Method Race Wheels: Shopify Year, Make and Model Search and Vehicle Fitment

Method Race Wheels makes race-proven wheels for trucks, Jeeps, cars and UTVs, sold through dealers and its own Shopify store.

Every wheel comes in many sizes, bolt patterns and offsets, and each combination is its own part number. A customer who knows their vehicle still has to work out which of those combinations will bolt on, and a wrong guess means a return of a heavy, mounted product.

When Method's marketing team reached out, the catalog already lived in Shopify with sizing as product variants. The fitment knowledge lived somewhere else: in a master parts list the engineering team updated fifteen to twenty times a year, and in a vehicle database held by a third-party fitment vendor. Nothing connected the two to the store. Customers browsed by series and called in to ask what fit.

Enter a vehicle, see only the wheels that fit it.

Method wanted shoppers to enter a vehicle and see only the wheels that fit it, on every collection page and on the product page itself. The team also wanted a second way in for customers who already know their specs: diameter, bolt pattern and finish. Both had to run off the master parts list the team already maintained, and both had to match the way serious off-road customers shop, which is fast, with no questions a gearhead would find pointless.

The reference points were the big tire and wheel retailers. The difference was that Method's catalog is one brand, one list of parts, and a team that knows exactly which vehicle each part belongs on.

The finder went through two rounds of design with Method's team.

Before the application work began, our design team ran a homepage concept for Method as one of its weekly design challenges, and the client's team asked to keep it in the conversation. The filter design went through two rounds with Method: a set of layouts, from which the team chose the horizontal bar, and then a background study that settled on Method's own orange, with the active tab turning black.

The result sits directly under the hero on the homepage and under the banner on every collection: two tabs, Shop by Vehicle and Shop by Fitment, and a single row of selects.

The first release put both finders on the store.

The vehicle finder connected to the fitment vendor's API and the parts list; the fitment finder ran on the parts list alone.

The vehicle finder takes year, make and model and returns the wheels and the exact part numbers that fit. The fitment finder cascades from left to right: choose a diameter and the bolt pattern list narrows to the patterns that exist in that diameter, choose a pattern and the finishes narrow again, with All Finishes as the default and the patterns sorted from smallest to largest. Results update as each selection is made, without a search button. On a collection page the finder filters within that collection and keeps the collection's own merchandising order. The selection persists from page to page, with a Showing filtered results bar at the top of the grid and a clear button to start over.

With a vehicle selected, the product page shows only the variants that fit it.

A wheel product page at Method lists every size, bolt pattern and offset as a variant, which is dozens of options on a popular design. With a vehicle selected, the page shows only the variants that fit that vehicle, so the dropdown drops from a long list to the one or two part numbers a customer can actually order. The selected vehicle is displayed above the options, and where the parts list carries a note for that combination, such as a cap that cannot be used, the note appears before the Add to Cart button.

The application behind the finders holds its own map of the parts list to Shopify.

It keeps a database with the master parts list on one side and the Shopify product and variant IDs on the other, mapped once so a lookup does not have to call out for every part. A sync against the Shopify catalog runs every few hours. Method's team updates the parts list from an admin screen with a CSV upload and a dry run that checks the file before anything changes, and new sizes, patterns and finishes appear in the finders when the list does.

The vehicle data moved twice during the engagement, and the customer never saw it.

The original vendor's API needed body and option selections before it would return a fitment, which the team felt was too many questions for its customers, so the vehicle finder was taken off the homepage while Method built its own fit guide. Method later moved its fitment data into a PIM with its own API, and we rebuilt the vehicle finder against it: the theme now calls the PIM directly for year, make, model and submodel, passing the Shopify collection or product on the request so the results are already scoped to the page. Submodels appear only when the vehicle has them and must be chosen when they do. The orange bar, the product page filtering and the way the finder behaves stayed the same for the customer throughout.

The second release checks every line item in the cart against the selected vehicle.

Method wanted every order checked against a vehicle before it shipped, instead of relying on a notes field customers filled in by hand, so the second release added a check in the cart. A green bar under the item confirms the fitment, a red bar marks a part that could not be verified, and a customer with no vehicle selected is asked to add one. Any fitment note from the PIM, such as a cap or fender clearance warning, is repeated under the item. The order carries a note recording whether the fitment was verified, so the team sees it before the wheels ship. Apparel and accessories are tagged so the check skips them, and the wording of every message is editable in the theme.

Alongside the finders we handled the theme work a store like this accumulates.

Product videos playing in the product gallery from files hosted in Shopify rather than YouTube, dealer news kept out of search results, theme speed work, pagination fixes on the long wheel collections, and an audit of the apps adding code to the storefront. One bug took several days to pin down because Shopify was returning a different number of products depending on the visitor's browser and device; finding it is the kind of work a brand should not have to do alone.

Method eventually consolidated its fitment data and lookups with its PIM vendor, and the Conspire-hosted application was retired.

The store still leads with a vehicle finder today. Since then, brands in the automotive space have come to us having seen the Method store and asked for its search by name.

Does year, make and model search on Shopify need an app?

It needs a data source that maps vehicles to part numbers, and something that turns those part numbers into Shopify products and variants on the page. For Method that was a small application of our own, then the brand's PIM API called straight from the theme. An off-the-shelf fitment app can work when its vehicle database matches the catalog; when a brand holds its own fitment knowledge, building on that data is usually the better store.

What about the product page?

This is where most fitment implementations stop short. Filtering a collection by vehicle is useful; filtering the variant dropdown on the product page to the parts that fit is what prevents the wrong order.

Can the brand's team maintain it?

Yes, if the data lives where the team already works. Method's team updated the parts list it was already keeping, and later its PIM, and the storefront followed.

Conspire is a Shopify Plus Premier Partner founded in Los Angeles in 2011. We build Shopify stores and run fractional Shopify teams for established brands.