Premium Women's Apparel · Google Ads · Full-Funnel
Period
Sep 2023 – Jan 2026
Channel
Google Ads
Company
Conversion Lab
Results
+71%
Google Ads revenue growth, year-on-year
₹1.19Cr
Google Ads revenue in Year 2
4.67x
Average ROAS in Year 2, on accurate tracking
Context
A premium sustainable women's western wear brand selling in India. High-quality clothing at an average order value of ₹8,129 — a category where customers don't impulse-buy. They discover on social, browse on mobile, revisit on desktop, search the brand name, then convert. The purchase cycle can run two to four weeks.
At this price point, platform ROAS is a partial truth at best. A customer might touch four channels before buying. Attribution captures some of that journey, not all of it. The metrics that actually tell you whether the account is working are MER, CAC payback, and returning customer rate — not the number on the dashboard.
I came on board in September 2023 to manage their Google Ads. The dashboard looked healthy. The conversion data did not add up.
What I did
Audit
Inherited an account running 8–10x ROAS. No obvious red flag — but the conversion data did not add up. Ran a full audit of the tracking setup before touching any campaigns.
Fix
The conversion setup was recording one purchase twice. Every ROAS figure in the account was inflated. Fixed the tracking in November 2023. Reported ROAS dropped from 10x to 3x immediately — that was the first accurate number the account had produced.
Build
Built three campaign layers: a BAU evergreen campaign for consistent high-intent demand, collection-based campaigns timed to product launches, and top-of-funnel visually rich campaigns to bring in net new audiences. Each layer had a distinct job.
Scale
January 2024 was the worst reported month — 2.11x ROAS as the algorithm recalibrated to accurate conversion data. We held the structure rather than reacting. By April, ROAS had recovered to 5x. Year 2 averaged 4.67x on 40% higher spend.
The ROAS journey
The drop in November was not underperformance — it was the account becoming honest for the first time.
Oct 2023
Pre-fix — inflated
10.44x
Nov 2023
First accurate reading
3.32x
Jan 2024
Algorithm recalibrating
2.11x
Apr 2024
Structure working
5.05x
Oct 2024
Year 2 peak
6.45x
Apr 2025
Sustained performance
6.23x
Why the dashboard was still lying
Even accurate ROAS understated the real return.
Premium customers don't buy once. The brand's 60-day CLV was ₹13,464 — already 3.9x the CAC of ₹3,408. Payback period: under 60 days. A first-time buyer at ₹8,129 AOV looked marginal on the platform dashboard. Against lifetime value, she was exactly who you wanted to acquire.
This is why MER mattered more than ROAS for this account. The platform only sees what it can attribute. The full picture — repeat purchases, cross-device journeys, brand search driven by awareness spend — was always better than what any single dashboard showed.
₹8,129
Average order value
₹13,464
60-day customer LTV
<60 days
CAC payback period
Year-on-year comparison
Year 1 · Sep 2023 – Aug 2024
Google Ads spend
₹18.2L
Google Ads revenue
₹69.5L
Average ROAS
~3.8x
Year 2 · Sep 2024 – Aug 2025
Google Ads spend
₹25.5L +40%
Google Ads revenue
₹1.19Cr +71%
Average ROAS
~4.67x
Revenue grew 71% while spend grew 40%. Every additional rupee of spend in Year 2 generated more revenue than it did in Year 1.
What this shows
Accurate data is not a given. It has to be earned — and sometimes that means willingly breaking numbers that look good. The 2.11x month was the most important month in this account's history. Everything that came after was built on something real.
For premium brands, the right question is never just "what is the ROAS?" It is whether the account structure matches how customers actually buy, and whether the measurement framework captures the full return — not just what the platform can attribute in a single session.