Google Ads Shopping Campaigns for Australian Ecommerce: How to Set Up, Optimise, and Scale Product Listing Ads in 2026
Australian ecommerce retailers collectively spend hundreds of millions of dollars on Google Shopping ads every year. A significant portion of that budget is wasted, not because Shopping ads do not work, but because most accounts are built on poor product feed quality, incorrect Merchant Centre configuration, and campaign structures that make optimisation nearly impossible. The retailers who get Shopping right are not spending more. They are spending smarter.
If you run an online store in Australia and you are not treating your product feed as your most important paid media asset, you are leaving money on the table every single day. Google uses your feed to decide when your ads appear, which search queries trigger them, and how prominently your products are shown. A poorly structured feed is the equivalent of handing Google a blurry map and asking it to drive customers to your door. Google Ads Shopping campaigns for Australian ecommerce require a level of technical discipline that most agencies and in-house teams simply do not apply.
This guide covers everything you need to know to build, optimise, and scale Shopping campaigns that generate measurable revenue in the Australian market. We will cover Google Merchant Centre setup for Australian stores including GST and AUD compliance, product feed optimisation, the real trade-offs between Standard Shopping and Performance Max, bidding strategies that work at scale, and how to structure campaigns by product margin. We will also share real results from accounts we have managed, because activity reports without revenue outcomes are not useful to anyone.
Key Takeaways
Feed optimisation is the single highest-leverage activity in any Shopping campaign. Better titles, GTINs, and product data can reduce CPC by 30 to 50 percent and dramatically improve ad relevance.
Google Merchant Centre has specific requirements for Australian retailers that catch many accounts out, particularly around GST display, AUD pricing, and domestic shipping zones.
Standard Shopping gives you control. Performance Max gives you reach. The right choice depends on your account maturity and how much data you have to feed Google's algorithm.
Target ROAS bidding works, but only after you have accumulated sufficient conversion data. Rushing into tROAS with thin data destroys performance.
Campaign structure by product margin, not just product category, is the approach that separates profitable Shopping accounts from ones that look good on paper but erode margins.
Attribution matters. Last-click attribution in Shopping significantly undervalues upper-funnel product impressions and will cause you to underbid on your best-performing products.
Shopping Campaign Types at a Glance
Campaign Type | Control Level | Best Use Case | Minimum Spend Recommendation | Key Trade-Off |
Standard Shopping | High | Accounts with clear margin segmentation and established data | $1,500/month AUD | Requires active management; no audience expansion |
Performance Max | Low to medium | Accounts with 50+ conversions/month; broad catalogue coverage | $3,000/month AUD | Limited transparency; strong automation when data is rich |
Local Inventory Ads | Medium | Retailers with physical stores in Australian suburbs | $1,000/month AUD | Requires in-store inventory feed; more complex setup |
Smart Shopping (legacy) | Low | No longer available; replaced by Performance Max | N/A | Fully deprecated by Google |
Why Shopping Ads Are the Highest-Intent Paid Channel for Ecommerce
When someone types "running shoes size 10 men Brooks Ghost" into Google, they are not researching. They are buying. Shopping ads capture that intent at the exact moment a purchase decision is being made, which is why they consistently outperform standard text ads for ecommerce revenue when managed correctly.
Google Shopping ads appear at the top of search results with a product image, price, store name, and ratings. That visual format does something text ads cannot: it pre-qualifies the click. If your price is visible and the shopper still clicks, they are already aware of what they will pay. That is a fundamentally warmer lead than someone who clicks a text ad without knowing the price point.
For Australian ecommerce specifically, the numbers support this channel. Statista data shows Australian ecommerce revenue is projected to exceed $64 billion AUD in 2026, with paid search, including Shopping ads, accounting for a significant portion of acquisition spend for mid-market and enterprise retailers. The category is growing, competition is intensifying, and the retailers who invest in feed quality and campaign architecture now will build a structural advantage that is hard for competitors to replicate quickly.
