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How does UPLIFY scale a women's apparel store from zero analytics to 23× ROAS in 12 months?

UPLIFY built a women's clothing store's Google Shopping engine from zero — no GA, Merchant Center, ad account, or product feed at the start. After laying the data foundation and a feed-first PMax architecture, 12 months delivered ₴4,067,396 in revenue (~$97K) from a ₴170,718 budget — ROAS 23.82×, 6,001 purchases, 4.2% cost-of-sales.

Google AdsPerformance MaxROASGoogle Merchant CenterGoogle Analytics 4ROAS 23.82×women's apparel e-commercefeed-first PMaxasset groupstROAS biddingUPLIFY case studyUkraineQ139583119
← cases · Google Ads · Women's clothing
CASE · GOOGLE ADS · PMAX FEB 2023 — JAN 2024 ● real data

ROAS 23.82× from zero:
6,000 purchases
in 12 months.

Google Shopping built from scratch for a women's clothing store. No analytics infrastructure at the start — we built it and scaled to ₴4.07M (~$97K) in revenue at 4.2% cost-of-sales.

ROAS
23.82×
2382% · CoS 4.2%
Revenue
₴4.07M
Google Ads · 12 mo
Budget
₴170.7K
paced scaling
Purchases · CPA
6,001
CPA ₴28.45 · CR 1.72%
client
Women's clothing online store
vertical
E-commerce · fashion / women's apparel
reporting period
February 2023 — January 2024
channel
Google Ads · Performance Max
model
data foundation → PMax arch → optimization
start
from zero — no analytics at the start
/ tl;dr

case in 5 lines.

pmax-womens-clothing.json ● active
[01]context::Start from zero — no GA, Merchant Center, or ad account at kickoff
[02]budget::₴170,718 (~$4.1K) over 12 months
[03]revenue::₴4,067,396 revenue (~$97K) · ROAS 23.82× · 6,001 purchases
[04]metrics::CTR 2.16% · CPC ₴0.49 · CPA ₴28.45 · CR 1.72% · CoS 4.2%
[05]approach::Feed-first PMax + product segmentation + weekly asset refinement
$_
/ 01 · context and goal

from shopping with no foundation to paced scaling with cost-of-sales control.

problem

Shopping from zero, no foundation

At kickoff there were no ad accounts and no analytics infrastructure. We had to build the entire foundation before we could talk about efficiency: GA4, Merchant Center, conversions, product feed.

goal

Paced volume growth with CoS control

Gradually grow sales volume while preserving long-term efficiency — a focus on cost-of-sales and ROAS, not short-term spikes.

/ 02 · what we did · scroll

framework: data foundation → PMax architecture → optimization.

STEP · 01DATA FOUNDATION

Data foundation

GA4, Merchant Center, Google Ads, conversion tracking — built from zero.

  • Set up GA4 with correct conversion-value pass-through
  • Registered and verified Merchant Center
  • Built the product feed and integrated it with Horoshop
  • Validated purchase tracking and return-attribution
GA4Merchant CenterFeedConversion tracking
STEP · 02PMAX ARCHITECTURE

Performance Max architecture

Product-relevance segmentation, feed-first strategy.

  • PMax campaigns segmented by category / season
  • Feed-first logic: focus on priority products
  • Asset groups with separate creatives per category
  • Audience signals to accelerate learning
PMaxAsset groupsAudience signalsCategory segmentation
STEP · 03OPTIMIZATION

Paced growth

Bid-strategy tests, asset refinement, weekly monitoring.

  • Tested bid strategies (Max Conversions → Max Value → tROAS)
  • Refined asset groups based on performance data
  • Weekly ROAS / CoS monitoring
  • Seasonal priority and budget adjustments
Bid strategy testsAsset refinementSeasonalWeekly optim
/ 03 · results

result: ₴4.07M (~$97K) revenue from a ₴170.7K budget · ROAS 23.82× over 12 months.

6,001 purchases · CoS 4.2% · zero foundation to planned scale

Reporting period
February 2023 — January 2024 (12 mo)
Budget
₴170,718 (~$4.1K)
Revenue
₴4,067,396 (~$97K)
ROAS
23.82×
Purchases
6,001
CPA
₴28.45
Cost-of-sales
4.2%
CTR
2.16%
CPC
₴0.49
CR
1.72%
Clicks
347,318
/ proof from the dashboard
Google Ads · ROAS 23.82× · CoS 4.2% · revenue ₴4.07M (~$97K)
Google Ads · ROAS 23.82× · CoS 4.2% · revenue ₴4.07M (~$97K)
₴4.07M
revenue from a ₴170.7K budget · ROAS 23.82× over 12 months
6,001 purchases · CoS 4.2% · from zero foundation to planned scale
/ more cases

the same approach on other projects.

CASE · META BOARD GAMES

Board games · 2400% ROAS

Meta Ads strategy rebuild: from budget burn to a controlled sales system.

2,400%
ROAS · $1,743 → $41,958
MetaCatalogDPA
open →
CASE · GOOGLE ADS KIDS GOODS

Kids' goods · 21.34×

Google Shopping from zero for a kids' goods store. Doubled the "kids' carpets" category with a dedicated cam…

21.34×
2134% · CoS 4.69%
GAMerchant CenterGoogle Ads
open →
CASE · GOOGLE ADS FURNITURE

Furniture · 7.26×

26 months of continuous Google Shopping / PMax for a furniture store. ₴3.8M budget → ₴27.7M revenue. S…

7.26×
726% · CoS 13.78%
GA4Merchant CenterLooker Studio
open →
all cases →
/ 04 · frequently asked questions

setting up GOOGLE ADS.

01What is "Shopping from zero" and how long does it take?

"From zero" means no GA, no Merchant Center, no feed, no ad account at the start. Building the foundation typically takes 5–10 working days if the site and CMS are ready.

02How do you segment a fashion catalog inside PMax?

By category, season, and margin. Priority products go into separate campaigns — to control budget and avoid diluting algorithm learning.

03When should you switch from Max Conversions to tROAS?

Once the account has 30–50 conversions per campaign and data is stable. Before that — small experiments with Max Value bidding.

04How do you work with asset groups in fashion?

Separate creatives per category (dresses vs sportswear), seasonal lifestyle photo sets. Regular refinement — no slop visuals.

05Which metrics matter most for fashion e-commerce?

Cost-of-sales and ROAS — the headline. CR for traffic-quality reads. CPC for bid efficiency. CPA as a benchmark against margin.

06How often do you monitor and optimize PMax?

Daily — spend, drift, trends. Weekly — deep dive: segmented insights, asset performance, feed health.

07How is conversion value calculated?

Order amounts via Enhanced E-commerce (GA4 transaction ID + value). tROAS only works with correct value data flowing through.

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