Unusual Discount Store Insight: Detecting and Managing Discount Anomalies

Unusual Discount Store Insight: Identifying and Managing High Discount Transactions #

 
Offering discounts is a common sales tactic, but applying discounts that are too high, whether intentionally or by mistake, can negatively impact your bottom line, leading to revenue loss, reduced profitability, and potential policy violations. Without a clear way to monitor significant discounts, store owners may find it challenging to maintain pricing integrity and financial health.

 
The Unusual Discount Store Insight in Ficos helps store owners identify orders where the discount percentage exceeds a predefined level. This feature flags these transactions, providing a detailed breakdown including profitability metrics and contextual comparisons, allowing retailers to investigate, take informed actions, and protect their revenue.

 

Understanding the Unusual Discount Store Insight #

 
The Unusual Discount Store Insight highlights orders where the applied discount percentage is strictly greater than a fixed threshold (currently set at 25%) relative to the order’s item total before discount. By flagging these specific high-discount transactions, store owners can investigate the reasons behind them and ensure they align with store policies and profitability goals.

 
Why is Tracking High Discounts Important?

• Prevents revenue leakage from excessive discounts.
• Helps detect potential misuse or errors in applying discounts.
• Ensures promotional activities remain within acceptable profitability parameters.
• Allows monitoring of discounting patterns related to specific staff or customers.

How the Unusual Discount Report Works #

 
Ficos identifies transactions where the discount percentage exceeds a fixed threshold of 25%. Users can view these flagged transactions over various time periods.

 
Key Process:

• Users select a time period (e.g., Last 7 Days, Last 30 Days, up to Last 365 Days).
• The system identifies all orders within that period where the discount percentage `(discount / itemsAmount * 100)` is strictly greater than 25%.
• These flagged orders are presented in a paginated list.
• Clicking on an order reveals detailed information for investigation.
• A bar chart visually represents the discount percentages of up to the top 15 flagged orders for the selected period.

 
Data Included in the Detailed View for Flagged Orders:

• Order Reference: Unique transaction identifier and date.
• Discount Details: The exact discount percentage and amount applied.
• Order Summary: Items amount, final total amount, and any order notes.
• Customer Details: Name and contact information (phone/email).
• Staff Responsible: The employee who processed the transaction and their contact info (email).
• Profitability Analysis: Estimated total cost of goods sold, estimated profit amount, and estimated profit margin for the specific order.
• Contextual Averages (Last 90 Days): Compares the order’s discount to the store’s overall average discount percentage, the specific staff member’s average discount percentage, and the specific customer’s average discount percentage over the last 90 days.
• Discounted Items: A list of products included in the order, showing quantity, selling price, and cost price per item.
• Investigation Points: Automated suggestions highlighting key areas to review for that specific transaction (e.g., discount vs. threshold/averages, profitability level, staff/customer patterns).

Key Insights from the Report #

 
The Unusual Discount Store Insight helps store owners analyze discounting patterns through:

• Detecting High Discounts: Quickly identifies orders exceeding the 25% discount threshold.
• Monitoring Staff and Customer Patterns: Highlights specific transactions by staff/customers and provides their 90-day average discount percentage for context.
• Assessing Profitability Impact: Shows the estimated profit margin for each flagged order, revealing potentially loss-making sales.
• Identifying Policy Deviations: Helps ensure that discounts applied are justified and align with store guidelines, especially when compared against the store’s 90-day average discount.

Practical Steps to Manage Unusual Discounts #

 
To maintain profitability and manage discount application effectively, store owners can:

• Review Flagged Transactions: Regularly check the insight for orders exceeding the 25% threshold.
• Investigate Low/Negative Margins: Pay close attention to flagged orders with low or negative estimated profit margins.
• Discuss with Staff: Use the detailed information (including staff 90-day averages and specific transaction details) to discuss high discount instances with employees and reinforce policies.
• Analyze Patterns: Look for recurring high discounts associated with specific staff, customers, or products.
• Refine Discount Policies: Ensure guidelines are clear about when and how discounts above certain levels can be applied, possibly requiring manager approval.
• Use Contextual Data: Leverage the 90-day average comparisons (store, staff, customer) to understand if a high discount is truly anomalous or part of a pattern.

How to Access the Unusual Discounts Store Insight #

1. Step 1: On the home screen, tap the ‘View Analytics’ link below the ‘Today’ dashboard summary.
2. Step 2: This will take you to the Store Analytics page.
3. Step 3: On the Store Analytics screen, look through the list of available insights and tap on ‘Unusual Discount Store Insight’.

