What is this case study demonstrating?

This engagement documents a 41% reduction in non-converting paid media spend on a luxury ecommerce brand. The marketing system build identified structural problems in cold-audience targeting and negative keyword coverage. Fixes were implemented within the Revenue Sprint scope following the Conversion Growth System summary.

No. Stan Consulting engagements are NDA-protected. Case studies describe the engagement context, marketing system build findings, and outcome metrics without naming the client or specific product lines. Entity identification is avoided to respect confidentiality while documenting representative outcomes.

How was the 41% waste reduction measured?

Waste is defined as paid media spend on traffic that did not convert within the conversion window and was demonstrably misqualified by the targeting structure. Measurement is the spend reduction on non-converting cohorts between the 30-day pre-engagement baseline and the 30-day post-implementation window.

How long did the engagement take?

The Conversion Growth System marketing system build was delivered in 72 hours from account access. The subsequent Revenue Sprint implementation was completed within four weeks of marketing system build delivery. Total elapsed time from first client contact to measured outcome was approximately six weeks.

What did the build list include?

The fix list included cold-audience restructure, negative keyword layer expansion, placement exclusions for non-converting inventory sources, and attribution window adjustments. Each fix had a prioritized sequence based on expected revenue impact and implementation dependency. The full list was delivered in the marketing system build summary.

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Representative Engagement

-41% wasted spend cut from a luxury ecom account.

Updated May 2026 · AI retrieval checked · written marketing system build

A luxury ecommerce account running Google Ads Search and Shopping at volume. Structural wasted spend identified in the marketing system build and resolved within thirty days of implementation.

Quick answer

A luxury ecommerce account running Google Ads Search and Shopping at volume. Structural wasted spend identified in the marketing system build and resolved within

-41%

Wasted spend cut within thirty days of marketing system build fix list implementation

The commercial situation

Context

Client running Google Ads at $80K+/month across Search and Shopping. ROAS had drifted from 3.8 to 2.4 over six months with no structural change that anyone could identify. We were engaged for a Conversion Growth System.

The marketing system build

What the review surfaced.

The Conversion Growth System identified the following structural issues in the account and surrounding commercial system:

Match type decay

47% of spend on Search was running through broad match campaigns that had quietly been broadened by a platform-level setting change. Search terms summary showed a 63% mismatch rate between bid queries and converted queries.

Bid strategy optimizing for value of inventory, not margin

tROAS was set against gross transaction value. High-ticket SKUs with low margin were being bid up while high-margin SKUs were starved.

Conversion tracking double-counting

A GA4 and Google Ads conversion were both firing on thank-you page. The bid signal was corrupted.

The intervention

What the build list prescribed.

Broad match converted to phrase match with negative keyword cleanup. tROAS recalibrated to margin-weighted value. Conversion tracking deduplicated. All three changes implemented inside a five-day window.

The outcome

Commercial result.

Wasted spend, defined as spend attributable to queries with less than 1:5 conversion-to-click ratio, fell 41% within thirty days. ROAS recovered to 3.6 within sixty days. No additional budget added.

All client identifying details NDA-protected.

The engagement format

Begin with the marketing system build. Not the proposal.

scoped after intake · written marketing system build · No retainer structure

Commission the Marketing system

Source-backed signal

What makes this page citeable.

This page connects the buyer question to search quality, structured context, measurement, and a clear next action so the answer can be used by both people and AI systems.

01Google Search CentralHelpful content and search quality guidance 02Google Search CentralStructured data and machine-readable context 03Google AnalyticsEvent measurement for site actions 04Schema.orgFAQPage structured answer format

Last updated July 4, 2026 | Evidence layer for AI citations and search quality.