Overview Dashboard
Your payment data holds the story of your business health. The Overview Dashboard in Corgi Intelligence surfaces that story at a glance, so you spend less time digging through charts and more time acting on what matters.
This page is your home base. It shows the metrics that matter most to your business model, plus AI-generated Key Insights that flag trends and revenue opportunities you might otherwise miss. Corgi Intelligence auto-detects whether you run a retail or subscription business during onboarding, then tailors the dashboard to match.
Dashboard Modes: Retail vs. Subscription
Corgi Intelligence selects one of two dashboard modes based on your business model. You do not need to configure this manually.
| Mode | Best For | Key Focus |
|---|---|---|
| Retail | E-commerce, marketplaces, and physical goods | One-time purchases, GMV, and product performance |
| Subscription | SaaS, recurring billing, and usage-based models | Recurring revenue, retention, and churn signals |
If your dashboard mode does not match your business model, reach out to your Corgi Labs contact. They will update your configuration.
Retail Dashboard
If you sell one-time products or services, your Overview Dashboard centers on purchase behavior and product performance. Here are the metrics you will see.
Gross Merchandise Value (GMV). The total value of all transactions processed in the selected period. This is your top-line revenue number.
Number of Transactions. The total count of payment attempts, including both approved and declined transactions.
Refund Rate. The percentage of transactions that were refunded, with a trend comparison against the previous period. A spike here can signal product issues, fulfillment problems, or policy friction.
Number of Unique Customers. The count of distinct customers who made at least one purchase in the period. This helps you gauge reach beyond raw transaction volume.
Repeat Purchase Rate. The percentage of customers who made two or more purchases. This is a direct indicator of loyalty and product-market fit.
Customer Lifetime Value (CLV). The average revenue per customer over their entire relationship with your business. Use this to calibrate acquisition spend and retention priorities.
Average Order Value (AOV). The mean transaction amount per order. Small movements in AOV can drive outsized revenue impact at scale.
Top 10 Products by GMV Contribution. A ranked table showing your best-performing products by revenue. Each row includes purchase count, repeat customers, and the percentage of total revenue that product represents. Use this to spot winners, duds, and portfolio concentration risk.
Subscription Dashboard
If you run a recurring or usage-based billing model, your Overview Dashboard focuses on revenue predictability and customer retention. Here are the metrics you will see.
Monthly Recurring Revenue (MRR). Your predictable monthly revenue from active subscriptions. This is the heartbeat of your subscription business.
Net Revenue Retention (NRR). Measures expansion, contraction, and churn relative to your starting revenue. An NRR above 100% means your existing customers are growing your revenue.
Gross Revenue Retention (GRR). The revenue you retain from existing customers, excluding expansion revenue. This shows how well you hold onto revenue before any upsells.
Logo Churn Rate. The percentage of customers who canceled during the period. Track this alongside revenue churn to understand whether you are losing small customers or large ones.
Dunning Recovery Rate. The percentage of failed subscription payments recovered through retry logic and dunning flows. A low rate here can signal a need to tighten your recovery strategy.
Deferred Revenue Balance. Revenue you have collected but not yet recognized. This matters for accounting accuracy and cash flow forecasting.
Revenue at Risk. Revenue tied to customers showing churn signals or failed payments. Use this to prioritize outreach before cancellation happens.
Key Insights
At the top of your Overview Dashboard, Corgi Intelligence surfaces AI-generated Key Insights. These are not static tips. They are observations drawn from your latest payment data, updated automatically, and designed to surface high-impact changes without manual chart review.
Here are the insight types you may see:
Approval Upside. An estimate of additional revenue you could unlock by improving your approval rate. The insight includes a specific dollar estimate, so you know the size of the opportunity.
Disputes Down / Up. A flag when your dispute rate changes meaningfully compared to the previous period. The insight includes a breakdown by primary and comparison ranges, so you see where the shift is coming from.
Churn Spike. An alert when churned revenue exceeds historical norms. The insight includes recommended actions, such as aligning dunning and card updater efforts to recover at-risk revenue.
Rule Bias. A warning when your fraud rules may be generating too many generic declines. The insight suggests refinements to help you block fraud, not buyers.
Key Insights refresh automatically as new data arrives. Treat them as your starting point for daily prioritization, not a replacement for deeper analysis.
Payments & Fraud Overview
Both dashboard modes include a Payments & Fraud Overview section at the bottom of the page. These four metrics apply to every merchant, regardless of business model. Each includes a trend comparison against the previous period.
Authorization Rate. The percentage of payment attempts approved by the issuing bank. This is the single biggest lever for revenue growth in most businesses.
Dispute Rate. The percentage of transactions that resulted in a customer dispute. Watch this closely, as disputes can trigger network monitoring programs and increase processing costs.
Block Rate. The percentage of transactions blocked by your fraud rules or risk screening. A sudden jump here can mean your rules are too tight, or that you are under attack.
Abandonment Rate. The percentage of checkout sessions abandoned before payment completion. High abandonment can signal UX friction, unexpected fees, or payment method gaps.
For deeper analysis, see Payment Analytics and Dispute & Fraud.
Last updated: 2026-06-16