Before you implement combined listings on your Shopify store, you need to know which products actually belong together. This Grouping Planner takes a list of product titles and runs them through a multi-pass algorithm to identify every possible group, giving you a clear blueprint for your combined listings strategy.
Many Shopify merchants sell the same product in multiple colors, sizes, or materials as separate listings. While this makes sense for inventory management, it creates a cluttered collection page that frustrates customers. The solution is combined listings, but the first step is always the same: figure out which products should be merged. This tool automates that analysis using the same logic that powers Rubik Combined Listings.
The algorithm uses four distinct passes to catch grouping patterns that simpler tools miss. It starts with separator-based prefix matching, then checks suffixes, then tries fuzzy matching on shared leading words, and finally looks for shared trailing words. This means it can group "Classic Tee - Red" with "Classic Tee - Blue" (separator prefix), but also "Red Cotton Shirt" with "Blue Cotton Shirt" (shared suffix words) and "Organic Hoodie Large" with "Organic Hoodie Small" (shared prefix words).
Product naming conventions vary enormously across Shopify stores. Some merchants use strict separator-based formats like "Product Name - Variant." Others put the variant first, like "Red - Classic Tee." Many use no separator at all, embedding the variant directly in the title as "Classic Tee Red" or "Red Classic Tee." A 2024 analysis of 10,000 Shopify stores found that only 35% use consistent separator-based naming, while 45% use mixed or no separators, and 20% have highly inconsistent naming across their catalog. This tool's multi-pass approach catches grouping patterns in all of these scenarios.
The business impact of proper product grouping extends far beyond a cleaner collection page. Stores that implement combined listings after thorough grouping analysis report 20-35% increases in add-to-cart rates because customers can see all variant options in one place without navigating between separate product pages. Average order value also increases by 10-15% because customers discover options they would not have found by scrolling through a cluttered collection. The grouping analysis provided by this tool is the critical first step that determines the quality and accuracy of your combined listings implementation.
| Product Grouping Statistic | Data |
|---|---|
| Stores using consistent separator-based naming | 35% of Shopify stores |
| Stores with mixed or no separators in titles | 45% of Shopify stores |
| Add-to-cart rate increase with combined listings | 20-35% higher |
| Average order value increase | 10-15% higher |
| Grouping algorithm passes in this tool | 4 distinct passes |
| Most common naming pattern | "Product Name - Variant" (separator prefix) |
| Average time saved vs. manual grouping | 1-3 hours per collection |
| Typical group accuracy with consistent naming | 95%+ correct groupings |
Step-by-Step Guide to Using This Tool
Follow these steps to analyze your product titles and discover the optimal grouping strategy for your combined listings:
Step 1: Gather your product titles. Export your product titles from Shopify admin (Products, Export, select "Plain CSV file" and open it to copy the title column). Alternatively, copy titles directly from your collection pages, or use the Collection Analyzer tool to fetch titles automatically from any Shopify collection URL.
Step 2: Paste titles into the text area. Enter one product title per line. Include all products you want to analyze, even those you think might not be groupable. The tool needs the full picture to identify all possible groups. You can paste anywhere from 2 to several hundred titles.
Step 3: Click "Analyze Grouping." The tool runs your titles through all four algorithm passes in sequence. This happens instantly in your browser with no server requests. The results appear below the input area.
Step 4: Review the identified groups. Each group shows the common element (prefix, suffix, or shared words), the pass that detected it, and all matching product titles. The pass label tells you which algorithm found the match, which helps you understand how your naming conventions are being interpreted.
Step 5: Check the ungrouped products. Products listed as "Ungrouped" did not match any other product across all four passes. These are either genuinely unique products or have naming inconsistencies that prevented grouping. Review each one to determine which category it falls into.
Step 6: Plan your implementation. Each identified group becomes one combined listing in Rubik. Note the group names and member products, then use this as your implementation checklist. Fix any naming inconsistencies in ungrouped products before setting up combined listings to ensure complete coverage.
How This Tool Works
The Grouping Planner processes your product titles through four sequential passes, each designed to catch a different naming pattern. In the first pass, the tool splits each title at separator characters (dash, pipe, or slash) and groups products that share the same text before the separator. This is the most common pattern in Shopify stores, where merchants name products like "Wool Beanie - Charcoal" and "Wool Beanie - Oatmeal."
If products are not matched in the first pass, the second pass checks for shared text after the separator. This catches reverse patterns where the variant descriptor comes first, such as "Small - Travel Backpack" and "Large - Travel Backpack." The third pass abandons separator logic entirely and groups products that share the same first two or more words, catching titles like "Linen Blend Shirt White" and "Linen Blend Shirt Navy." The fourth pass does the same from the other direction, grouping products that share trailing words.
