
Product feeds are either a growth asset or a silent tax
If your feed is wrong, you pay for it. Wasted ad spend. Lost impressions. Low-quality clicks that never convert. Most SMEs don’t spot it because the problem hides inside “performance”. But a messy feed is one of the fastest ways to turn paid media into noise. This is fixable. Not with more tweaks. With a simple system you can run: clean data, clear segmentation, and a weekly QA rhythm that keeps your best products eligible, visible, and profitable.
Built around outcomes, not platform scores.


Product feeds are either a growth asset or a silent tax
If your feed is wrong, you pay for it.
You pay in wasted ad spend.
You pay in lost impressions.
You pay in low-quality traffic that never converts.
Most SMEs don’t notice it because the problem hides inside “performance”.
But a messy feed is one of the fastest ways to turn paid media into noise.
This is fixable.
And it’s not a “Google thing”.
It’s a commercial system.
What a product feed really does (in business terms)
A product feed is the dataset that decides:
What gets shown.
When it gets shown.
And whether it gets trusted enough to win the click.
Google Shopping, Performance Max, Meta catalogue ads, marketplaces.
They all run on structured product data.
If that data is incomplete or inconsistent, you don’t just get lower performance.
You get less control.
The failure modes that hit profit (not just “optimisation scores”)
1) You’re bidding on the wrong version of your product
Variant confusion creates irrelevant clicks.
Irrelevant clicks kill ROAS.
Common causes:
Titles that hide the key differentiator (size, fit, compatibility).
Wrong GTIN/MPN mapping.
Variants merged or split incorrectly.
2) You lose coverage without noticing
Your best products can simply stop serving.
Disapprovals.
Price mismatches.
Out-of-stock handling that removes you from auctions.
The dashboard will call it “limited eligibility”.
Your P&L will call it missed demand.
3) You can’t scale winners because the inputs aren’t stable
Even when ads “work”, scaling becomes fragile.
The reason is simple.
The system can’t learn reliably from inconsistent data.
A feed improvement system you can actually run
Step 1: Decide what “good” means for your business
Not for the platform.
Pick 3 commercial outcomes:
Higher qualified traffic.
Higher conversion rate.
Better margin efficiency.
If a feed change doesn’t support one of those, it’s busywork.
That’s outcomes over activity [KB100].
Step 2: Fix the fields that control matching and trust
Start here:
Title (clarity first, keyword second).
Product type / category mapping.
GTIN/MPN where applicable.
Images (clean, consistent, policy-safe).
Price + availability accuracy.
If it can’t be explained simply, it won’t be maintained [KB099].
Step 3: Create a “feed QA” checklist and run it weekly
Make it boring.
Make it repeatable.
Check:
Disapprovals and warnings.
Sudden drops in impressions by product group.
Price mismatch frequency.
Top spend / low conversion SKUs (usually a feed issue or offer issue).
Systems create momentum [KB101].
Step 4: Segment your feed so you can make real decisions
Don’t treat the catalogue as one blob.
Create groups by:
Margin tier.
Stock depth.
Hero products vs long tail.
Seasonality.
This is how you stop “optimising” and start allocating budget on purpose.
The takeaway
A product feed isn’t admin.
It’s infrastructure.
If it’s clean, your ads get cheaper and your winners scale faster.
If it’s messy, you’ll keep paying to learn the same lessons.
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