High-intent search behaviour is where our clients consistently find the best return on ad spend. When I audited the Google Ads account for a Queensland-based building and pest inspection business, the problem was not that Shopping or search ads were not working in principle. The problem was that the account was attracting traffic from postcodes the business could not even service. The targeting was broad, the feed data was thin, and the campaign structure made it impossible to isolate what was actually performing. After restructuring the account, removing non-serviceable area traffic, and aligning campaigns to genuine high-intent search behaviour, the account generated 574 additional leads over six months, cut cost per conversion by $37.93, and reduced average cost per click by $12.56. The client had to hire additional staff to manage the volume. That is what rigorous campaign architecture produces.
Setting Up Google Merchant Centre for Australian Stores
GST Compliance and AUD Pricing
This is where a significant number of Australian ecommerce accounts trip up from day one. Google Merchant Centre requires that the price you display in your feed exactly matches the price shown on your product page. For Australian retailers, that means displaying GST-inclusive prices, because Australian Consumer Law requires prices shown to consumers to include GST.
If your Shopify store shows prices inclusive of GST but your feed is pulling exclusive prices from a backend API, your Merchant Centre account will generate price mismatch disapprovals. Google's crawlers check your live product pages against your feed regularly, and discrepancies result in product disapprovals that silently kill your campaign reach.
When configuring Merchant Centre for an Australian store:
Set your target country to Australia and your currency to AUD.
Ensure your feed prices are GST-inclusive for all products sold to Australian consumers.
If you sell to both Australian and international customers, you may need separate feeds for separate target countries.
The ACCC's guidelines on price display should inform how you handle any promotional pricing in your feed. Struck-through "was" prices need to reflect genuine prior pricing to comply with Australian Consumer Law.
Shipping Configuration for Australian Zones
Australia's geography creates shipping complexity that many retailers configure poorly in Merchant Centre. Google uses your shipping settings to calculate estimated delivery dates shown in Shopping ads. Inaccurate shipping settings damage conversion rates because shoppers in Perth see delivery estimates that assume they are in Sydney.
Set up shipping tables that account for:
Separate rate zones for metro versus regional versus remote Australia. Australia Post and most third-party carriers have different rates and transit times for regional Queensland, the Northern Territory, and Western Australian regional centres compared to capital city metros.
Weight and dimension-based shipping rules if your products vary significantly in size.
Free shipping thresholds if you offer them, because Google can display a "Free Delivery" badge that materially improves click-through rates.
A common mistake is setting a single flat shipping rate nationally. It may simplify your feed but it inaccurately represents what customers in regional Australia actually pay, which damages trust when they reach checkout.
Returns Policy Requirements
From 2024, Google has increasingly factored returns policy data into Shopping ad quality signals. Australian retailers should configure their returns policy in Merchant Centre to reflect their actual policy. If you offer free returns, displaying that in your Shopping ads provides a competitive signal. If returns have a cost, configure that accurately. Merchant Centre now supports structured returns data including the return window, return method, and whether the cost is free or customer-paid.
Product Feed Optimisation: The Highest-Leverage Activity in Shopping
Product Titles: Where Most Retailers Lose
Google uses your product title as the primary signal to match your product to search queries. A poor title is the single most common cause of underperformance I see in Shopping audits. Most retailers write titles the way they would write them for their own catalogue: brand-first, creative, and brief. Google's algorithm does not care about creative. It cares about relevance.
A weak title: "Ghost 16" A strong title: "Brooks Ghost 16 Men's Running Shoes Size 10 Grey/Blue AUS"
The strong title front-loads the brand, includes the specific model, specifies the category, includes size and colour attributes, and signals the market. Every one of those elements is a matching signal Google uses to determine which searches trigger your ad.