How Unusual Discounts Work #

 
The Unusual Discount Store Insight identifies orders where the discount percentage surpasses a fixed threshold, enabling store owners to review potentially problematic transactions.

 
How It Works:

• Flags orders where the discount percentage `(discount / itemsAmount * 100)` is strictly greater than 25%.
• Allows users to select a time period (e.g., Last 30 Days, Last 90 Days) for analysis.
• Lists all flagged transactions from the selected period, with pagination if needed.
• Provides a detailed view for each flagged order, including:
  • Order reference, date, discount amount, and percentage.
  • Customer and staff member details.
  • Estimated profitability (cost, profit amount, profit margin).
  • Comparison with 90-day average discount percentages (Store, Staff, Customer).
  • List of items in the order.
• Offers an optional bar chart showing discount percentages for up to the top 15 flagged orders.

 
By leveraging this insight, store owners can scrutinize high-discount transactions, understand their impact on profitability, and take corrective actions to prevent revenue loss and ensure policy adherence.

 

Glossary of Terms for Unusual Discount Store Insight #

 
Below are key terms used in the Unusual Discount Store Insight report to help store owners understand the concepts and metrics involved.

• Discount Threshold: The predefined percentage (currently fixed at 25%) above which a discount, calculated as `(discount / itemsAmount * 100)`, is flagged by this insight for review.
• Discount Anomaly: An order flagged by the insight because its discount percentage exceeds the fixed 25% threshold. Further context is provided by comparing it to 90-day averages.
• Items Amount: The total value of items in an order *before* any discounts are applied. Used as the base for calculating the discount percentage.
• Profitability Metrics (Estimated): Calculations based on order revenue (considering discount) and recorded product cost prices:
  • Total Cost: Estimated cost of goods sold for the items in the order.
  • Profit Amount: Estimated profit (Revenue – Total Cost).
  • Profit Margin: Estimated profit expressed as a percentage of revenue.
• Contextual Averages (90-Day): Average discount percentages calculated over the last 90 days for comparison purposes:
  • Store Avg Discount %: The average discount percentage across all qualifying orders in the store.
  • Staff Avg Discount %: The average discount percentage for orders processed by the specific staff member associated with the flagged transaction.
  • Customer Avg Discount %: The average discount percentage for orders associated with the specific customer on the flagged transaction.
• Revenue Leakage: Loss of potential revenue due to excessive or unauthorized discounts, untracked promotions, or improper pricing strategies.
• Profitability Goals: The financial targets a store aims to achieve, ensuring discounts do not negatively impact revenue and net profit.
• Fraudulent Discounting: The misuse of discounts, either by employees or customers, to exploit price reductions for unauthorized benefits.
• Discount Policy Violations: Any discounts applied that do not adhere to the store’s established discounting rules or approval processes.
• Employee Discounting Behavior: The patterns and trends in how employees apply discounts, which help store owners detect potential misuse or unauthorized promotions, informed by individual transaction details and 90-day averages.
• Customer Discount Trends: An analysis of how often and how much discount a particular customer receives, helping identify loyalty-based or potentially exploitative discounting patterns, informed by individual transaction details and 90-day averages.
• High-Risk Transactions: Sales transactions flagged by this insight due to exceeding the 25% discount threshold, which may require further review for profitability impact and policy compliance.
• Store Insights: A feature in Ficos that provides data-driven reports, including unusual discounts, to help store owners make informed decisions about their business operations.
• Order Reference: A unique identifier assigned to each transaction, allowing store owners to track specific orders that have been flagged for review.
• Discount Percentage: The proportion of the items’ total value (before discount) deducted as a discount, expressed as a percentage `(discount / itemsAmount * 100)`.
• Total Discount Amount: The absolute monetary value of the discount applied to a specific transaction.
• Approval Process: A structured workflow where discounts above a certain threshold might require authorization from a manager or store owner before being applied (this insight helps identify transactions that might need such scrutiny based on policy).
• Data-Driven Promotions: Discount strategies based on analyzed sales data (like the insights provided here on profitability and context) to ensure that discounts enhance revenue rather than cause financial losses.

 
This glossary serves as a reference guide for store owners to effectively interpret the Unusual Discount Store Insight report and take appropriate actions based on the findings.

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