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Lifestyle & Accessories Case Study

$17.6M in Revenue in 11 Months Through Strategic Google Ads Restructure

How we helped a lifestyle accessories brand reduce branded keyword dependency, restructure for seasonality, and build a scalable growth framework on Google Ads.

$17.6M Revenue Generated
538% Overall ROAS
11 mo. Engagement
+71% Shopify Sales YoY

What We Found When We Took Over

On the surface, this account looked like a success. Strong reported ROAS, decent revenue. But the founder wasn't convinced — and he was right.

01
65–70% of Revenue Was Branded

After an in-depth audit, we discovered that the majority of reported revenue was coming from branded searches — customers already searching for the brand's name. This inflated results and hid true performance from non-branded campaigns.

02
Branded and Non-Branded Keywords Were Mixed

Most of the Performance Max campaigns weren't excluding branded keywords. We suspected about 60–70% of conversions from these campaigns came from branded queries, making it impossible to measure true incremental growth.

03
No Framework for Seasonality

This brand's catalogue is highly seasonal — what's trending in March can flop by April. Yet nearly 70% of the budget was tied up in a single standard shopping campaign with one ad group. Google's smart bidding would eventually adjust, but always with a costly delay.

A Framework Built to Scale Long-Term

Step 01
Separate Branded vs. Non-Branded

We applied keyword exclusions to all non-branded campaigns so branded queries couldn't inflate results. We then built a dashboard to track the non-branded revenue percentage daily — giving us real-time visibility into true incremental growth.

Step 02
Focus on New Customer Acquisition

High ROAS from returning customers wasn't the goal. We built a custom column to measure the % of new customers each campaign generated and set this as a secondary KPI alongside ROAS — ensuring the account was driving real business growth, not just repeat purchases.

Step 03
Build Flexibility Into the Structure

With products turning over every few weeks, we needed to shift spend proactively. We used custom labels — seller ratings, collection tags, seasonal flags — to segment campaigns and move budget into trending products 3–5 weeks before peak demand, not during it.

Step 04
Create a Tiered Campaign Framework

We designed a layered structure with differentiated tROAS targets so budget flowed naturally toward the highest-priority campaigns:

  • Standard Shopping (tROAS 300–350%) as a profitable catch-all baseline
  • Performance Max (tROAS 250–300%) for trending collections with aggressive bidding
  • Search campaigns for scaling proven keywords with exact-match control

Clarity, Control, and Flexibility

Every campaign had a defined role. Bidding targets were set deliberately so budget flowed toward the highest-priority campaigns without overlap or cannibalisation.

Branded Search
Branded Search Campaign

Captured all direct brand searches. Individual ad groups for different collections and themes. Target Impression Share bidding with a max CPC cap — avoiding the common mistake of applying tROAS or tCPA to branded search.

TIS
Bidding
Branded Shopping
Branded Shopping Campaign

Dominated SERPs for branded product searches. Required smart bidding (the one exception) with a high tROAS target (+500%) to prevent the campaign from competing on non-branded queries.

500%+
tROAS
Standard Shopping
Shopping Catch-All

Profitable baseline coverage for the full catalogue. Products segmented using custom labels (collections, performance tiers, seasonality flags). Served as the foundation of consistent non-branded revenue.

300–350%
tROAS
Performance Max
PMax for Trending Collections

Once a collection started (or was about to start) trending, it was moved into its own PMax campaign. Deliberately more aggressive tROAS than the catch-all, so Google prioritised these products for budget allocation. Feed-only and full-asset groups tested per campaign.

250–300%
tROAS
Search
Search Campaigns for Winning Keywords

Built from top-performing terms identified in Shopping. Campaigns broken out by product category, with ad groups segmented by collection. Tight negative keyword management prevented overlap between campaigns.

tROAS
Bidding
Demand Gen
YouTube / Demand Gen

Introduced in the final months to expand reach with cold audiences. Top-performing assets from Meta and TikTok repurposed for YouTube Shorts, converting at 1.5–1.8x as reported on platform. Used to fill the funnel and drive assisted conversions.

Awareness
Why we moved trending products INTO their own campaigns — not out of them. Conventional wisdom says to isolate poor performers. Here, we did the opposite: isolating trending products into dedicated PMax campaigns let us allocate budget proactively — weeks before Google's automation would have caught up on its own.

11 Months. Measurable Impact.

$17.6M
Total Revenue Generated

$6.71M increase year-over-year. A 71% lift in Shopify sales compared to the prior 11-month period.

538%
Overall ROAS

Achieved across all campaigns — branded and non-branded — over the full 11-month engagement.

36→65%
Non-Branded Revenue Share

Nearly doubled the share of revenue coming from non-branded campaigns — the clearest signal of true incremental growth from Google Ads.

+71%
Shopify Sales YoY

Total Shopify revenue increased 71% compared to the same period in the prior year — validating that Google Ads was driving real business growth.

Full Results Summary
$17,600,000 in sales generated
538% overall ROAS
$6.71M revenue increase year-over-year
Non-branded revenue share: 36% → 65%
71% more Shopify sales vs. prior year
New customer acquisition share increased
Account Screenshots
Revenue and ROAS overview
Revenue & ROAS Overview
$20.7M in sales at 563% ROAS over 14 months
Non-branded revenue share growth
Non-Branded Revenue Share
Monthly tracking from 36% to 65% non-branded revenue
New customer acquisition rate
New Customer Acquisition
64–74% new customer rate across top campaigns
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