Title optimisation formula for Australian retailers:
Brand + Product Type + Key Attributes (size, colour, material) + Model Number or SKU where relevant
For apparel: Brand + Gender + Product Type + Key Feature + Colour + Size
For electronics: Brand + Product Name + Model Number + Key Spec
For homewares: Brand + Product Type + Material + Colour + Dimensions
GTINs: Non-Negotiable for Branded Products
Global Trade Item Numbers (GTINs) are the barcodes that uniquely identify products. If you sell branded products, Google requires GTINs in your feed. Products without GTINs for branded items receive lower quality scores and are shown less frequently. More importantly, when you provide accurate GTINs, Google can match your products against its product knowledge graph, improving relevance matching and often reducing CPC because your Quality Score improves.
For products you manufacture yourself, GTINs are not required, but you should set the "identifier_exists" attribute to false in your feed. Leaving it blank or providing an incorrect value creates disapprovals.
Custom Labels: The Secret to Margin-Aware Campaign Structure
Custom labels are one of the most underused features in Google Shopping. They allow you to apply your own segmentation to products in your feed, which then lets you build campaign structures that reflect your business logic rather than just Google's product categories.
Useful custom label strategies for Australian retailers:
Margin tier: Label products as high-margin, medium-margin, and low-margin. This lets you bid more aggressively on products where every sale generates strong contribution margin.
Sale status: Label products that are currently on promotion. Promotional products often have higher conversion rates and warrant more aggressive bidding temporarily.
Seasonality: Label products that are seasonal to the Australian calendar (for example, summer outdoor furniture, winter heating products). You can then adjust budgets and bids to align with seasonal demand.
Stock level: Label low-stock products to prevent wasted spend on products you cannot fulfil. Nothing damages customer experience more than a Shopping ad that leads to an out-of-stock product.
New arrivals: Label new products that you want to gather data on quickly. You can create separate campaigns with specific budgets to accelerate data collection.
Supplemental Feeds
A supplemental feed allows you to override or add attributes to your primary product feed without changing the primary feed itself. This is particularly useful when your ecommerce platform generates a feed that you cannot fully control. Common uses include adding custom labels, correcting titles at scale, or adding promotional text.
For Australian retailers using Shopify, BigCommerce, or WooCommerce, apps like GoDataFeed, DataFeedWatch, and Feedonomics allow you to build supplemental feeds with rules-based logic. These tools are worth the investment if your catalogue has more than 500 SKUs or if your primary feed is generated from a legacy ERP system that does not produce Shopping-ready output.
Standard Shopping vs Performance Max: When to Use Each
This is the question I am asked more than any other in Shopping campaign management right now. The honest answer is that both have their place, and the right choice depends on the maturity of your account and the quality of your data.
Standard Shopping: Control and Transparency
Standard Shopping campaigns give you explicit control over bidding at the product group level, search term visibility through a search terms report, and the ability to sculpt which queries trigger your ads through negative keywords. For accounts that are earlier in their data accumulation journey, or for accounts where margin segmentation is critical, Standard Shopping remains the superior choice.
Standard Shopping is the right choice when:
Your account has fewer than 50 conversions per month across Shopping campaigns.
You have distinct product margin tiers that require different bidding logic.
You are in a competitive category where search term visibility and negative keyword management are critical to profitable scaling.
You want to test specific product groups against each other with clean data separation.
Performance Max: Reach and Automation at Scale
Performance Max (PMax) replaced Smart Shopping in 2022 and has continued to evolve as Google's primary vehicle for automated campaign management. PMax uses Google's machine learning to serve ads across Search, Shopping, Display, YouTube, Gmail, and Maps from a single campaign. The automation is genuinely powerful when it has sufficient data to learn from.
The major limitation of PMax for Shopping-focused retailers is visibility. You get very limited search term reporting, which makes it difficult to identify wasted spend or to build a meaningful negative keyword list. Google has incrementally improved reporting in PMax, but as of 2026 it remains significantly less transparent than Standard Shopping.
