Magento 2 Product Sorting Options: Popularity Sorting for Store Growth

• Types of Magento 2 Product Sorting Options

• Why Does Sorting by Popularity Matter?

• How to Put Popularity Sorting in Place in Magento 2?

• Summary

Types of Magento 2 Product Sorting Options

1. Default Sorting Options

Magento 2 product sorting organizes items according to position, name, and price. Store administrators access these through:

Catalog > Categories > Display Settings > Default Product Listing Sort By

Available Options

• Position Sorting: Manual arrangement that needs updates as inventory changes.

• Name Sorting: Alphabetical organization, which offers limited customer value.

• Price Sorting: Cost-based ordering that misses behavioral data.

These default options serve basic organizational needs. They lack advanced metrics that track customer behavior patterns.

2. Extended Sorting Options

Better sorting needs more functionality beyond core Magento capabilities. 2 primary approaches deliver popularity-based sorting.

Setup Approaches

• Extension Use: Pre-built solutions from the Magento marketplace.

• Custom Development: Tailored solutions for:

  • Unique business requirements

  • Advanced sorting algorithms

Extension solutions offer rapid deployment. Custom development provides complete customization for complex business logic.

Why Does Sorting by Popularity Matter?

1. Better Discoverability

Popularity sorting places high-performing products in prominent positions. The system tracks customer behavior patterns.

Elements of Buyer Behavior

• Buying Frequency: Sales volume over specified time periods.

• Activity Metrics: Page views, time spent, and interaction rates.

• Social Validation: Review scores and customer rating aggregation.

This automated promotion removes manual curation. It puts trending products in visibility spots on Magento category pages.

2. Higher Conversion Rates

Popular products convert at higher rates through psychological social proof mechanisms. Customer behavior research shows clear benefits.

Trust Building Factors

• Previous Buyer Validation: Cuts down buying hesitation.

• Decision Help: Proven choices lessen customer cognitive load.

• Risk Reduction: Popular items carry implicit quality endorsements.

Customers find relevant products faster. Thus, they feel more confident about their buying decisions.

3. Better User Experience

Popularity-based sorting creates intuitive navigation. It matches customer expectations from social platforms and modern e-commerce sites.

User Experience Benefits

• Expectation Alignment: Customers expect relevant, trending content first.

• Less Friction: Faster product discovery cuts abandonment rates.

• Higher Satisfaction: Meeting user expectations makes the site experience better.

This approach cuts customer frustration and search time. It increases activity metrics across touchpoints.

4. Data-Based Decisions

Popularity metrics provide usable business intelligence for planning decisions.

Key Data Elements

• Trend Identification: Spot which products customers want before competitors do.

• Inventory Planning: Use sales numbers to decide what products to buy and stock.

• Marketing Focus: Promote products that show strong sales potential.

These data points allow proactive business strategies. They replace reactive responses to market changes.

How to Put Popularity Sorting in Place in Magento 2?

1. Use Magento 2 Extensions

Extensions provide the fastest setup path. They work for stores requiring immediate popularity sorting functionality.

I. Select an Extension

Compare features, compatibility, and support quality of extensions.

A. Popular Marketplace Solutions:

• Advanced sorting extensions with metrics and configuration options.

• User-optimized extensions with popularity algorithms and responsive design.

B. Evaluation Criteria:

• Available Sorting Metrics: Sales, views, ratings, and wishlist additions.

• Magento Version Compatibility: Future update commitments.

• Documentation Quality: Developer support responsiveness.

• Performance Impact: Page load times and server resources.

• Customer Reviews: Marketplace ratings for reliability assessment.

II. Install and Setup

Installation methods vary based on technical knowledge and server access preferences.

A. Admin Panel Installation:

• Navigate to System > Web Setup Wizard > Component Manager. This provides guided installation without command-line access.

• Follow the on-screen instructions to complete the setup process.

B. Post-installation Configuration:

• Access extension settings: Stores > Configuration > [Extension Name].

• Configure sorting algorithms, cache settings, and performance tuning settings.

• Test for functionality on a staging environment before deploying to production.

III. Configure Popularity Metrics

Metric configuration determines which customer behaviors influence product ranking algorithms.

Common Popularity Metrics:

• Best Sellers: Sales volume calculations over rolling time periods.

• Most Viewed: Page analytics, tracking customer interest levels.

• Top Rated: Review score aggregation and rating count weighting.

• Recently Trending: Time-weighted popularity, favoring recent activity.

Update category display settings by navigating to Catalog > Categories > Display Settings. Establish popularity as the default sorting option for a better customer experience.

