The rise of AI means the old-school obsession with hyper-granularity - dozens of campaigns, hundreds of ad groups, endless manual bid tweaks - is mostly a thing of the past. Think less spreadsheet chaos, more strategic calm.
Why the shift? Because Google’s algorithm can process signals at a scale no human could ever hope to match. Location, time of day, device, intent, behaviour and the list goes on. Juggling thousands of inputs in real time. Impressive stuff.
So yes, our role has changed. But it hasn’t disappeared.
We absolutely should be leaning into machine learning. Smart bidding. PMax. If used properly, these tools help make sure your budget is spent showing the right ad to the right person at the right time.
But AI is only as clever as the data you feed it.
If your product data is messy, incomplete, or poorly structured, the algorithm doesn’t magically fix that for you. It just does its best with what it’s given. And that’s how you end up paying for clicks on products you don’t really want to push. Or worse, products that don’t even make sense for the query.
Feed optimisation doesn’t always get the spotlight. It’s not shiny. It’s not new. But it is absolutely essential if you want automated campaigns to actually perform.
At its core, feed optimisation helps Google understand:
There are plenty of tools out there, from DIY platforms to fully managed services. The trick is choosing one that matches what you’re trying to achieve, and how hands-on you want to be.
So what do these tools actually do?
For starters, they help you tidy up large product feeds with thousands of SKUs. That might mean:
Then there’s attribute mapping and enrichment. In fashion, for example, being able to append size information directly into product titles can significantly improve relevance.
And then there’s one of our favourite features: custom labels.
Custom labels give you serious control over how products are grouped and prioritised in Google Ads. Want to push high-margin items? Dial them up. Slow movers? Dial them down. It's simple, powerful, and criminally underused.
Once the foundations are solid, things get even better. Inventory management ensures products drop out of the auction the moment they go out of stock, saving budget and sparing customers that deeply frustrating “out of stock” click.
Title enhancement uses performance data to enrich product titles with search terms that actually convert. The result? Higher click-through rates, stronger conversion rates, and happier algorithms all round.
Some platforms even offer AI-led image testing, helping you understand which product visuals resonate most with shoppers. Because yes, people really do judge a product by its cover.
And that’s still only part of the picture.
Spoiler: it’s not AI.
Automation isn’t the villain of this story. In fact, it’s doing exactly what it was designed to do. The real challenge is making sure the data we give it is clean, relevant, and working hard behind the scenes. That’s where we believe paid marketers now add the most value. Less time micromanaging bids. More time focusing on feed quality, structure, and strategy. When the data is right, the algorithm can do its thing. And do it exceptionally well.
Because in a world full of automated paid search, feed optimisation isn’t a “nice to have”. It’s the foundation everything else is built on.