Performance Max is the right choice when:
Your account generates 50+ conversions per month from Shopping and you have consistent revenue data.
You have a broad catalogue where manual product group management in Standard Shopping becomes operationally difficult.
You have strong creative assets (images, videos, headlines, descriptions) to feed the algorithm across channels.
You want to capture demand across Google's full network, not just Shopping placements.
One practical approach that works well for Australian mid-market retailers: run Standard Shopping for your highest-margin products where control matters most, and run PMax for broader catalogue coverage on mid-tier and lower-margin products. This hybrid structure gives you the transparency you need where it counts and the reach automation provides where margin pressure is lower.
Bidding Strategies That Work for Australian Ecommerce
The Data Threshold Problem
The most common mistake I see Australian retailers make with Shopping bidding is rushing into Target ROAS (tROAS) before they have sufficient conversion data. Google's bidding algorithms need a minimum of 50 conversions in a 30-day window to function reliably. Below that threshold, tROAS will often cause Google to either underbid (starving your ads of impressions) or overbid erratically, burning budget on low-quality clicks.
The recommended progression for Shopping bidding:
Maximise Clicks (initial phase, 30 to 60 days): Get your products in front of buyers, collect conversion data, and identify which products actually convert. Set a maximum CPC cap to prevent overspending on high-competition products.
Target ROAS (once you have 50+ conversions per month): Set an initial tROAS target that is achievable based on your historical data. Do not set an aspirational ROAS immediately. If your account has been running at 300% ROAS, set the target at 250 to 280% initially, then raise it incrementally as the algorithm adapts.
Maximise Conversion Value (alternative to tROAS): If your conversion data is sufficient but your ROAS varies widely across product categories, Maximise Conversion Value without a ROAS target can sometimes outperform tROAS by giving the algorithm more flexibility.
Australian ROAS Benchmarks by Vertical
These are indicative benchmarks based on our experience managing Shopping campaigns for Australian ecommerce clients. They are not guarantees, and your specific catalogue, margins, and competitive landscape will influence your actual results:
Apparel and footwear: 200 to 350% ROAS
Home and garden: 250 to 450% ROAS
Consumer electronics: 300 to 600% ROAS (lower margins but high transaction values)
Sports and outdoor: 200 to 400% ROAS
Beauty and health: 300 to 500% ROAS
Automotive parts and accessories: 400 to 700% ROAS
If you are running at significantly below these benchmarks, the issue is almost always feed quality, campaign structure, or attribution (which we will cover shortly), not the channel itself.
Structuring Campaigns by Margin and Product Category
Most Australian retailers structure their Shopping campaigns by product category because that is the intuitive way to organise a catalogue. It is not the most profitable way.
The correct principle: your bid should reflect the profit you make on a sale, not just the revenue. A $500 product with a 10% gross margin ($50 contribution) should be bidding very differently to a $200 product with a 60% gross margin ($120 contribution). When you structure campaigns purely by category, you blend high-margin and low-margin products under the same bidding logic and optimise toward revenue, not profit.
Margin-aware campaign structure:
Tier 1 (high margin): Products with gross margin above 50%. Aggressive tROAS targets that reflect margin (for example, a $200 product with 60% margin warrants a higher tROAS target because there is more room to spend on acquisition).
Tier 2 (mid margin): Products with gross margin of 25 to 50%. Moderate tROAS targets.
Tier 3 (low margin or clearance): Products with gross margin below 25%. Conservative bidding or manual CPC caps. Consider whether these products should be advertised at all.
New products (no data): Isolated campaign with Maximise Clicks and a CPC cap to collect data without distorting your established campaigns.
This structure requires custom labels in your feed (as described above) and a willingness to invest in setup time upfront. The payoff is a Shopping account that grows revenue and profit simultaneously rather than just chasing revenue metrics.
Negative Keywords and Search Term Sculpting
Negative keywords in Shopping campaigns work differently to search campaigns. You cannot see every query that triggers a Shopping ad, but you can build a negative keyword list that prevents irrelevant queries from consuming budget.
