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Filter Analytics

Track which filters shoppers use, how they combine filters, and which options are most popular.

Filter Analytics

Filter analytics show you how shoppers interact with your product filters. This data helps you optimize your filter configuration, identify which attributes matter most to your customers, and spot underperforming filters.

What Is Tracked

The analytics client (analytics-client.js) tracks these filter events on your storefront:

EventTriggerData Captured
filter_selectShopper selects a filter optionFilter key, filter value, selected/deselected, collection handle
filter_clearShopper clears a filterFilter key (or "all" for clear all), clear type

Events are batched and sent to the backend every 5 seconds to minimize network requests. A final flush occurs on page unload using navigator.sendBeacon().

Dashboard Views

Filter Usage Overview

Shows aggregate metrics for filter interactions:

  • Total filter interactions -- How many times shoppers selected or deselected filter options
  • Filter usage rate -- Percentage of sessions that used at least one filter
  • Average filters per session -- How many filter options shoppers typically select
  • Top filters -- Ranked list of most-used filters

Filter Usage by Type

Breaks down usage across your filter types:

FilterInteractionsUsage Rate
Color1,23442%
Size98734%
Price Range75626%
Brand54319%

This helps you identify which filters drive the most engagement and which may be candidates for removal or repositioning.

Popular Filter Values

Shows the most frequently selected values within each filter:

  • Color: Black (28%), White (22%), Blue (18%)
  • Size: M (31%), L (26%), S (21%)
  • Price: $25-$50 (35%), $50-$100 (28%)

Filter Combinations

Shows which filters are commonly used together. For example, shoppers who filter by "Color: Black" often also filter by "Size: M." This data can inform how you organize and position your filters.

Date Range Filtering

All analytics views support date range filtering. The default view shows the last 30 days. You can adjust the range using the date picker at the top of the analytics page.

Collection-Level Analysis

Filter analytics can be broken down by collection. This helps you understand:

  • Which filters are most useful on specific collection pages
  • Whether collection-specific filter sets are needed
  • Which collections have the highest filter engagement

Using Filter Analytics

Optimize Filter Ordering

Put your most-used filters at the top of the sidebar. If "Color" gets 42% usage and "Brand" gets 19%, Color should appear first.

Remove Low-Usage Filters

Filters that are rarely used add visual clutter without adding value. Consider removing or collapsing filters with less than 5% usage.

Identify Missing Filters

If shoppers frequently search for attributes you do not offer as filters (visible in search query analytics), consider adding those as new filter types.

Validate Filter Set Decisions

If you have collection-specific filter sets, analytics confirm whether the customization is justified. A filter that gets 0% usage on a specific collection can be removed from that collection's filter set.

Data Retention

Analytics events are retained for 90 days. After 90 days, individual events are purged, but aggregate daily rollups are retained indefinitely for trend analysis.

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