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Build a Keyword Dictionary for Shopify Plus Search (Synonyms, Variants and Must-Win Queries)

22 Jan, 2026 • 9 min read

Why a Keyword Dictionary Is the Fastest Way to Fix “No Results” and Wrong Results

On Shopify Plus, search breaks most often because customers do not search using your product titles.

They search using:

abbreviations (example: “ft” vs “feet”)
shorthand (example: “3x5” instead of “3 ft x 5 ft”)
partial names
misspellings
“customer language” that your catalog never uses

Your internal playbook describes the solution clearly: build high-intent keyword sets per intent, based on past searches and stakeholder notes, then add synonyms/variants/misspellings/abbreviations/customer language and tag “must-win” queries.

That deliverable is what we call a Keyword Dictionary.

What Is a Keyword Dictionary in Ecommerce Search?

A Keyword Dictionary is a structured dataset that maps:

Customer query → intent → expected result behavior
plus, all relevant query variants: synonyms, abbreviations, misspellings, and common phrasing

In your framework, the dictionary is built per intent, not as one giant flat list. That prevents conflicts and keeps relevance predictable.

Step-by-Step: How to Build High-Intent Keyword Sets per Intent

Step 1 - Start With Real Inputs (Not Brainstorming)

Pull keywords from:

Past search history / site analytics (when available)
Stakeholder notes (brand managers, customer support, sales calls)
Common “frustration queries” (where customers expected a match but got nothing)

This matches the playbook: “Reviewed past searches and stakeholder notes to define keywords that must resolve correctly.”

Step 2 - For Each Intent, Create a “Query Cluster”

A query cluster is one intent + all of its variations.

Example structure:

Canonical query (the clean, most standard phrasing)
Variants (format changes: spacing, punctuation, ordering)
Synonyms (different words, same meaning)
Abbreviations (ft/feet, oz/ounces, etc.)
Misspellings
Customer language (how customers naturally describe the product)

Your playbook explicitly calls out adding: “synonyms, variants, misspellings, abbreviations, and customer language.”

Step 3 - Mark “Must-Win” Queries (Non-Negotiable)

Not all searches deserve equal attention.

Your framework recommends marking must-win queries using business criteria:

high revenue
high frequency
high frustration (support tickets/repeats)

Why this matters: Must-win queries become your “unit tests.” They must work immediately and must not regress after catalog changes.

Step 4 - Attach Expected Results Behavior

Every keyword cluster should define the expected outcome:

preferred collections/categories
preferred attributes (size, use-case, etc.)
hero products (best sellers to boost)

This links directly into the next step of your process: attaching best sellers per intent and creating intent → product priority mapping.

The Keyword Dictionary Template (Google Sheet Columns)

This is a practical column set that is both implementation-friendly and audit-friendly.

Tab 1: Keyword Dictionary

Intent Name
Intent Type (product/use-case/attribute/quantity)
Canonical Query
Query Variants (comma-separated)
Synonyms (comma-separated)
Abbreviations (comma-separated)
Misspellings (comma-separated)
Customer Language Notes (free text)
Must-Win? (Yes/No)
Expected Result Type (collection/product list / direct product)
Target Collections (optional)
Hero Products to Boost (optional)
Priority (P0/P1/P2)
Owner (brand manager/support / Webgarh)
Status (draft / implemented/validated)

This aligns with your documented deliverable: “Keyword Dictionary per intent.”

How to Keep the Dictionary “AI-Friendly” and “Search Engine Friendly”

If you want the content (and your process) to be legible to AI models and easy for humans to execute:

Use consistent naming for intents and attributes
Prefer canonical forms (one “standard” version per cluster)
Keep variants as structured lists (not paragraphs)
Store “expected behavior” explicitly instead of implied assumptions
Maintain a “must-win” list and treat it like a QA suite

Common Mistakes That Make Search Worse

Mistake 1: Dumping all synonyms into one global pool

This creates cross-intent conflicts. Your framework avoids that by building keyword sets per intent.

Mistake 2: No “must-win” discipline

If you don’t mark must-win queries, teams waste time tuning low-value searches while high-value searches keep failing.

Mistake 3: Not using stakeholder notes

Brand managers and support teams know the exact language customers use. Your playbook explicitly uses stakeholder notes as an input source.

FAQs

What should a Shopify Plus keyword dictionary include?

Synonyms, variants, misspellings, abbreviations, customer language, and “must-win” flags mapped per intent.

What are “must-win” queries?

High-revenue, high-frequency, or high-frustration searches that must resolve correctly and should be treated like QA tests.

Why build keyword sets per intent instead of a single synonym list?

Because the same word can represent different needs intent separation reduces conflicts and improves relevance control.

Need This Fixed Properly? Explore Our Services

If your store search is hurting conversions, the solution usually isn’t “one tweak” it’s the right storefront foundation + a growth system you can run consistently. At Webgarh, we help Shopify and Shopify Plus brands improve discovery, conversion, and scalability through two proven service tracks:

If your theme, search UX, filters, collections, and performance are limiting results, explore our end-to-end storefront improvements and replatforming capabilities.
Learn more: Storefront Development & Replatforming
If you want a structured roadmap for improving traffic, conversion, retention, and measurable growth, our Build-Grow-Scale model organizes execution across the full ecommerce lifecycle.
Learn more: Build–Grow–Scale Model

Fix Shopify Search Properly (The Shopify Plus Search Improvement Framework)

If you want search improvements that scale (and don’t regress), follow our complete framework:

NEXT > Best Sellers and Merchandising Without Breaking Relevance

How to Rank Best Sellers First Without Making Search Worse

How to Choose the Right Shopify Search Solution (So Results Improve Immediately)

Fixing SKU/UPC Search in Shopify: Reducing Customer Friction

Shopify Plus Search Implementation: Fast Stabilization, Must-Win QA and Iteration

Choosing a Shopify Search App: A Capability Checklist for Large Catalogs

How to fix search on shopify plus store

If customers are searching on your Shopify Plus store but not finding the right products, you are not dealing with a “search feature problem.”

You are dealing with a revenue leak.

Intent Mapping (The Core Differentiator)

Shopify Search Isn’t a Keyword Problem - It’s an Intent Problem

If you want us to improve your store search results and rank the right best sellers without breaking relevance, request our Shopify Search Diagnostic. We’ll review your current search behavior, identify where boosts are helping or hurting and build an intent-based merchandising plan (hero products + query clusters + QA checks) that your team can maintain.
To get started, fill out this short form and share your top sellers and top searches our team will review the inputs and respond with the recommended next steps and the fastest path to implementation.

Money Singla

Money Singla is a high-level Shopify consultant specializing in extending the platform beyond its standard capabilities. With deep expertise in custom development, advanced integrations, and eCommerce strategy, he helps businesses unlock Shopify’s full potential. Whether it’s optimizing store performance, building custom functionalities, or overcoming platform

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