For Australian retailers, common negative keyword categories to build from day one:
Competitor-specific terms where you do not want to appear against competitors with significantly lower prices.
DIY and how-to queries that indicate research intent rather than purchase intent (for example, "how to install", "DIY guide", "tutorial").
Wholesale and trade queries if you sell direct to consumer and do not have trade pricing.
Used, second-hand, refurbished if you only sell new products.
Non-serviceable locations if your products have geographic limitations.
Add negative keywords at the campaign level for broad exclusions and at the ad group level for more specific sculpting. Review your search terms report weekly during the first 90 days of a campaign and monthly after that.
Measuring True ROAS With Proper Attribution
This is the section that most Shopping campaign guides skip over, and it is genuinely important. If you are measuring Shopping performance on last-click attribution in Google Ads, you are almost certainly making bidding decisions based on inaccurate data.
Shopping ads, particularly for products with longer consideration cycles, contribute to purchase journeys that span multiple touchpoints. A customer might click a Shopping ad, visit your store, leave, see a remarketing ad, and then convert through a branded search. Last-click attribution gives 100% of the credit to the branded search and zero to the Shopping ad that initiated the journey. This causes you to underbid on Shopping and overbid on branded search.
For Australian ecommerce retailers, we recommend:
Data-driven attribution (DDA): Google's DDA model distributes credit across touchpoints based on observed conversion paths. It is available in Google Ads when you have sufficient conversion data and it is materially more accurate than last-click for Shopping.
Cross-channel attribution in GA4: Google Analytics 4 provides path analysis tools that show you how Shopping ads contribute to multi-touch conversion paths. Connect your GA4 property to Google Ads and use the attribution comparison tool to understand the gap between last-click and data-driven values for your Shopping campaigns.
Revenue tracking accuracy: Ensure your conversion tracking captures actual revenue values, not just conversion events. Shopping optimisation without revenue data forces Google's algorithm to optimise for the wrong objective. Verify your conversion values match your actual order values at least monthly.
Our analytics services are specifically designed to close this attribution gap for ecommerce retailers who are making budget decisions based on incomplete data. Getting attribution right is not optional if you want to scale Shopping profitably.
Case Study 1: Ecommerce Retailer, Product Feed Overhaul
A mid-sized Australian home goods retailer came to us with a Shopping account that had been running for 18 months. The account was spending approximately $12,000 AUD per month and returning a reported ROAS of around 280%. The business owner felt the account had plateaued and wanted to scale.
When I audited the account, the feed was the immediate problem. Product titles were brand-first and brief. Only 40% of branded products had GTINs. There were no custom labels, so all products were bidding under a single campaign with no margin segmentation. Attribution was on last-click.
Over 90 days we rebuilt the feed using DataFeedWatch, applied GTIN data across the catalogue, rewrote titles using our optimisation formula, introduced margin-tier custom labels, restructured into three margin-segmented campaigns, and moved to data-driven attribution. We also added 312 negative keywords in the first 30 days of the new structure.
At the 90-day mark: average CPC had dropped by 34%, ROAS (measured on data-driven attribution) increased to 420%, and monthly revenue from Shopping grew by 67% on roughly the same budget. The retailer then increased their Shopping budget by $5,000 per month, knowing the underlying infrastructure would support profitable scaling.
Case Study 2: Scaling a Seasonal Ecommerce Brand
An Australian outdoor and adventure retailer had strong seasonal sales (summer camping and hiking products) but struggled with Shopping performance during their peak period. Their previous agency had run a single Standard Shopping campaign with no seasonal logic, resulting in budget exhaustion during peak demand and wasted spend during off-peak months.
We implemented a seasonal custom label structure, identified the top 80 SKUs by historical revenue and margin, gave those products dedicated campaigns with higher budget caps and tROAS targets calibrated to their actual margin, and created a separate "catalogue clearance" campaign for end-of-season lines with conservative bidding.
