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8-Figure Home & Lifestyle Brand
Google Ads · Large Account Management

Google Ads Portfolio. $1.07M managed spend. 4.06× blended ROAS across 7 campaigns.

4.06×
Blended ROAS · Jan–May 2026
$4.33M Attributed Revenue
3.75×–5.02× Campaign-Level Range
5 Months Jan–May 2026
Jan 1 – May 31, 2026 · All 7 Active Campaigns
4.06× Blended ROAS
$4.33M Platform-Attributed Revenue $1.07M Managed Spend
Google Ads campaign dashboard showing 4.06× blended ROAS across 7 campaigns on $1.07M managed spend, Jan to May 2026. An Optimize your budgets recommendation is visible. Campaign names redacted per NDA.

Google Ads · Jan 1 – May 31, 2026 · 4.06× blended ROAS · $1.07M managed spend · 7 campaignsCampaign names withheld per client NDA.

At $1M+ in annual Google Ads spend, the cost of each structural decision scales with it. A targeting inefficiency that costs a smaller account a few hundred dollars a month costs a portfolio like this several thousand.

Seven campaigns served different purposes: brand demand capture, category search, product-line coverage, seasonal, broader acquisition. The account was already producing a strong blended result. The question was whether the portfolio was being managed as a coordinated system or as seven isolated lines held to an identical efficiency expectation.

What the Review Found

01

One ROAS target applied across seven different jobs

Brand Search captures existing demand at high intent. Acquisition reaches new customers at lower intent. Both were held to the same target ROAS. One target across those two jobs obscures the difference and constrains delivery where it shouldn't.

02

Overlapping query responsibilities across campaigns

Multiple campaigns covered closely related Search demand. When query ownership overlaps, attribution gets murky and budget decisions become harder to evaluate. Which campaign was accountable for which traffic wasn't always clear.

03

Feed titles written at category level, not SKU level

Several product titles used broad category language or internal catalog terminology. The campaigns were targeting high-intent product queries, but the feed wasn't giving Google the SKU-level attributes needed to match against them: product type, material, color, size, style.

04

Some bidding targets belonged to an earlier version of the account

Several targets had been set when the account looked different. Campaign structure, conversion behavior, and product mix had all shifted. Stale targets either constrain delivery or permit lower-efficiency volume. Across $1M+ in spend, that compounds.

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Campaign Portfolio

Seven campaigns, each managed to its own role. 4.06× blended ROAS.

Different demand types and different efficiency targets, with no single ROAS benchmark applied across the whole portfolio.

01  ·  Demand Capture
Brand Search
High-intent branded demand
Captured: existing & in-market
High conversion rate; defend volume, not margin
5.02×
Core Non-Brand Search
High-intent product and category demand
Captured: product & category intent
Concentrates on purchase-intent queries
4.78×
02  ·  Product Coverage
Product Line A · Performance Max
Primary product-line coverage
Reach: feed + audience signals
Primary line; holds budget priority
4.41×
Product Line B · Performance Max
Secondary product-line coverage
Reach: feed + audience signals
Secondary line; capped relative to Line A
4.21×
Product Line C · Shopping
Feed-led product coverage
Reach: feed-driven SKU queries
Below-portfolio ROAS expected by design
3.94×
03  ·  Demand Development
Seasonal & Promotional
Time-bound promotional demand
Conversion: time-sensitive window
Evaluated over promo window, not full period
3.82×
Acquisition · Broader Reach
New-customer reach, broader demand
Prospecting: lower-intent new audience
Lower target ROAS appropriate for this role
3.75×

A lower campaign ROAS does not indicate underperformance. It reflects that campaign's role. The Efficiency Role column documents the intended function, not the achieved efficiency.

What We Changed

Aligned bidding targets with campaign role and current conditions

Each campaign was reviewed against its demand type, conversion behavior, and role in the portfolio. Targets held to a single efficiency standard across structurally different campaigns were adjusted. Targets that hadn't changed as the account evolved were reset against current conversion data.

Created clearer query responsibilities across the portfolio

We identified where Search, Shopping, and Performance Max campaigns overlapped on related demand and applied negative keyword, exclusion, and campaign-setting controls. Each campaign got a clear query responsibility. That made budget and attribution decisions straightforward.

Rebuilt product feed titles at the SKU level

Product titles were rewritten around the attributes customers use in Search: product type, material, color, size, style. Internal catalog language was replaced with the terms that match real queries. Visibility on targeted product searches improved once the revised titles were approved.

Reviewed budget allocation across the portfolio

Budget allocation was reviewed against campaign role, conversion value, efficiency, and available demand. Where the evidence supported a different distribution, allocation was adjusted to better reflect each campaign's contribution to the account.

At $1M+ in spend, one high-performing campaign isn't enough to explain account health. What matters is whether every campaign in the portfolio is pulling its weight across brand, category, product coverage, seasonal, and acquisition.

Outcome

The 4.06× blended ROAS reflects seven campaigns each held to a different standard. Brand Search ran at 5.02×. The acquisition campaign ran at 3.75×. That gap isn't a problem. Those campaigns have different jobs, and the blended number lands where it does when each is managed to its own role.

At $1.07M in spend across five months, there is no room for ambiguity about which campaign is doing what. The architecture gave the team clear answers about where to allocate the next dollar, which campaigns were competing for the same queries, and which roles were underrepresented. That clarity is the actual deliverable. The 4.06× is what it produced.

Phil Chan Head of Growth MESAscale
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About the strategist

Phil has more than a decade of paid-media experience across agency, enterprise, and ecommerce. Most of that time was spent in senior account leadership, directing multi-channel portfolios at seven-figure monthly scale. That context shapes how he approaches individual accounts: not campaign by campaign, but as a system.

Through MESAscale, he works with established ecommerce brands on Google, Meta, and YouTube. His focus is account architecture: where spend is being lost, where cross-channel coordination is breaking down, and which structural changes compound over time.

10+ Years in Paid Media Enterprise + Ecommerce Google · Meta · YouTube
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