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Weekly Loom walkthroughs with a written summary, plus a dedicated Slack channel with the team available seven days a week. No portal you have to log into to find your numbers.

How do you stay updated on industry trends and best practices?

Through our close relations with Google, we receive ongoing training from high-level representatives on new features often before public release. Our scale across high-spending accounts gives us real-time data on what's actually working.

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Our specialists are among the top professionals globally. At Ad-Lab we enforce stringent conditions to ensure each team member handles a minimal number of accounts, allowing unparalleled focus on each client.

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Yes. We conduct in-depth audits and provide strategic recommendations. We identify areas where your previous or current agency is missing optimization opportunities.

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What's a typical Ad-Lab client size?

$30,000+ in monthly Google + YouTube ad spend, or $100,000+ in monthly revenue. Most are doing both. Below that range the audit doesn't surface enough leverage to justify our model. Above $1M/month is where the system around the ad starts compounding hardest. If you're not sure where you fit, apply for the free audit anyway and we'll tell you straight.

Why aren't you on Meta or TikTok?

Because the work that compounds Google + YouTube spend at scale (landing pages, creative, feed engineering, tracking, AI ops, weekly audits) is full-time work. Spreading thin across Meta and TikTok would mean less depth in the channels where we already have $150M+ of pattern recognition. We partner with Meta and TikTok specialists for clients who need both, but we won't pretend to be the best at every channel ourselves. That said, the Google + YouTube work we ship affects your Meta and TikTok performance every week (branded search volume, AOV across the shop, blended CPA), and we report that cross-channel context as part of the standard cadence.

All case studies

EcommerceIllustrative example60 days

A 3.2x ROAS account that was losing money on its bestsellers

We rebuilt the bidder around profit, not revenue. Same sales, 36% more margin.

Gross profit

+36%

POAS

1.0 → 1.4

ROAS

3.2x → 3.1x

Revenue

Flat

Chapter 01

Revenue is a vanity metric at the SKU level

ROAS optimises revenue. Revenue is not profit. When your catalogue has a mix of margins, a flat ROAS target quietly pushes budget toward whatever converts most easily, and the things that convert most easily are often your discounted, low-margin bestsellers. The dashboard goes up and to the right. The contribution margin sits at break-even. Everyone's confused about why a winning account feels broke.

Here's the math that exposed it. A flat 3.2x ROAS means your ad cost is the sale price divided by 3.2. Run that against two real SKUs from this account and the truth is brutal.

Same ROAS, opposite outcomes

SKU	Price	Margin	ROAS	Profit per sale after ad cost
Discounted bundle	$80	12%	3.2x	−$15
Hero product	$140	58%	3.2x	+$37

The $80 sale costs $25 in ads and carries $9.60 of margin, so it loses $15. The $140 sale costs $44 and carries $81 of margin, so it makes $37. Same ROAS. One funds the business, one drains it.

Chapter 02

Feeding profit into the bidder

If you send Google revenue, it buys revenue. Send it profit and it buys profit.

The rebuild

1
Pulled true margin per SKU
Got real landed cost and margin per product from the brand's finance and store data. No estimates. Bidding to profit only works if the profit number is right.
2
Tagged margin tiers with custom labels
Every SKU labelled into a margin tier in a supplemental feed, so campaigns could be split and targeted off real economics.
3
Sent profit as the conversion value
Switched the conversion value from revenue to a margin-adjusted profit value, so the bidder optimises toward money kept rather than money moved.
4
Locked down tracking with enhanced + server-side conversions
Bidding to profit against bad data just optimises against bad data faster. Enhanced conversions plus a server-side setup made the values accurate and complete under consent mode.
5
Set targets off break-even per tier
Each margin tier got a tROAS derived from its own break-even plus a buffer, instead of one flat number pretending every product was the same.

What you send is what you get

What you send Google	What it optimises for
Revenue (the default)	More sales, at any margin
Profit (margin-adjusted value)	More money kept

Chapter 03

Sixty-day results

Before and after

Metric	Before	After (day 60)
Revenue	$240K / month	~$236K / month
Ad spend	$75K	$75K
ROAS	3.2x	3.1x
Gross profit	$76.8K	$104K
POAS	1.0	1.4

Revenue flat, spend flat, and the business kept an extra $27K a month.

Our dashboards said we were winning all year. The first month we bid to profit, revenue barely moved and we kept twenty-seven thousand more dollars. That was the real account the whole time.

Founder

Questions we get asked about this

What's the difference between ROAS and POAS?

ROAS is revenue over ad spend. POAS is profit over ad spend. ROAS treats an $80 sale at 12% margin the same as an $80 sale at 60% margin, even though one funds the business and one drains it. POAS only counts the money you keep. If your margins vary across the catalogue, ROAS will quietly push budget toward your worst products because they often convert easiest.

How do I send profit to Google instead of revenue?

Two routes. The clean one is to send a profit-adjusted conversion value from your store or server, so Google bids on margin directly. The simpler one is to tag SKUs into margin tiers with custom labels and run separate tROAS targets per tier set off each tier's break-even. Most accounts start with tiers and graduate to true profit values once tracking is solid.

What's my break-even ROAS?

One divided by your gross margin. A 50% margin product breaks even at 2.0x, a 25% margin product at 4.0x, a 12% margin product at 8.3x. This is why a flat ROAS target across a mixed catalogue is a mistake: the same 3.2x is wildly profitable on one product and deeply unprofitable on another.

Do I need server-side tracking for this?

You need accurate values, and enhanced conversions plus a server-side setup is the reliable way to get them, especially post-iOS and with consent mode in play. If your conversion values are wrong or undercounted, bidding to profit just optimises against bad data faster.

Frameworks behind this case study

Calculator: POAS

Calculator: break-even ROAS

Glossary: POAS

About these numbers

Illustrative example. The campaign structure and the margin math shown are the exact approach we deploy. The figures are representative of what it produces for accounts in this spend band over a 60-day window, not an export from one client's account.

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Apr 22, 2026

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