During their following peak summer period, the account achieved a 512% ROAS across their top-tier campaign, a 38% improvement on the prior year peak. More importantly, the clearance campaign moved old stock at a positive return rather than the retailer resorting to offline discounting. The client attributed this to having the right campaign architecture in place before peak demand, not scrambling to fix it during peak.
What Our Clients Say
"Before working with 3P Digital, our Shopping campaigns felt like a black box. We were spending a significant amount each month and seeing some returns, but we had no real understanding of which products were actually profitable and which were draining budget. The feed overhaul and campaign restructure they did changed everything. We now have full visibility into margin performance by product tier, and our ROAS has held above 400% for six consecutive months. The transparency and the results are both better than anything our previous agency delivered."
Ecommerce Director, Australian home goods retailer (name withheld for confidentiality)
Need Help With Your Shopping Campaigns?
If you are an Australian ecommerce retailer investing in Shopping ads and you are not confident your campaigns are structured for profitable scaling, the best starting point is a structured audit. Our paid media team conducts Shopping audits that cover feed quality, campaign structure, attribution accuracy, and bidding strategy, and we present findings with specific, prioritised recommendations tied to revenue impact.
We operate on a pay-per-performance model because we only succeed when you succeed. If Shopping campaigns are not growing your revenue, our model does not reward us for managing them. That alignment is why our clients get results rather than activity reports.
You can also explore our ecommerce SEO services for building organic traffic that compounds over time, and our conversion rate optimisation services to ensure the traffic your Shopping ads send actually converts at your highest possible rate. Shopping ads drive the click. CRO determines whether that click becomes a customer.
View our case studies for detailed results across our client portfolio, or contact us to discuss your ecommerce paid media situation directly.
FAQs
How much does it cost to run Google Shopping ads in Australia?
There is no minimum spend requirement set by Google, but in practice, Shopping campaigns need sufficient budget to gather conversion data before automated bidding strategies can function effectively. For Australian retailers entering the channel, a realistic starting budget is $1,500 to $3,000 AUD per month. That is enough to generate meaningful data across a mid-sized catalogue within 60 to 90 days. Retailers with large catalogues or highly competitive categories (electronics, apparel) will typically need higher budgets to achieve coverage across their priority products.
Why are my products disapproved in Google Merchant Centre?
Disapprovals are most commonly caused by four issues for Australian retailers. First, price mismatches between your feed and your live product pages, often driven by GST-inclusive versus exclusive pricing inconsistencies. Second, missing or incorrect GTINs for branded products. Third, landing page issues where your product URL returns an error or redirects incorrectly. Fourth, policy violations, which include pricing that does not comply with Australian Consumer Law or products in restricted categories (certain health products, weapons, and financial products have specific requirements). Check the Diagnostics tab in Merchant Centre for specific disapproval reasons and resolve them systematically.
Does Performance Max cannibalise my Standard Shopping campaigns?
Yes, it can, and this is a real issue for accounts running both campaign types simultaneously. Google's general rule is that Performance Max takes priority over Standard Shopping when both campaigns are eligible to serve for the same query. The practical implication is that your Standard Shopping campaigns will see reduced impression share when PMax is active. The solution is deliberate campaign segmentation: use custom labels and campaign-level product exclusions to separate the products you want to control in Standard Shopping from those you are running through PMax. Some retailers also use brand exclusions in PMax to prevent it from consuming budget on branded queries that Standard Shopping handles more efficiently.
What is the minimum number of products needed to run Shopping ads?
There is no technical minimum. You can run Shopping ads with a single product. Practically, however, Google's automated bidding algorithms perform better with more products and more conversion data. If you have fewer than 10 to 20 products, Standard Shopping with manual CPC or Maximise Clicks bidding is more appropriate than any automated strategy. For very small catalogues, also consider whether Shopping is the right primary channel or whether it should complement a search campaign strategy.
