If scoring results seem inconsistent, check for conflicting factors – high weights on opposing criteria can create unpredictable results
For performance issues with large catalogs, reduce the batch size in the performance settings area
If certain products never appear in top positions despite high scores, verify you haven’t accidentally excluded their categories or tags
When scores aren’t reflecting recent sales, check that your “Orders from” timeframe is appropriate for your sales volume
If custom fields aren’t influencing scores correctly, verify the exact field name in your database and ensure the data type selection matches the actual data
For unexpected ranking behavior, use the preview function to isolate which factor is causing the issue by temporarily setting others to zero
If tags or categories aren’t affecting scores as expected, verify you’ve entered the correct slugs (not names) in the field below the slider
When changes don’t seem to take effect, try forcing a manual recalculation of scores
For server timeout issues during calculations, try increasing PHP memory limits or reducing the calculation batch size
If frontend sorting doesn’t match backend preview, check for caching plugins that might be preserving old sort orders

When making complex changes, adjust one factor at a time and test the results to maintain a clear understanding of how each change affects your overall product ordering.

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• Begin by analyzing your unique store characteristics – product types, customer behavior, inventory cycles, and business objectives
• Create a “baseline” formula that reflects your general business priorities as a starting point
• Adjust individual sliders to match your store’s specific needs:
  • Fashion stores: Emphasize Creation Date with a shorter threshold to highlight new arrivals
  • Electronics stores: Balance Reviews and Revenue factors to promote reliable, popular items
  • Seasonal businesses: Use Categories and Tags with higher weights to promote in-season merchandise
  • Specialty stores: Leverage Custom Meta fields to prioritize products with store-specific attributes
  • High-volume retailers: Increase Stock factor weight to prevent overselling popular items
• Consider your business cycle when developing strategies – create different formulas for different periods
• For stores with diverse product categories, consider creating separate strategies for different sections
• Use the preview feature extensively when building your unique formula to ensure results match expectations
• Document successful configurations so you can replicate or modify them for future campaigns
• Monitor performance metrics after implementing new strategies to measure their effectiveness

Remember that effective ranking strategies should align with your overall business goals – whether that’s maximizing profit margins, clearing excess inventory, or promoting specific brands or collections.

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• Each vertical slider represents a factor in your scoring formula and can be positioned to reflect its relative importance
• The higher you position a slider, the more influence that factor has on the final product score
• To create an effective weighted formula, consider which factors are most important for your current business objectives
• Balance complementary factors – for example, combine Revenue (30% importance) with Stock (20%) and Reviews (20%) with the remaining weight distributed to other factors
• For seasonal strategies, adjust your weights temporarily – increase the Category slider and add your “Summer” category to the field below
• Test different combinations using the Preview button to see how products reorder before implementing changes
• Create formulas for specific scenarios:
  • Bestseller focus: Position Revenue slider high, with moderate Stock influence
  • New arrivals: Position Creation Date slider high with a 14-30 day threshold
  • Clearance: Position Stock slider high with “over” threshold setting and add clearance tags
  • Profit maximization: Position Custom Meta slider high configured for margin data

The power of WooRanker comes from combining these factors into balanced formulas that automatically adjust your product rankings based on real-time store performance data.

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• Locate the Categories and Tags sliders in the WooRanker configuration panel
• Adjust the vertical slider position to determine how strongly these factors influence the final score
• In the field below the slider, add the specific category or tag slugs you want to prioritize
• Products with these tags or in these categories will receive a scoring boost based on the slider position
• You can add multiple categories or tags and they will all contribute to the score
• Use this feature to highlight seasonal collections, promotional items, or strategically important product groups
• Combine with other factors like Revenue or Stock for more nuanced ranking strategies
• Preview the results before saving to ensure your priority products are appearing as expected

This approach gives you precise control over which product groups receive extra visibility in your store without having to manually reorder hundreds of items. It’s particularly useful for promotional campaigns or when launching new product lines that need additional exposure.

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• Activate custom field scoring by toggling the blue “On” switch in the Custom Post Meta panel
• Set your desired influence level by adjusting the vertical slider position – higher positions give custom fields more weight in the final score
• Choose the appropriate data type from the “Postmeta Type” dropdown:
  • “Numerical” for number values (profit margins, inventory age, etc.)
  • “String” for text values (product conditions, materials, etc.)
  • “Existence” to check if a field simply exists or not
• For numerical fields, select a comparison operator (=, >, >=, <, <=, !=) and enter a threshold value
• Configure scoring methods like “Percentage” to determine exactly how values translate to scores
• In the “CHIP NAMES” field, enter the exact custom field keys you want to include in your scoring formula

This feature is particularly valuable for stores with specialized inventory characteristics or unique business models where standard factors don’t fully capture product prioritization needs. By incorporating your custom data, you can create scoring logic that precisely matches your specific business requirements.

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