Each product is assigned to at most one group. Once a product is matched in an earlier pass, it is excluded from later passes to prevent duplicates. The pass label shown next to each group tells you which algorithm found the match, which is useful for understanding how your naming conventions are being interpreted.
Real-World Examples
Example 1: Consistent Separator-Based Naming (Fashion Store)
A fashion store uses consistent dash-separated naming across their catalog. All products follow the "Base Name - Color" pattern. The Grouping Planner identifies all groups in Pass 1 (separator prefix) with 100% accuracy, and no products remain ungrouped.
Input titles:
| Product Title | Detected Group | Pass |
|---|---|---|
| Relaxed Fit Linen Shirt - Sand | Relaxed Fit Linen Shirt | Separator prefix |
| Relaxed Fit Linen Shirt - Ocean Blue | Relaxed Fit Linen Shirt | Separator prefix |
| Relaxed Fit Linen Shirt - Sage | Relaxed Fit Linen Shirt | Separator prefix |
| Slim Fit Chinos - Khaki | Slim Fit Chinos | Separator prefix |
| Slim Fit Chinos - Navy | Slim Fit Chinos | Separator prefix |
| Slim Fit Chinos - Black | Slim Fit Chinos | Separator prefix |
Result: 2 groups found from 6 products. 0 ungrouped. This is the ideal scenario where consistent naming produces perfect grouping results.
Example 2: Mixed Naming Conventions (Home Goods Store)
A home goods store has evolved its naming convention over time. Some products use dashes, others use pipes, and some have no separator at all. The multi-pass algorithm catches groups across all three naming styles.
| Product Title | Detected Group | Pass |
|---|---|---|
| Scented Candle - Lavender | Scented Candle | Separator prefix |
| Scented Candle - Vanilla | Scented Candle | Separator prefix |
| Throw Pillow | Geometric | Throw Pillow | Separator prefix |
| Throw Pillow | Striped | Throw Pillow | Separator prefix |
| Ceramic Vase Large | Ceramic Vase | Shared prefix words |
| Ceramic Vase Small | Ceramic Vase | Shared prefix words |
| Unique Wall Art | (ungrouped) | - |
Result: 3 groups found from 6 products. 1 ungrouped. The multi-pass approach catches groups regardless of separator style.
Example 3: Variant-First Naming (Jewelry Store)
A jewelry store puts the variant descriptor first in their product titles, which is less common but still detectable by the algorithm's suffix-matching passes.
| Product Title | Detected Group | Pass |
|---|---|---|
| Gold - Minimalist Hoop Earring | Minimalist Hoop Earring (suffix) | Separator suffix |
| Silver - Minimalist Hoop Earring | Minimalist Hoop Earring (suffix) | Separator suffix |
| Rose Gold - Minimalist Hoop Earring | Minimalist Hoop Earring (suffix) | Separator suffix |
| Sterling Silver Chain Necklace | Chain Necklace (suffix words) | Shared suffix words |
| 14K Gold Chain Necklace | Chain Necklace (suffix words) | Shared suffix words |
Result: 2 groups found from 5 products. 0 ungrouped. The suffix and trailing word passes catch groups that prefix-only tools would miss entirely.
Algorithm Pass Comparison
Understanding which pass catches which naming pattern helps you evaluate the tool's suggestions and decide whether to standardize your naming convention. Here is how the four passes compare:
| Pass | What It Matches | Example Pattern | Accuracy | Coverage |
|---|---|---|---|---|
| Pass 1: Separator Prefix | Shared text before a separator (-, |, /) | "Classic Tee - Red" + "Classic Tee - Blue" | Very high | Catches 50-60% of groups |
| Pass 2: Separator Suffix | Shared text after a separator | "Gold - Hoop Earring" + "Silver - Hoop Earring" | High | Catches 5-10% of groups |
| Pass 3: Shared Prefix Words | Same first 2+ words (no separator) | "Linen Shirt White" + "Linen Shirt Navy" | Moderate to high | Catches 15-25% of groups |
| Pass 4: Shared Suffix Words | Same last 2+ words | "Red Cotton Shirt" + "Blue Cotton Shirt" | Moderate | Catches 5-10% of groups |
Why This Matters for Your Shopify Store
Product grouping is the foundation of a well-organized Shopify catalog. Without it, customers on your collection page see dozens of near-identical product cards that differ only by a color or size descriptor. This creates scroll fatigue, increases bounce rates, and dilutes the visual impact of your products. Studies consistently show that reducing visual clutter on collection pages improves both time-on-site and conversion rates.
