I recently came across a brilliant question from someone who had just bought a classic car parts business. They were trying to figure out how to make Google Ads work for automotive aftermarket parts, and their challenge highlights a fundamental problem I see all the time in the industry.
The Fitment Data Problem
Here's what most people don't realise about automotive advertising: the way customers search is completely different from almost every other ecommerce vertical.
If you're selling trainers, your customer searches for "Nike Air Jordan Model 123, Size 12" and that's exactly what you put in your product title. Simple. The product name matches the search query, Google matches them together, everyone's happy.
But if you're selling a Moog Ball Joint with part number 12345, nobody is searching for that. Your customers are searching for "1985 Oldsmobile Cutlass Ciera ball joint" or "ball joint for Honda Civic 2008" or any one of potentially hundreds of vehicle-specific queries.
And here's where it gets complicated: that single ball joint might fit 100 different vehicles. How do you structure your data feed to capture all that search demand?
The Variant Multiplication Strategy
The solution is elegantly simple in concept: you create variants of each product for every vehicle it fits.
Say you have that Moog Ball Joint #12345. In your standard product feed, you'd have one listing with whatever title the manufacturer gave it. But that's not how people search.
Instead, you create multiple entries in your feed for the same physical product. Each entry represents the same ball joint, but targeted at a different vehicle application. So instead of one product listing, you might have 50, 100, or even more.
Here's what stays the same across all variants:
The product page URL (they all point to the same page)
The price
The product image
The description
Here's what changes:
The Item ID (absolutely critical)
The Product Title
Getting the Item ID Right
The Item ID change is non-negotiable. Google uses Item IDs to identify unique products in your feed. If you submit 100 variants with the same Item ID, Google will just see it as one product with constantly changing data, which will cause all sorts of problems.
The simplest approach is to take your base Item ID and append a suffix for each vehicle application. So if your original Item ID is "MOOG-BJ-12345", your variants become:
MOOG-BJ-12345-001
MOOG-BJ-12345-002
MOOG-BJ-12345-003
This keeps things organised and traceable back to the original product whilst giving Google the unique identifiers it needs.
Crafting Vehicle-Specific Titles
Now for the part that actually drives the results: your product titles.
Each variant gets a title optimised for the specific vehicle it fits. Instead of "Moog Ball Joint #12345", you'd have:
Ball Joint for 1985 Oldsmobile Cutlass Ciera
Ball Joint for 1986 Oldsmobile Cutlass Ciera
Ball Joint for 1984 Chevrolet Celebrity
Each title is now perfectly aligned with how actual customers search. When someone searches for "1985 Oldsmobile Cutlass Ciera ball joint", Google can match them with a product whose title contains exactly those words. Your Quality Score improves, your click-through rate improves, and your cost per acquisition drops.
The Scale Challenge and Automation
I won't pretend this is quick to set up manually. If you have 5,000 products and each fits an average of 50 vehicles, you're looking at 250,000 variants. That's not something you're going to knock out in an afternoon with a spreadsheet.
This is where proper feed management tools become essential. If you already have ACES data (the industry standard for automotive fitment information), you have the raw data you need. The challenge is transforming that data into a properly structured product feed.
Most serious automotive aftermarket retailers use dedicated feed tools that can:
Import your base product catalogue
Import your ACES fitment data
Automatically generate variants for each vehicle application
Apply title templates that insert year, make, and model dynamically
Keep everything synchronised when products or fitment data changes
The title template might look something like: "{Product Type} for {Year} {Make} {Model}". The system then iterates through every product-vehicle combination and generates the appropriate variant automatically.
What About Performance Max?
This variant strategy works brilliantly for Standard Shopping campaigns, but it works just as well with Performance Max. Google's automation will pick up on the vehicle-specific titles and match them to relevant searches.
The one thing to watch is that your asset groups are structured sensibly. You probably don't want all 250,000 variants lumped into a single asset group. Consider splitting by product category, vehicle decade, or some other logical grouping that allows you to manage performance and allocate budget appropriately.
Common Mistakes to Avoid
Having seen quite a few automotive parts advertisers attempt this, here are the pitfalls I see most often:
Duplicate Item IDs: Every variant needs a unique Item ID. Get this wrong and your feed will be a mess.
Generic titles: Some advertisers use titles like "Ball Joint - Fits Oldsmobile". That's not specific enough. Include the year. Include the exact model. The more specific your title matches the search query, the better your performance.
Ignoring landing page experience: All your variants point to the same product page, which is fine, but make sure that page clearly shows the fitment information. The customer who clicked on "Ball Joint for 1985 Oldsmobile Cutlass Ciera" wants to land on a page that confirms this part fits their vehicle. If they can't find that confirmation quickly, they'll bounce.
Is This Worth the Effort?
For automotive aftermarket parts, absolutely yes. This isn't a nice-to-have optimisation, it's fundamental to making Google Shopping work in this vertical.
The alternative is having product titles that don't match how people search, which means poor relevance scores, low click-through rates, and wasted ad spend on impressions that never convert.
The key is treating your fitment data as the strategic asset it is. If you have comprehensive ACES data, you have everything you need to build a highly effective Google Shopping presence. It just requires the right feed structure to unlock that potential.
Conclusion
Advertising automotive aftermarket parts on Google requires a fundamentally different approach to product feed structure. Because customers search by vehicle rather than by part number, you need to create variants of each product for every vehicle it fits.
The key elements are:
Unique Item IDs for each variant using a suffix system
Vehicle-specific product titles that include year, make, and model
Automation through feed tools to manage the scale of variant creation
Clean fitment data (ideally ACES format) as the foundation
Landing pages that confirm fitment to maintain relevance after the click