2. Focus on Custom Development

Custom development gives complete flexibility. It works for stores needing unique sorting algorithms or complex business logic integration.

I. Alter Product Collection

To change product collections, intercept Magento's core sorting mechanisms. Use plugin architecture for this process.

Target the Magento\Catalog\Model\ResourceModel\Product\Collection class. This is for sorting logic injection:

public function beforeAddAttributeToSort($subject, $attribute, $dir = 'ASC')
{
    if ($attribute == 'popularity_score') {
        // Apply custom popularity sorting logic
        $subject->getSelect()->order('popularity_score DESC');
        return [$attribute, $dir];
    }
    return [$attribute, $dir];
}

This plugin applies custom popularity algorithms. It maintains compatibility with existing Magento functionality.

II. Create a Popularity Attribute

Popularity attributes store calculated scores for each product. This allows efficient database-level sorting operations.

A. Attribute Creation Process:

Navigate to Stores > Attributes > Product for new attribute configuration.

B. Required Attribute Settings:

• Attribute Code: popularity_score for internal system identification.

• Catalog Input Type: Integer for numerical score storage.

• Default Value: 0 for new products without historical data.

• Used for Sorting: Yes, to allow category and search page sorting.

• Scope: Store View for multi-store popularity differentiation.

This attribute allows fast query execution. It enables consistent performance across large product catalogs.

III. Put Sorting Logic in Place

The sorting logic setup needs event observers. They track the collected data and apply popularity calculations..

public function execute(\Magento\Framework\Event\Observer $observer)
{
    $collection = $observer->getCollection();
    $request = $this->request->getParam('product_list_order');
    
    if ($request === 'popularity') {
        $collection->addAttributeToSort('popularity_score', 'DESC');
        $collection->addAttributeToFilter('popularity_score', ['gt' => 0]);
    }
}

This observer activates when customers select popularity options. Such selections occur from category page sorting dropdowns.

3. Combine Different Metrics

Multi-metric popularity scoring provides complete product ranking. It uses diverse customer behavior indicators.

I. Define Popularity Metrics

Metric selection depends on business objectives. It also depends on available data sources within the Magento environment.

A. Core Data Sources:

• Sales Data: Extract from sales_order_item table for sale volume analysis.

• Page Analytics: Integrate Google Analytics API or Magento reporting for view tracking.

• Review Metrics: Query review and rating tables for customer satisfaction indicators.

• Inventory Turnover: Calculate stock movement rates for demand assessment.

B. Recommended Metric Weighting Strategies:

• E-commerce Focused: Sales, Views, Reviews.

• Content Discovery: Views, Reviews, Sales.

• Quality Emphasis: Reviews, Sales, Views.

II. Calculate a Composite Score

Composite scoring algorithms combine several metrics into unified popularity rankings. They use weighted mathematical formulas.

class PopularityCalculator
{
    public function calculateScore($product)
    {
        $salesScore = $this->getSalesCount($product) * 0.5;
        $viewScore = $this->getViewCount($product) * 0.3;
        $reviewScore = $this->getReviewScore($product) * 0.2;
        
        $totalScore = $salesScore + $viewScore + $reviewScore;
        return min(100, $totalScore); // Normalize to 0-100 scale
    }
}

Normalization Techniques:

• Linear Scaling: Convert raw scores to consistent comparison ranges.

• Logarithmic Scaling: Cut the impact of extreme outliers in high-volume products.

• Percentile Ranking: Position products relative to the catalog performance distribution.

III. Update the Scores

Automated score updates keep popularity rankings current with customer behavior. They use scheduled background processing..

    
        
            0 2 * * *
        
    

This cron job updates scores when fewer customers browse your store. Thus, your site does not slow down.

4. Put Good Practices in Place

Thoughtful setups maintain system performance and user experience quality.

I. Focus on Smart Placement

Popularity sorting works at high-impact customer touchpoints. Apply it throughout the shopping journey.

A. Primary Setup Locations:

• Category Pages: Default sorting for immediate customer benefit.

• Search Results: Relevance boost through popularity weighting.

• Homepage Features: Showcase trending products for exposure.

• Related Products: Cross-selling through popularity integration.

B. Performance Considerations:

• Cache Popularity Scores: Cut database query overhead.

• Lazy Loading: For large category collections.

• Track Page Load: To check the impact and tune query performance.

II. Handle Edge Cases

Edge case management keeps a consistent user experience. It works across diverse scenarios and data conditions.

A. New Product Handling:

• Default Scores: Based on category averages.

• Promotional Boosting: For the featured newest arrivals.

• Gradual Increase: Scores as activity data accumulates.

