SHOPPING ADS

Google Shopping in the US is expensive and opaque — ROAS targets alone will not fix a campaign without the right feed and structure

US Shopping CPCs have risen 25% since 2021. Performance Max has removed search query visibility. Most brands running PMax have a single asset group, a default Shopify feed, and no way to tell what their campaigns are actually spending on. The brands managing Shopping profitably have feed control, product segmentation, and a structure that separates new acquisition from returning customer conversions.

This is for you if

Who this is for

Shopping is a meaningful part of your paid mix. PMax is running. The ROAS dashboard looks acceptable. But you cannot tell whether that ROAS is coming from new customers or returning buyers who would have purchased anyway. Your customer acquisition cost from paid search has been rising for two years and you want to understand whether the feed and structure are the cause.

You have segmented by product type. You have tried different ROAS targets. You have given the algorithm time to learn. But PMax still allocates budget in ways you cannot explain, search term data is not available, and you suspect the campaign is spending heavily on YouTube Shorts inventory that is not driving measurable revenue. You need someone to look at the account from the outside and tell you what is actually happening.

When you started, the Shopify Google channel integration was enough. It set up PMax automatically, pulled products from your catalogue, and produced some revenue. Now you have 500 to 5,000 SKUs, meaningful margins to protect, and a budget large enough that a poorly structured campaign is costing real money. The default setup was fine at $2,000 per month. It is not fine at $20,000 per month.

What's broken

What is broken

Single PMax campaign with one asset group and no product segmentation

A single asset group covering all products with a single ROAS target tells Google's algorithm to optimise across your entire catalogue for one efficiency metric. The algorithm does this by concentrating spend on the path of least resistance: returning customers, low-priced products with high historical conversion rates, and branded queries. New customer acquisition — which requires higher bids and more impressions against cold audiences — is systematically underserved. The campaign reports a ROAS that reflects the easy conversions, not the incremental growth the brand needs.

Product feed relying on Shopify's default export

Shopify's default product feed exports titles as they appear in your product catalogue: "Blue Hoodie - M," "Ceramic Mug Set - 4 Pack," "Running Shoe - Black - Size 10." These titles do not match the search queries US buyers use. Buyers search "men's blue pullover hoodie medium," "ceramic coffee mug gift set," "black road running shoes." The gap between your feed titles and actual search queries limits Shopping impressions to exact-match catalogue searches, missing the broader category demand that drives new customer acquisition.

No supplemental feed to control titles without editing Shopify products

To improve a feed title, someone has to edit the product in Shopify. In a catalogue of hundreds or thousands of SKUs, that means either a manual editing project across the product catalogue or a conflict between the marketing team's SEO-optimised product titles and the Shopping team's query-optimised feed titles. A supplemental feed solves this by allowing feed field overrides — including titles, descriptions, and custom labels — without changing the source Shopify product data. Without one, feed optimisation is constrained by whoever controls the Shopify product catalogue.

No search term visibility from PMax

Performance Max does not surface the actual search queries triggering your Shopping ads. Google Ads shows "search categories" in PMax reporting, not individual search terms. Without a parallel Standard Shopping campaign running at a lower budget, there is no mechanism to see what queries are driving Shopping clicks. This means negative keyword strategy is built on guesswork, title optimisation has no search term feedback loop, and the account cannot identify irrelevant or low-intent queries consuming budget. Brands spending significant sums on PMax without a search term visibility strategy are optimising without data.

What we engineer

What we do

PMax campaign audit and spend attribution analysis

We deconstruct your PMax spend by placement type, product group, and audience segment to identify where budget is going and which spend is driving incremental revenue versus harvesting existing demand. We flag YouTube Shorts allocation, brand query spend, and low-margin product overspend before we recommend any structural changes.

Supplemental feed build for title and attribute control

We build a supplemental feed that overrides product titles, descriptions, and custom labels in your Shopping feed without touching your Shopify product catalogue. Title rewrites are informed by US search query data, competitor feed analysis, and category-level keyword volume. Custom labels are added to support margin-tier segmentation.

Product segmentation by margin, category, and LTV

We segment your product catalogue using custom labels in the supplemental feed, then restructure your PMax campaign with asset groups that reflect those segments. ROAS targets are calculated by segment based on the gross margin and acceptable cost-of-sale for each product group.

