How to Filter Orders by Store Credit Usage in PayHelm

Overview

PayHelm allows you to filter your orders based on store credit usage, making it easy to analyze transactions where customers used store credit as part of their payment method. This feature helps you track store credit redemption patterns, customer loyalty program effectiveness, and financial reconciliation.

Understanding Store Credit Filtering

What Store Credit Filtering Shows

The Store Credit Range filter helps you identify:
• Orders with any store credit usage: Find all transactions where customers redeemed store credit
• Store credit amount ranges: Filter by specific store credit amounts used
• Payment method analysis: Understand how often customers use store credit vs other payment methods
• Customer behavior patterns: Track store credit redemption trends over time

Use Cases for Store Credit Filtering

• Loyalty program analysis: Monitor how frequently customers redeem store credit
• Financial reconciliation: Track store credit liability and usage
• Customer retention insights: Analyze purchasing patterns of store credit users
• Promotional campaign tracking: Measure effectiveness of store credit promotions

How to Filter Orders by Store Credit Usage

Step 1: Access the Dashboard Filters

1. Navigate to your PayHelm Dashboard
2. Locate the filter section at the top of your dashboard
3. Look for the Range Filters area in the left sidebar under "Search Filters"

Step 2: Set Up Store Credit Range Filter

1. Find "Range Filters" in the left sidebar search filters panel
2. Locate "Total Store Credit Range" in the list of available range filters
3. Click on the Total Store Credit Range option to activate it

Step 3: Configure Your Store Credit Filter

1. Set the minimum value: Enter "0.01" to capture any orders with store credit usage
2. Set the maximum value: Enter a high number like "1000000" to include all amounts
3. Apply the filter: Click the "Apply" button to activate your filter

Step 4: Review Filtered Results

Your dashboard will now display:
• Orders that used store credit: Only transactions with store credit payments
• Total Store Credit metric: Shows the total amount of store credit used in filtered orders
• Updated analytics: All dashboard metrics reflect store credit order data only

Advanced Filtering Options

Specific Store Credit Amount Ranges

You can create more targeted filters by setting specific ranges:
• Low store credit usage: Set range from 0.01 to 25.00
• Medium store credit usage: Set range from 25.01 to 100.00
• High store credit usage: Set range from 100.01 to 1000000

Combining with Other Filters

Enhance your analysis by combining store credit filters with:
• Date ranges: Analyze store credit usage during specific periods
• Customer segments: Focus on particular customer groups
• Product categories: See which products customers buy with store credit
• Platform filters: Compare store credit usage across different sales channels

Understanding Your Store Credit Data

Key Metrics to Monitor

When filtering by store credit usage, pay attention to:
• Total Store Credit: The aggregate amount of store credit redeemed
• Order Count: Number of orders that included store credit payments
• Average Order Value: Typical order size when store credit is used
• Customer Distribution: How many unique customers used store credit

Analysis Insights

Store credit filtering can reveal:
• Customer loyalty patterns: Frequent store credit users may be your most loyal customers
• Seasonal trends: Store credit usage might spike during certain periods
• Product preferences: Items commonly purchased with store credit
• Mixed payment behavior: How customers combine store credit with other payment methods

Troubleshooting Store Credit Filtering

No Results Appearing

If your filter shows no results:
• Check your date range: Ensure the selected period includes orders with store credit
• Verify store credit integration: Confirm your store credit system is properly connected
• Review minimum value: Make sure you set the minimum to 0.01 or lower
• Clear other filters: Remove conflicting filters that might exclude store credit orders

Unexpected Results

If results don't match expectations:
• Verify store credit tracking: Ensure your platform properly reports store credit usage
• Check data sync: Recent store credit orders may still be processing
• Review filter combination: Other active filters might be affecting results
• Confirm date ranges: Make sure the time period aligns with known store credit activity

Store Credit Not Showing in Filters

If you don't see the Store Credit Range option:
• Refresh your dashboard: Reload the page to ensure all filters are loaded
• Check account permissions: Ensure you have access to advanced filtering features
• Verify data availability: Your account needs store credit transaction data to show this filter

Best Practices for Store Credit Analysis

Regular Monitoring

• Weekly reviews: Track store credit usage patterns during active campaigns
• Monthly analysis: Monitor overall store credit liability and redemption rates
• Quarterly assessments: Evaluate customer loyalty program effectiveness
• Annual planning: Use store credit data for loyalty program strategy

Data-Driven Decisions

Use store credit filtering to:
1. Optimize loyalty programs: Adjust store credit offerings based on usage patterns
2. Improve customer retention: Identify and nurture high store credit users
3. Plan inventory: Stock products popular with store credit customers
4. Forecast cash flow: Understand store credit liability impact on revenue

Combining Analysis Methods

Enhanced insights come from combining store credit data with:
• Customer lifetime value: Track the value of store credit users over time
• Purchase frequency: Monitor how store credit affects buying behavior
• Product performance: Identify which items drive store credit redemption
• Geographic patterns: Understand regional store credit usage differences

Exporting Store Credit Reports

Available Export Options

• CSV format: For detailed spreadsheet analysis
• PDF reports: For sharing with stakeholders
• Automated reports: Schedule regular store credit usage reports
• API integration: Connect store credit data with other business systems

Setting Up Regular Reports

1. Configure your store credit filter with desired parameters
2. Set up automated reporting for regular intervals
3. Choose recipients for automatic report delivery
4. Monitor trends over time to identify patterns

Related Features

Customer Segmentation

Store credit filtering works well with customer segmentation to:
• Identify high-value store credit users
• Track customer loyalty program participation
• Analyze retention rates for different customer groups

Financial Reporting

Combine store credit data with financial reports for:
• Store credit liability tracking
• Revenue impact analysis
• Payment method distribution insights
• Cash flow forecasting

Marketing Analytics

Use store credit insights for:
• Loyalty program optimization
• Targeted campaign development
• Customer retention strategies
• Promotional effectiveness measurement

Store credit filtering provides valuable insights into customer loyalty and payment preferences. By understanding how customers use store credit, you can optimize your loyalty programs, improve customer retention, and make informed business decisions about store credit policies and promotions.