Filter Data Health for Shopify
Stop broken filters from costing you sales.
FacetGuard audits your catalog for the attribute issues that make Shopify collection & search filters disappear, explode into noise, or return empty results — then shows you exactly which products to fix.
- Catch collections where filters won’t display
- Find high-cardinality values that hide filter options
- Fix inconsistent option names like Color vs Colour vs Color:
- Spot missing coverage across options & metafields
Designed for Online Store 2.0 storefront filtering and Search & Discovery workflows.
Sample report
Issues Inbox
Filter blocker
Filters won’t display in large collections
Explains why and where it happens, with affected collections.
Collections
At-risk overview
- Summer Sale Blockers
- New Arrivals Coverage
- Accessories Values
Attributes
Value distribution
Find near-duplicates and long-tail noise values.
FacetGuard surfaces product-, collection-, and attribute-level fix lists.
FacetGuard
FacetGuard finds the catalog attribute issues that make Shopify filters messy, missing, or misleading — and gives you a prioritized fix list by product, collection, and attribute.
Core promise
Keep your Shopify filters clean, complete, and conversion-ready. Find the products with attribute problems that break collections and search filters — before customers do.
Why Shopify filters fail silently
Filter issues often don’t look like errors — they look like “the storefront is weird today.” Here are the real-world symptoms FacetGuard is built to catch.
Filters vanish on some pages
Large collections or certain search result contexts can prevent filters from showing at all, leaving shoppers with only “sort” and endless scrolling.
Filter values don’t show
Too many unique values (cardinality explosion) can hide options or dilute the filter list with one-off noise.
“Color” becomes three different things
Inconsistent naming like Color vs Colour vs Color: (or trailing spaces) splits coverage and breaks expectations.
Coverage gaps create “empty” browsing
Missing options or metafield values mean shoppers can’t narrow down — or they filter and see incomplete results.
Variant-level gotchas confuse results
A single product can satisfy multiple filter values across variants (e.g., one product has Red and Blue variants). FacetGuard helps you spot where this behavior creates confusing intersections.
Implementation-aware checks (headless/API)
When storefronts are API-powered, metafield types and schema choices can limit how filters are built. FacetGuard flags readiness issues early.
How it works
FacetGuard is designed to help teams diagnose and fix filter data issues quickly, without guesswork.
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Step 1
Connect
Designed to run read-only audits of your catalog attributes and filter configuration.
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Step 2
Scan & prioritize
Get a single inbox of issues with severity and “where it happens” context (collection, search, attribute).
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Step 3
Fix with product-level action lists
Drill down to the exact products/variants driving the issue, export, and share a report-style summary internally.
Features
Built for merchants, agencies, and teams managing large catalogs — with practical outputs you can act on.
- One place to see all filter-related data issues
- Severity + impact summary (e.g., affects collections/products)
- Drill-down to affected products/variants
- Detect collections where Shopify won’t show filters due to size thresholds
- Flag high-risk search contexts where filters might not appear
- Explain “why” in simple language and show where it happens
- Identify attributes with too many unique values
- Highlight long-tail noise values that dilute filters
- Per-collection breakdown so teams can fix what matters most
- Find near-duplicate option names (case/punctuation/whitespace)
- Coverage: what % of products in a collection actually have “Color”, “Size”, etc.
- List the exact products missing required options
- See which collections are at risk and why
- Issue counts + top offenders
- Export affected products for that collection
- Deep dive per attribute (e.g., Color)
- Value distribution + normalization problems
- See products causing messy values
- Export CSV of affected products/variants per issue
- Mark issues as ignored/resolved to reduce noise
- Easy to share internally as a report-style summary
Coming soon
A few roadmap items we’re actively exploring.
- Grouping/merge suggestions for messy values (exportable “grouping plan”)
- Scheduled monitoring & alerts when new bad values appear
- In-admin product page indicators (“this product is causing filter issues”)
- One-click bulk fixes (future concept, designed for safety + review)
What FacetGuard checks
A focused set of checks that map directly to the ways filtering breaks: visibility, value limits, consistency, and coverage.
Visibility blockers
- • Collections at risk of filters not displaying due to size thresholds
- • High-risk search contexts where filters may not appear
- • Clear “why” explanations tied to where shoppers experience the issue
Cardinality / value limits
- • Attributes with too many unique values (long-tail noise)
- • Per-collection breakdown so you can focus cleanup where it matters
Normalization (naming consistency)
- • Near-duplicate option names (case, punctuation, whitespace)
- • Value normalization issues that create misleading filter choices
Coverage gaps
- • Missing options/metafield values that reduce filter completeness
- • Exact product lists for what’s missing by collection
Metafield readiness (implementation-aware)
- • Checks designed to highlight common headless/API filtering constraints
- • Metafield type and schema choices that can limit filter behavior
Variant-level gotchas
If one product has multiple variant values (e.g., multiple colors), filters can behave in ways that surprise shoppers. FacetGuard flags places where this creates confusing intersections and messy results.
Use cases
FacetGuard fits into how teams actually maintain catalogs — whether you’re in-house or supporting multiple client stores.
Merchants
Keep filters useful as your catalog grows — and prevent “missing filter” surprises.
Agencies
Standardize filter data quality across client stores with repeatable checks and exports.
Developers
Debug filter behavior with clear, URL-level explanations and catalog-level root causes.
Merch teams
Reduce noise and improve navigation consistency with prioritized cleanup lists.
Security & permissions
FacetGuard is designed to focus on catalog attribute health and filter configuration, with a least-privilege posture.
- Designed to run read-only audits
- Least-privilege permissions (scopes are chosen to support catalog checks)
- We focus on catalog attributes, not customer PII
Exact scopes depend on your store setup.
What teams typically share internally
A report-style summary of where filters are at risk, which attributes are noisy, and which products need cleanup — so ops, merch, and dev can align on the same list.
Example summary sections
- • At-risk collections + reasons
- • Noisy attributes (long-tail values)
- • Missing coverage (products to fix)
- • Exports for cleanup workflows
FAQ
Common questions from merchants, agencies, and teams managing filter-heavy catalogs.
Make filters trustworthy again.
Request early access to FacetGuard. Tell us about your catalog size and what’s breaking today — we’ll follow up with next steps.
No pricing on the site yet — we’re focusing on building the right checks and workflows.
Request early access
Send us a note — we’ll follow up with next steps.