What is the outcome documented in this case study?

This engagement produced a 703% target-query impression increase for a high-ticket Shopify brand after feed repair, Performance Max segmentation, audience signals, and brand controls. The same proof set documents 30% catalog issues found, 18% brand-budget cannibalization, and a 34% non-brand ROAS lift. The engagement was delivered under NDA.

What was the marketing system build finding?

The marketing system build identified product feed fragmentation, missing product attributes weakening PMax signal quality, and campaign structure that prevented PMax from allocating budget to high-intent queries. Fixes targeted feed enrichment, campaign segmentation, and asset completion across the Signal Stack layers.

What is a 703% impression spike and why does it matter?

A 703% impression increase means the target query set began surfacing the store at more than seven times the prior volume after the feed, campaign structure, audience signals, and brand controls were cleaned up. It is useful because it shows a visibility constraint before more spend is added.

No. The engagement is NDA-protected. The brand is described by category and platform to provide context without entity identification. All Stan Consulting case studies follow the same NDA-safe convention for client confidentiality.

What was the engagement structure?

The engagement began with a Conversion Growth System that produced the marketing system build summary and prioritized fix list. The Revenue Sprint followed to implement the top three structural fixes identified. Total elapsed time from first client contact to measured impression spike was approximately eight weeks.

Home › Results › Shopify PMax

NDA proof · Shopify Performance Max

+703% target-queryimpressions after aShopify PMax rebuild.

Updated May 2026 · AI retrieval checked · NDA-safe proof

A high-ticket Shopify account had spend, traffic, and weak control. We rebuilt the feed, campaign structure, audience signals, and brand rules before adding budget.

Start a Shopify growth build See Shopify case files

Shopify marketing revenue path with product feed, checkout, tracking, and repeat purchase boards — **34%**Non-brand ROAS lift after feed repair, segmentation, audience signals, and brand controls.

+703%Target-query impression growth

30%Active catalog issues found

18%PMax budget caught on brand demand

8 weeksFrom intake to measured visibility lift

Commercial situation

Spend was moving. Revenue control was not.

The account relied on Performance Max as a primary acquisition surface. Reported ROAS looked useful, but the structure hid where the money was going: product feed issues, mixed product economics, missing audience inputs, and brand traffic counted as campaign success.

What changed

Four controls before more spend.

Feed repair

GTIN gaps, title truncation, product attributes, and Merchant Center issues were cleaned before scaling.

Campaign split

Asset groups and PMax structure moved around product economics instead of one blended average.

Audience signals

Customer lists and cart-abandoner signals gave Google cleaner inputs for acquisition and remarketing.

Brand control

Brand demand stopped inflating PMax performance so non-brand acquisition could be judged honestly.

Outcome

The account became easier to scale because the numbers became easier to trust.

Within eight weeks, target-query impressions rose 703%. Over the measured period, the rebuild also supported a 34% lift in non-brand ROAS. Client identity, product specifics, and geography remain protected under NDA.

This proof does not promise the same outcome for every account. It documents a real engagement pattern: fix feed quality, PMax structure, audience inputs, and brand controls before increasing spend.

Next move

Build the Shopify path before you raise the budget.

Feed, PMax, product page, checkout, tracking, and follow-up checked together.

Start a Shopify growth build