How dxw3 QSP Made WooCommerce Filtering Faster on a 39,000-Product Tire Catalog

Large WooCommerce catalogs can become difficult to use when product filtering is slow. This is especially true for tire and rim stores, where customers often need to narrow products by several technical attributes before they can find the right item.

This case study shows how dxw3 Quick Search Pro, also called QSP, improved product filtering speed on krengas.fi, a WooCommerce tire and rim store with more than 39,000 products.

The goal was simple: make the product search experience faster and more usable for customers.

The problem: large WooCommerce catalogs need fast filtering

krengas.fi was the site where the need for QSP became clear.

The store had a large product catalog, with thousands of tires and rims. Customers needed to filter products by practical tire attributes such as width, profile, season, and brand.

The previous setup used Product Filter for WooCommerce by WBW. It is a general-purpose WooCommerce filtering plugin, and this type of plugin can work well in many stores. But in this large tire catalog setup, the filtering experience was too slow for the kind of product search the site needed.

This was not a theoretical problem. It came from a real WooCommerce store with a real usability issue: customers needed faster product filtering.

The solution: purpose-built indexed filtering with QSP

QSP was built specifically for fast WooCommerce product filtering on large catalogs.

Instead of relying only on the standard WordPress/WooCommerce query path for every filter change, QSP uses a purpose-built indexing system and a faster endpoint-based filtering flow.

The idea is simple:

• store the searchable product attributes in optimized index tables
• query those indexes directly when the customer changes filters
• return matching products quickly
• keep product counts accurate after every filter step

This approach is especially useful for catalog types where products have many structured attributes, such as tires and rims.

Test setup

The benchmark compared the previous WBW filter setup against QSP on the same WooCommerce catalog.

The purpose was not to compare two identical query implementations. The purpose was to compare the real visitor experience of the previous general-purpose filter setup against QSP’s indexed filtering system.

The test conditions were:

• same WooCommerce site
• same product catalog
• same filter steps
• logged-out visitor testing
• LiteSpeed Cache disabled
• browser cache disabled in Chrome DevTools
• product counts checked after each step
• each step measured three times
• median result used

The main number used in the comparison is results visible time. This means the time from the user action until the updated product results were visible on screen.

Benchmark results

Step	Action	Products	WBW results visible	QSP results visible
T1	Initial page load	39,415	14.36 s	1.99 s
T2	Add tire width 205	658	10.79 s	0.41 s
T3	Add tire profile 55	171	2.81 s	0.38 s
T4	Add season: summer	100	2.82 s	0.42 s
T5	Change tire width to 215	93	2.92 s	0.77 s
T6	Go to results page 2	93	12.10 s	0.37 s

In every measured step, QSP returned the results faster.

The largest differences appeared in the first filter selection and pagination. Selecting tire width 205 took about 10.79 seconds before results were visible with the previous WBW setup. With QSP, the same step took about 0.41 seconds.

Going to page 2 took about 12.10 seconds with the previous WBW setup and about 0.37 seconds with QSP.

Technical request comparison

Visible speed is the most important number for customers, but the technical request data also showed a clear difference.

Step	Action	WBW main request	QSP main request	WBW transferred data	QSP transferred data
T1	Initial page load	13.66 s	1.52 s	2.0 MB	1.5 MB
T2	Add tire width 205	8.61 s	0.27 s	3.7 MB	0.2 MB
T3	Add tire profile 55	1.37 s	0.24 s	2.1 MB	0.2 MB
T4	Add season: summer	1.08 s	0.23 s	2.3 MB	0.2 MB
T5	Change tire width to 215	1.18 s	0.49 s	4.3 MB	0.5 MB
T6	Go to results page 2	10.45 s	0.23 s	2.5 MB	0.1 MB

The QSP requests were consistently lighter and faster.

For the width change test, QSP required two UI actions, so both actions were added together for a fair comparison.

Why the difference matters

In a large product catalog, filtering speed directly affects usability.

A customer searching for tires may not only select one filter. A realistic search flow can include several steps:

1. select tire width
2. select tire profile
3. select season
4. select brand
5. go to the next result page

If each step takes several seconds, the search experience starts to feel heavy. Customers may stop using the filters, leave the page, or fail to find the right product.

QSP makes this flow feel much closer to instant. That is the practical benefit of using an indexed filtering system for a large WooCommerce catalog.

Fairness note

This benchmark is not a universal claim about every WBW installation or every WooCommerce store.

It compares the installed WBW Product Filter configuration previously used on krengas.fi against QSP on the same catalog, using the same progressive filter steps and matching product counts.

Reset behavior was excluded from the main comparison because WBW’s AJAX reset returned two fewer products than the initial page load in this setup, while a full reload returned the original count. QSP reset returned the same count as the initial page load.

The main benchmark focuses on the filter steps where both systems returned matching product counts.

The result

QSP is now running live on krengas.fi with the improved indexing engine.

The result is a much faster product filtering experience for a WooCommerce catalog with more than 39,000 products.

For this type of store, the benefit is clear: customers can narrow products faster, product counts remain accurate, and the filtering experience feels much lighter than the previous setup.

Conclusion

General-purpose WooCommerce filter plugins are flexible, and they can be a good fit for many stores. But large structured catalogs, such as tire and rim stores, often need a more specialized approach.

QSP was built for this problem.

On krengas.fi, QSP replaced a slower filtering flow with a purpose-built indexed filtering system. The same product catalog and the same filter steps produced the same result counts, but the results became visible much faster.

For WooCommerce stores with large catalogs, this kind of speed improvement can make product search feel usable again.

Need faster WooCommerce filtering?

QSP is designed for WooCommerce stores with large product catalogs where standard filtering becomes too slow.

It is especially suitable for stores with structured product data, such as:

• tires
• rims
• spare parts
• technical products
• products with many attributes
• large B2B or B2C catalogs

Learn more about dxw3 Quick Search Pro or contact dxw3 for a performance-focused WooCommerce filtering solution.