Standard Shopping campaign for search term visibility

We build a Standard Shopping campaign running alongside PMax at a lower budget. Its primary function is to surface actual search term data that PMax does not provide. This data feeds the negative keyword strategy for both campaigns and informs ongoing title optimisation in the supplemental feed.

Negative keyword strategy built from actual search data

Using search term reports from the Standard Shopping campaign and any available historical data, we build and maintain negative keyword lists that filter irrelevant queries, competitor brand terms, and low-intent searches from both campaigns.

RLSA remarketing Shopping setup

We build remarketing lists for Shopping ads (RLSA) targeting past website visitors who did not convert. These lists are applied to bid adjustments in Standard Shopping campaigns to increase bid competitiveness for high-intent return visitors without inflating bids for cold traffic.

Ongoing feed maintenance and monthly performance reporting

Monthly audits cover feed errors, price accuracy, out-of-stock SKUs, and title relevance against current search query data. Performance reports break out ROAS by segment, new customer ratio, impression share, and spend allocation by placement type inside PMax.

What changes

What changes

Before
After
Before A single asset group covering all products with a single ROAS target tells Google's algorithm to optimise across your entire catalogue for one efficiency metric. The algorithm does this by concentrating spend on the path of least resistance: returning customers, low-priced products with high historical conversion rates, and branded queries. New customer acquisition — which requires higher bids and more impressions against cold audiences — is systematically underserved. The campaign reports a ROAS that reflects the easy conversions, not the incremental growth the brand needs.
After Product segmentation and per-asset-group ROAS targets mean budget flows to high-margin products and new customer acquisition, not to the easiest conversions. The campaign structure reflects what you are trying to achieve commercially, not what the algorithm finds convenient.
Before Shopify's default product feed exports titles as they appear in your product catalogue: "Blue Hoodie - M," "Ceramic Mug Set - 4 Pack," "Running Shoe - Black - Size 10." These titles do not match the search queries US buyers use. Buyers search "men's blue pullover hoodie medium," "ceramic coffee mug gift set," "black road running shoes." The gap between your feed titles and actual search queries limits Shopping impressions to exact-match catalogue searches, missing the broader category demand that drives new customer acquisition.
After Supplemental feed titles are built around actual US search volume data. Shopping impressions expand beyond branded and exact-match catalogue searches to include the category-level demand where new customer acquisition happens.
Before To improve a feed title, someone has to edit the product in Shopify. In a catalogue of hundreds or thousands of SKUs, that means either a manual editing project across the product catalogue or a conflict between the marketing team's SEO-optimised product titles and the Shopping team's query-optimised feed titles. A supplemental feed solves this by allowing feed field overrides — including titles, descriptions, and custom labels — without changing the source Shopify product data. Without one, feed optimisation is constrained by whoever controls the Shopify product catalogue.
After The Standard Shopping campaign surfaces actual queries triggering your Shopping ads. Negative keywords are added based on real data. Title rewrites are validated against what is driving clicks. The optimisation loop runs on evidence, not estimates.
Before Performance Max does not surface the actual search queries triggering your Shopping ads. Google Ads shows "search categories" in PMax reporting, not individual search terms. Without a parallel Standard Shopping campaign running at a lower budget, there is no mechanism to see what queries are driving Shopping clicks. This means negative keyword strategy is built on guesswork, title optimisation has no search term feedback loop, and the account cannot identify irrelevant or low-intent queries consuming budget. Brands spending significant sums on PMax without a search term visibility strategy are optimising without data.
After The supplemental feed means title and attribute changes do not require Shopify product edits. New products are added to the correct segmentation tier by adding a custom label. The structure accommodates a growing catalogue without requiring a rebuild every time product volume increases significantly.
How it works

How we work

  1. 01

    Diagnostic

    We audit your PMax structure, pull spend data by placement and product group, review your feed against US search query data, and assess the supplemental feed situation and search term visibility gap. You receive a written diagnostic before we discuss scope or cost.

  2. 02

    Supplemental feed and segmentation build

    We build the supplemental feed with rewritten titles, descriptions, and custom labels for margin-tier segmentation. We restructure the PMax campaign with asset groups that reflect the segmentation. ROAS targets are set per asset group using your margin data.

  3. 03

    Standard Shopping and RLSA setup

    We launch the Standard Shopping campaign for search term visibility, build RLSA lists from your existing audience data, and apply them to bid adjustments in Standard Shopping. Negative keyword lists are built from the first available search term data.