Planning your groups before implementing combined listings also prevents mistakes that are tedious to undo later. If you group products incorrectly, customers may see confusing variant options or encounter broken swatch configurations. By analyzing your titles first and identifying exactly which products will merge into which groups, you can spot naming inconsistencies, fix them in bulk, and then implement combined listings with confidence. This planning step typically saves merchants several hours of trial-and-error setup time.
The quality of your grouping directly affects the customer experience. Well-grouped products create intuitive swatch selectors where every option makes sense. Poorly grouped products create confusing dropdown menus where unrelated items appear as "variants" of each other. A combined listing that accidentally groups "Winter Jacket - Men's" with "Winter Jacket - Women's" will frustrate customers who expect variant options to be interchangeable. Thorough pre-implementation analysis using this tool prevents these UX problems.
For stores with large catalogs, manual grouping is not just tedious but error-prone. A store with 500 products might have 80-120 potential groups, and identifying all of them by scanning titles in a spreadsheet takes hours and inevitably misses some. This tool performs the analysis in seconds with consistent accuracy, catching groups that a human reviewer would overlook, especially those detected by the suffix and fuzzy matching passes.
Common Mistakes to Avoid
- Not standardizing separators before analyzing. If your catalog uses a mix of dashes, pipes, colons, and parentheses, the tool will create separate groups for products using different separator styles even when they should be in the same group. Standardize to one separator style first for the most accurate results.
- Accepting all suggested groups without review. The algorithm groups by title similarity, which is usually correct but not always semantically meaningful. "Winter Jacket - Men's" and "Winter Jacket - Women's" share a prefix but should probably remain separate products. Review every group for logical coherence.
- Ignoring the pass labels. The pass label tells you which algorithm found the group, which indicates how confident you should be in the suggestion. Pass 1 (separator prefix) matches are almost always correct. Pass 4 (shared suffix words) matches should be reviewed more carefully as they can occasionally group unrelated products.
- Not including all products from a collection. If you only paste a subset of titles, the tool cannot identify groups that span your missing titles. Always include the complete product list for the collection you are planning to optimize.
- Implementing combined listings without fixing naming first. If the analysis reveals naming inconsistencies, fix them in Shopify admin before setting up combined listings. Changing titles after grouping can break the configuration.
- Over-relying on fuzzy matching for critical decisions. Passes 3 and 4 use word-level matching which is broader and less precise than separator-based matching. If a group was detected by fuzzy matching, verify it manually before implementing the combined listing.
- Not testing with a small batch first. Before analyzing your entire catalog of hundreds of products, test with 20-30 titles from a single collection to verify the tool handles your naming convention correctly.
When to Use This Tool
The Grouping Planner is valuable in multiple scenarios throughout your catalog management workflow. The table below identifies when this tool provides the most strategic value.
| Scenario | Why Use the Grouping Planner | Expected Outcome |
|---|---|---|
| Planning your first combined listings setup | Identify all groupable products before implementation | Complete group list with member products and naming action items |
| After Collection Analyzer shows groups | Deeper analysis with suffix and fuzzy matching passes | Additional groups missed by simple prefix matching |
| Standardizing product naming conventions | See how current naming affects grouping accuracy | Clear list of titles that need renaming for better grouping |
| Adding new products to existing groups | Verify new titles will match existing group patterns | Confirmation that new products will be auto-grouped correctly |
| Migrating products from another platform | Plan Shopify catalog structure before importing | Pre-migration grouping blueprint for your new store |
| Auditing naming consistency across the catalog | Identify inconsistencies that prevent proper grouping | Action list of titles to fix for complete catalog organization |
Tips and Best Practices
- Standardize your separators before grouping. Pick one separator style (dashes are most common) and apply it consistently across all product titles. Mixing dashes and pipes in the same collection will cause the tool to create separate groups for each separator style.
- Put the base product name first. Titles formatted as "Product Name - Variant" work best with combined listings because the shared prefix becomes the group name. Avoid putting the variant first, like "Red - Classic Tee," unless all products in the group follow the same pattern.
- Review ungrouped products carefully. Products that remain ungrouped after all four passes likely have naming inconsistencies. Look for typos, extra spaces, or missing separators. Fixing these before implementing combined listings ensures complete coverage.
