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Case study / Google Ads

Case Study: $3K to 21.23 ROAS Using PMax Tiers

A 20K-SKU computer parts store used PMax price tiering to reach 21.23 ROAS on a $3K budget, using feed structure and product economics to guide campaign segmentation.

ROAS21.23ROAS from the homepage proof summary.
ROAS21.23

ROAS from the homepage proof summary.

01

Problem

A large SKU catalog needed campaign structure tied to margin and product economics.

A large SKU catalog needed campaign structure tied to margin and product economics.
02

Action

Segmented PMax by price tiers, feed structure, and product economics.

Segmented PMax by price tiers, feed structure, and product economics.
03

Result

The account reached 21.23 ROAS on a $3K budget.

The account reached 21.23 ROAS on a $3K budget.

A 20K-SKU computer parts store used PMax price tiering to reach 21.23 ROAS on a $3K budget, using feed structure and product economics to guide campaign segmentation.

Problem

A large SKU catalog needed campaign structure tied to margin and product economics.

Action

Segmented PMax by price tiers, feed structure, and product economics.

Result

The account reached 21.23 ROAS on a $3K budget.

The Decision-to-Outcome System

The result belongs to a decision loop, not an isolated tactic.

This google ads case is presented through the same five stages: diagnose the constraint, validate the evidence, decide the move, execute it, and prove the change.

  1. 01

    Diagnose

    Find the commercial constraint before choosing a channel task.

    Input: Website, account, tracking, feed, margins, demand, or buyer prompts.
  2. 02

    Validate

    Check the data, economics, demand, and implementation reality behind it.

    Output: Trusted baseline, attribution, margins, lead quality, stock, and access limits.
  3. 03

    Decide

    Choose the highest-leverage move and make the trade-offs explicit.

    Output: One priority, target metric, assumptions, exclusions, and decision date.
  4. 04

    Execute

    Ship the smallest coherent intervention that can change the outcome.

    Output: Owner, sequence, dependencies, approvals, and validation method.
  5. 05

    Prove

    Read the result against revenue, margin, pipeline, or qualified demand.

    Output: Metric movement, confidence, exclusions, unintended effects, and next decision.

Repeat: evidence from Prove becomes the next Diagnose input.

Verified worked example

What the loop looked like in one PMax relaunch.

  1. What the dashboard appeared to showROAS was 3.06 while PMax needed to scale.
  2. What the diagnosis foundBrand demand could hide acquisition efficiency; the conversion signal and segmentation needed cleaning.
  3. What decision was madeRelaunch PMax around cleaner signal, clearer segments, and brand-bleed control.
  4. What was implementedRebuilt the campaign structure and increased spend with discipline.
  5. What changedROAS reached 5.90 and revenue almost tripled on 37% more spend.
Read the verified case