  4. 04

    Ongoing optimisation and reporting

    Weekly performance monitoring, monthly feed audits, and quarterly structural reviews. Search term data from Standard Shopping feeds into ongoing title optimisation and negative keyword expansion. Reports cover ROAS by segment, impression share, new customer ratio, and feed health.

Common questions

Frequently asked questions

Should I run Performance Max or Standard Shopping or both?

Most US brands spending more than $5,000 per month on Shopping benefit from running both. Performance Max is the primary campaign and receives the majority of the budget because Google allocates more Shopping inventory to PMax than to Standard Shopping. Standard Shopping runs alongside it at a lower budget — its primary function is not to compete with PMax but to surface the actual search term data that PMax withholds. The search terms from Standard Shopping feed the negative keyword strategy for both campaigns and validate whether PMax titles and assets are matching the right queries. Running only PMax without any search term visibility mechanism is a structural disadvantage in a competitive market.

How do I see what search terms are triggering my Shopping ads in PMax?

Performance Max does not provide individual search term reports. Google shows aggregated "search categories" in PMax reporting, which describe query themes rather than actual queries. The practical workaround is to run a Standard Shopping campaign with a lower priority and budget alongside PMax. Standard Shopping does surface individual search term data in the Search Terms report. By monitoring this report, you can identify irrelevant queries triggering Shopping clicks, build negative keyword lists, and understand which search intents are driving your Shopping traffic. There is no method within PMax itself to access individual search query data.

What is a supplemental feed and why do I need one?

A supplemental feed is a secondary data source in Google Merchant Centre that overrides or adds attributes to your primary product feed without changing the source data. For a Shopify store, the primary feed pulls product data directly from the Shopify catalogue. A supplemental feed sits on top of it and replaces specific fields — most commonly product titles, descriptions, and custom labels — with optimised versions. You need a supplemental feed when your Shopping titles need to be different from your Shopify product titles (which they almost always do for query optimisation), and when you want to add segmentation attributes like margin tier labels without adding custom fields to every Shopify product manually. The supplemental feed makes the Shopping operation independent of whoever manages the Shopify product catalogue.

How do I segment products by margin in Google Shopping campaigns?

Margin-based segmentation is implemented using custom labels in the product feed. You assign a custom label value to each product based on its margin tier — for example, custom label 0 is set to "high," "mid," or "low" depending on the product's gross margin. In your PMax campaign, you create separate asset groups filtered by those custom label values. Each asset group receives a ROAS target calculated from the margin available in that tier. High-margin products can accept a lower ROAS target (more spend per revenue dollar) because each dollar of revenue generates more profit. Low-margin products need a higher ROAS target to remain profitable. Without this segmentation, a single ROAS target applies across all products regardless of their profitability, which produces a blended result that masks the performance of individual margin tiers.

What ROAS target is realistic for Google Shopping in a competitive US category?

ROAS targets in the US vary significantly by category, average order value, and margin structure. Highly competitive categories — consumer electronics, apparel, home goods, beauty — typically see Shopping ROAS between 3x and 6x for brands with well-optimised feeds and campaign structures. Categories with less competition or higher average order values can achieve 8x to 12x. The correct target for your business is not the category average. It is the ROAS at which your net margin after advertising cost remains positive: if your gross margin is 55% and you are willing to spend 15% of revenue on paid acquisition, your minimum viable ROAS is 6.7x. Setting a ROAS target below your margin-derived minimum produces profitable-looking campaigns that are losing money in aggregate. We calculate per-segment ROAS targets from your margin data as part of the campaign structure build.

Our team

The people behind the work

Not a black box. Real specialists you can call, with their names on the work.

Niraj Raut

Niraj Raut

Founder — Ecommerce SEO
Keshab Joshi

Keshab Joshi

PPC Expert
Hawrry Bhattarai

Hawrry Bhattarai

Google Ads Expert
Arogya Rijal

Arogya Rijal

SaaS SEO Expert
Start here

Find out what your Shopping campaigns are actually spending on

We start with a diagnostic. We pull your PMax spend by placement and product group, review your feed titles against US search query data, and identify the structural gaps between your current setup and a campaign built around your margin and acquisition targets. You get a written summary before we discuss any engagement.