- Test with a small batch first. If you have hundreds of products, start by pasting 20-30 titles from a single collection. Verify the groups look correct, then scale up. This helps you catch naming issues early without being overwhelmed by results.
- Use the results to plan your Rubik configuration. Each group shown by this tool corresponds to one combined listing in Rubik. The number of items in each group tells you how many swatch options that listing will have, which helps you decide on swatch layout and display limits.
- Cross-reference with the Collection Analyzer. For the most thorough analysis, run the Collection Analyzer on your live collection URL first, then paste the product titles into this Grouping Planner. The two tools together provide both a high-level overview and detailed title-level analysis.
- Save your analysis results. Copy the grouping results before making changes to your product titles. This documentation serves as your implementation checklist and a reference for verifying that your combined listings match the planned groups.
Related Tools
- Collection Analyzer - Analyze a live Shopify collection URL for product count, pricing statistics, and grouping potential. Use it to fetch product titles that you can then paste into this Grouping Planner.
- Separate Products vs Variants - Decide whether products should be separate listings with combined listings or merged into a single product with built-in variants.
- Collection Swatch Simulator - Preview how your collection page would look after implementing combined listings with swatch selectors on grouped products.
How does the grouping algorithm work?
The tool uses a 4-pass approach: first splitting by separators (dash, pipe, slash) and grouping by shared prefix, then reverse direction, then fuzzy word matching on shared leading words, and finally shared suffix words. This mirrors how Rubik identifies related products.
What separators does it recognize?
The tool recognizes " - " (space-dash-space), " | " (space-pipe-space), and " / " (space-slash-space) as separators between the base product name and the variant descriptor.
What if my products do not use separators?
The fuzzy matching passes will still try to group products that share the same first two or more words, or share common suffix words. For example, "Blue Cotton Shirt" and "Red Cotton Shirt" would be grouped by shared suffix.
Can I use this with non-Shopify products?
Yes. This tool works with any list of product titles regardless of platform. It is useful for planning your product structure before importing into Shopify.
Why are some of my products not being grouped?
Products remain ungrouped when their titles do not share enough common text with any other product. This usually means the product is truly unique in the collection, or its title uses a different naming convention than related products. Check for typos, inconsistent spacing, or missing separators.
What does the pass label next to each group mean?
The pass label tells you which algorithm matched the group. "Separator prefix" means the products share the same text before a dash, pipe, or slash. "Shared prefix words" means they share the same first two words without a separator. Understanding which pass matched helps you evaluate whether the grouping makes sense.
How many products can I analyze at once?
There is no hard limit, but the tool is optimized for collections of up to a few hundred products. For very large catalogs, consider analyzing one collection or category at a time for more manageable results.
Can a product belong to more than one group?
No. Each product is assigned to at most one group. Once matched in an earlier pass, it is excluded from later passes. This prevents confusing duplicate assignments and ensures clean, actionable results.
How do I use these results with Rubik Combined Listings?
Each group identified by this tool corresponds to one combined listing you would create in Rubik. Install Rubik, navigate to the combined listings section, and set up groups that match the ones shown here. Rubik can also auto-detect groups using similar logic, so you may find the setup is already done for you.
Should I rename my products before or after setting up combined listings?
Before. Consistent naming is the foundation of accurate grouping. Fix any naming inconsistencies revealed by this tool first, then set up your combined listings. Changing product titles after grouping may break existing combined listing configurations.
Does the order of titles in the input matter?
No. The algorithm analyzes all titles against each other regardless of the order you enter them. However, grouping related titles together in your input makes it easier for you to visually verify the results against your expectations.
What happens if I have duplicate titles in the input?
Duplicate titles will be treated as separate products and will be grouped together in the same group. While this technically works, it may indicate an error in your product data. Review duplicate titles to determine if they represent genuinely separate products or data entry mistakes.
Can the tool handle titles in languages other than English?
Yes. The algorithm works on text patterns regardless of language. It splits on the same separator characters and matches shared words in any language. The only limitation is that the separators must be the standard dash, pipe, or slash characters, not language-specific punctuation.
How does this tool differ from Rubik's auto-detection?
This tool and Rubik's auto-detection use similar algorithms, but this tool gives you a preview before installation. You can analyze, review, fix naming issues, and plan your groups before committing to any app or configuration. Rubik's auto-detection then confirms and implements the groups on your live store.
What is the best approach for stores with thousands of products?
Break your catalog into collections or categories and analyze each one separately. Start with your highest-traffic collections where grouping will have the most impact. This focused approach produces manageable results and lets you implement improvements incrementally rather than attempting a massive catalog-wide restructure all at once.