B. Data Quality Management:

• Filter Bot Traffic: From analytics data to prevent score manipulation.

• Handle Identical Scores: Through secondary sorting criteria.

• Fallback Mechanisms: For missing or corrupted data.

III. Keep Data Fresh

Data freshness protocols maintain accuracy. They balance system performance and real-time responsiveness requirements.

A. Recommended Update Frequency Guidelines:

Store Type	Update Frequency
High-traffic Stores	Every hour during peak periods Every day during off-peak periods
Medium-traffic Stores	Every day updates Deep analysis every week
Low-traffic Stores	Every day updates Full recalculation every month

B. Quality Assurance Steps:

• Check Data Validation: Before score updates.

• Track Unusual Patterns: Indicating system anomalies.

• Maintain Backup Scoring: For system reliability.

5. Test and Tune

Testing verifies the setup results. It identifies tuning opportunities for sustained performance gains.

I. Verify the Setup

Test across several environments and user scenarios.

A. Functional Testing:

• Product Order: Confirm products with higher scores appear first in category listings.

• Cache Validation: Check all integration and invalidation mechanisms.

B. Technical Validation:

• Database Performance: Track query performance and tuning opportunities.

• Error Logs: Check for setup-related issues.

• Edge Cases: Verify proper handling of error conditions.

II. Measure Performance Impact

Performance measurement quantifies business value. It identifies areas requiring more tuning efforts.

A. Key Performance Indicators:

Metric	What It Measures
Conversion Rate	Sale completion percentage changes
Average Order Value	Revenue per transaction changes
Time on Site	Customer activity duration increases
Bounce Rate	Immediate exit percentage changes
Product Discovery	Click-through rates on sorted listings

B. Analytics setup:

Use Google Analytics 4 for e-commerce or Magento's native reporting. Track metric changes over recommended 4-6 week periods for statistical significance.

III. Conduct A/B Testing

A/B testing tunes sorting algorithms. It identifies the most effective popularity metrics for specific customer segments.

A. Testing Methodologies:

• Metric Comparison: Sales-based versus view-based popularity algorithms.

• Weighting Tuning: Different percentage allocations in composite scoring.

• Timeline Analysis: Recent activity emphasis versus historical data inclusion.

• Segment Testing: Different algorithms for customer groups or product categories.

B. Recommended Statistical Requirements:

• Testing Period: At least every 2 weeks for reliable data collection.

• Traffic Split: Even division between control and test groups.

• Monitoring: Both primary metrics (conversion) and secondary indicators (activity).

FAQs

1. Does popularity sorting impact database performance and page load speed?

Popularity sorting adds the least database overhead with the right setup. Use cached popularity scores and tuned queries to maintain fast page loads. Regular indexing prevents performance degradation.

2. Can I use popularity sorting on mobile devices without affecting performance?

Yes, popularity sorting works well on mobile devices. Modern extensions support responsive design and PWA compatibility in Magento 2. Cache tuning keeps consistent performance across all devices.

3. Which Magento 2 versions support advanced popularity sorting extensions?

Most popularity-sorting extensions support Magento 2.0.x through 2.4.8. This includes patches as well. Check extension compatibility before installation. The latest versions offer better features and improved performance.

4. How do I prevent fake reviews from affecting popularity calculations?

Put review validation systems in place and filter suspicious activity. Use time-weighted scoring to cut the impact of review manipulation. Check for unusual patterns and exclude bot traffic from calculations.

5. Can popularity sorting work with Elasticsearch and advanced search functionality?

Yes, modern sorting extensions support Elasticsearch integration in Magento 2. This combination increases search performance and allows complex filtering with popularity ranking. Configure both systems for results.

6. What happens to popularity scores during product imports or bulk updates?

Popularity scores remain stable during product imports. Schedule score recalculation after bulk operations complete. Use background processing to prevent frontend disruption during large data updates.

7. How do I test popularity sorting results without affecting customer experience?

Use A/B testing tools to split traffic between different sorting algorithms. Track conversion rates and activity metrics for each variation. Put gradual rollouts in place to cut risk.

Summary

Magento 2 product sorting options promote high-performing products through popularity-based algorithms. Proper setups demand choosing appropriate metrics. You also need to maintain data freshness and conduct continuous tuning:

• Extensions deliver popularity sorting with almost-zero technical requirements.

• Custom development offers algorithmic flexibility and integration with existing systems.

• Composite scoring combines many data sources for complete ranking accuracy.

• Smart setup focuses on high-impact pages where customers often buy products.

• Regular testing and tuning help sustain performance gains and value generation.

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