How long does it take to see results from Google Shopping campaigns?
For most Australian retailers entering the channel fresh, expect a 60 to 90 day period before you have reliable performance data. The first 30 days are primarily data collection. Days 30 to 60 involve feed refinement and initial bid adjustments based on early data. By day 90, you should have enough conversion history to make informed decisions about campaign structure and bidding strategy. Retailers who expect strong ROAS in the first 30 days and pull spend when they do not see it are repeating one of the most common and costly mistakes in Shopping campaign management.
What are the best feed management apps for Shopify and BigCommerce in Australia?
For Shopify, the most commonly used tools by Australian retailers are DataFeedWatch, Feedonomics, and GoDataFeed. All three allow rules-based feed transformation, custom label application, and supplemental feed management. Shopify's native Google channel app is functional for small catalogues but lacks the optimisation depth that mid-market retailers need. For BigCommerce, the native Google Shopping integration works acceptably for basic setup, but DataFeedWatch integrates well with BigCommerce and is worth the investment for catalogues above 500 SKUs. For WooCommerce, the WooCommerce Google Listings and Ads plugin is the most straightforward starting point, with DataFeedWatch again being the upgrade path for larger catalogues.
Do Australian shipping requirements affect Shopping ad performance?
Yes, significantly. Shipping configuration in Google Merchant Centre directly affects whether Google shows your ads to users in specific regions and what estimated delivery information is displayed. Inaccurate shipping settings, particularly flat rates that do not reflect actual regional Australia delivery costs and times, will show incorrect information to shoppers and damage trust at checkout. Google also rewards accurate, fast shipping estimates with better placement in Shopping results. If you offer free shipping above a threshold, configuring that correctly in Merchant Centre enables a "Free Delivery" badge that consistently improves click-through rates. Configure shipping by weight, destination zone, and carrier transit time, not just a single national flat rate.
Can Google Shopping work alongside an SEO strategy for ecommerce?
Absolutely, and the combination is often more powerful than either channel in isolation. Shopping ads deliver immediate visibility for high-intent queries while SEO builds compounding organic traffic over time. The two channels also inform each other: search term data from your Shopping campaigns identifies product and category keywords worth targeting in your SEO content strategy, and organic traffic data shows you which product categories have genuine demand beyond paid traffic. Our ecommerce SEO services are often run alongside Shopping campaigns specifically because the data sharing between channels produces better outcomes for both.
References
Google Merchant Centre Help Documentation, Google's official documentation for Merchant Centre setup, product data specifications, feed requirements, and disapproval resolution. Covers GST and regional pricing requirements for Australian retailers. Available through Google's support portal.
Google Ads Shopping Campaigns Help, Google's official guide to Shopping campaign setup, campaign types, bidding strategies, and Performance Max versus Standard Shopping comparison. Includes guidance on product groups, negative keywords, and reporting. Available through Google Ads Help.
Statista Australian Ecommerce Market Data (2026), Statista's annual projections for Australian ecommerce revenue, growth rates by category, and consumer behaviour in online retail. Used for market size and growth trend references in this article.
Australian Competition and Consumer Commission (ACCC), Pricing and Advertising Guidelines, The ACCC's guidance on how businesses must display prices in Australia, including GST-inclusive pricing requirements and rules around comparative pricing ("was/now" promotional pricing). Relevant to Shopping feed compliance under Australian Consumer Law.
Google Performance Max Best Practices Guide, Google's official guidance on asset creation, audience signals, campaign structure, and measurement for Performance Max campaigns. Covers the transition from Smart Shopping and the differences between PMax and Standard Shopping for ecommerce advertisers.
Google Analytics 4 Attribution Documentation, Google's documentation on attribution models available in GA4 and Google Ads, including data-driven attribution methodology, cross-channel path analysis, and how to compare attribution models for ecommerce reporting.

