max campaign reported:

A$199,434.88 in revenue

1,120.78 website purchases

12.03x conversion value over cost

523.08 new customers

During the optimization period, Google Ads reporting also showed ROAS reaching as high as 13.56x in review windows.

What changed

The biggest shift was moving from isolated campaign launches to a staged data-building strategy.

Instead of expecting Performance Max to work immediately, the account was built toward it.

The process looked more like this:

1. Strengthen conversion volume.

2. Build cleaner purchase signals.

3. Launch Performance Max once the account had enough data.

4. Use each campaign version to improve the next.

5. Focus budget around the products and categories proving the strongest purchase intent.

This helped the account move beyond the original 3x ROAS ceiling and into a much stronger return range.

The takeaway

Performance Max works best when it has the right data going into it.

For this e-commerce account, the win was not just launching a PMax campaign. The win was building the account to a place where PMax had enough conversion signals to perform.

This case study shows why e-commerce ad strategy is not only about picking the right campaign type. It is about timing, product focus, policy navigation, conversion volume, and using past performance to train better future results.