How to configure the YMM (fitment) search
The next big step of Convermax setup is to configure data sources.
How does the Convermax YMM search work
The general idea
Our app uses a set of data sources to configure accurate search results by vehicle inside your store.
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First, we use data that comes from the platform. We pull all product data with their fields from ==BigCommerce.==
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Secondly, our engine processes all products with the store’s custom logic (if present) to get additional filters working and analyzes fields like ==Type and Category== to determine where to obtain external data.
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In the third step, fitment information is loaded from external resources (e.g., SEMA Data Co-op, PDM, etc.) and internal sources (tags and metafields). How this data is connected with the products is ==shown below== We call the vehicle with the product identifier a fitment. The list of vehicles available on the YMM panel consists of all fitments used by any product.
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The fourth step is loading additional attributes from external resources. It can be wheel and tire information from a data provider (e.g., DriveRightData, FitmentGroup, etc.) or custom data. Custom data may come in different forms:
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product attributes defined in custom fields,
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a spreadsheet provided by the store listing information on the compatibility of wheel-tire attributes with vehicles.
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When all the preparation work is done, this combined data is saved to an index that will be used to process the search requests. The index automatically updates on a schedule, every 12 hours by default.
You can see all supported integrations on our website. Most of them can be ==connected through the Fitment Sources page== in our app.
Also, we have a list of supported custom fitment data formats with guides on how to connect them in our ==doc pages==
Matching products with fitments aka mapping
First, we download all fitment data, process it to achieve a more unified format, and save it to a separate search index. Second, we do the fitment matching.
In general, there are three methods we use to apply fitments to the product:
- Fitments that are stored on the product, in ==custom fields==. They are just applied to the product they’re stored on.
- Fitments from custom data sources. They are considered to be made for use at the exact store and therefore matched using the SKU.
- The most complicated method is matching products with fitments from all different integration sources. Depending on the source, we can use the product SKU itself, or try to extract an MPN part from it and use it with the product brand. Sometimes the SKU is used unchanged; in other cases, we transform it or use pattern matching to form a search request to a fitment data index. The brand also can be transformed inside the search process to match the data source canonicals.
All these different approaches are aimed at improving the fitment coverage, but still, using canonical brand names and unchanged manufacturer SKUs shouldn’t be underestimated in achieving success.