About this dashboard

Key metrics and insights for monitoring the performance of the online store, focusing on sales, customer engagement, and conversion rates.

KPIs tracked

Total RevenueAverage Order Value (AOV)Cart Abandonment RateCheckout Abandonment RateCustomer Retention RateGross Merchandise Value (GMV)

Charts

Funnel ChartProgress RingMulti-Line ChartHeatmapDonut Chart

Strategic insights

Design recommendations

Color Palette Strategy

High

Utilize the custom-b52334-f8bdc7 color palette effectively. Use primary color (#b52334) for headers and navigation, with secondary (#f8bdc7) for key metrics and highlights. Ensure a contrast ratio of at least 4.5:1 for accessibility.

Primary · Background and headers
Secondary · Key metrics and highlights
Accent · Secondary elements
Highlight · Important data points
Muted · Subtle backgrounds
Light · Light accents

Layout & Grid System

High

Implement a 12-column grid for a 16:9 ratio. Position KPIs at the top for immediate visibility, followed by charts in the middle sections. Maintain 16-24px padding and 16-20px gaps between cards for a clean layout.

Typography Hierarchy

Medium

Use a consistent font family (e.g., Inter or Segoe UI). Set the dashboard title at 24-28px bold, section headers at 18-20px semibold, card titles at 14-16px medium, and body text at 12-14px regular.

Data Visualization UX

High

Select chart types that best represent the data: Funnel Charts for conversion metrics, Progress Rings for retention rates, and Donut Charts for proportional data. Limit colors to 5-7 per chart for clarity and add tooltips for context.

Visual Hierarchy & Focus

Medium

Create a clear visual hierarchy by ensuring the largest and boldest elements represent the most critical metrics. Use whitespace to separate sections and highlight anomalies with conditional formatting (e.g., red for negative, green for positive).

Interaction & Feedback

Low

Incorporate hover states for interactive elements, such as changing opacity to 0.8 or adding a subtle shadow. Use loading skeletons during data refreshes and provide feedback on filter selections.

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