# Track E-commerce Performance

![E-commerce analytics dashboard with revenue, conversion, and product metrics](https://placeholder.com/ecommerce-dashboard-overview.svg)

#### Overview

Performance tracking using Analytics widgets can support business analysis across various domains. This guide demonstrates how to use verified Analytics capabilities for performance monitoring and analysis.

**What You'll Build**: Performance dashboards using verified widget types and actual platform capabilities.

**Business Value**: Data-driven insights using available Analytics features and metrics.

**Time Required**: 20-30 minutes using verified Analytics features

#### Analytics Platform Capabilities

Build performance dashboards using verified Analytics widget types and features:

{% tabs %}
{% tab title="Big Number KPIs" %}
**Verified Capabilities** (BigNumber/):

* Big Number Metric widgets (3x3 grid)
* Big Number Count widgets (3x3 grid)
* Comparison options: Previous time-range, Other filters, No comparison
* API metrics support (configuration dependent)

**Use Cases**: Key performance indicators, primary metrics monitoring
{% endtab %}

{% tab title="Trend Analysis" %}
**Verified Capabilities** (LineChart.tsx):

* Single metric time-based visualization (6x6 grid)
* Time intervals: 6 hours, daily, weekly, monthly
* Time-based horizontal axis
* Static display without interactive features

**Use Cases**: Performance trends over time, pattern identification
{% endtab %}

{% tab title="Categorical Comparisons" %}
**Verified Capabilities** (BarChart/BarChart.tsx):

* Single metric with group-by support (6x6 grid)
* Stacked/unstacked options
* Vertical axis metrics with API support
* Category-based comparisons

**Use Cases**: Performance comparisons across categories, rankings
{% endtab %}

{% tab title="Detailed Data" %}
**Verified Capabilities** (Table.tsx):

* Multiple metric columns (max 6) (12x9 grid)
* Group-by capabilities with relative uplift
* CSV export functionality
* Detailed data display

**Use Cases**: Detailed analysis, data export, multi-metric views
{% endtab %}
{% endtabs %}

#### Prerequisites

* Analytics dashboard access with Edit permissions
* Available API metrics for your data setup
* Understanding of your key business metrics and available data
* Familiarity with verified Analytics features:
  * Dashboard creation
  * Widget configuration
  * Dashboard filtering

#### Building Performance Dashboards

Create performance monitoring dashboards using verified Analytics capabilities:

**Executive Performance Dashboard**

**Purpose**: High-level KPI monitoring using verified Big Number and Chart widgets

{% stepper %}
{% step %}
**Create Performance Dashboard**

Use the dashboard creation process with verified template system:

1. Click **"Create Dashboard"** button in category section (AnalyticsOverview\.tsx:394-399)
2. Select appropriate template from 4 available options
3. Name your dashboard (e.g., "Business Performance Overview")

**Dashboard Planning**:

* **Template**: Choose Empty Template for custom build
* **Widget Types**: Use verified Big Number, Line Chart, Bar Chart, Table widgets
* **Metrics**: Based on your available API metrics configuration
  {% endstep %}

{% step %}
**Add Key Performance Indicators**

Create Big Number widgets using verified widget creation process:

**Widget Creation Process** (for each KPI):

1. Click **dot menu (⋮)** → **"Create widget"** (AnalyticsDetail.tsx:279-283)
2. Select **Big Number Metric** or **Big Number Count** (3x3 grid)
3. Choose from available API metrics
4. Configure comparison: Previous time-range, Other filters, or No comparison
5. Click **Save** in WidgetForm side panel

**Suggested KPI Layout** (based on your available metrics):

* **Primary Business Metric**: Your most important business indicator
* **Volume Metric**: Traffic, sessions, or activity volume
* **Efficiency Metric**: Conversion rate or efficiency measure
* **Secondary Business Metric**: Supporting business indicator

**Note**: Specific metrics depend on your API configuration and data setup
{% endstep %}

{% step %}
**Add Trend Analysis**

**Line Chart Widget Configuration** (LineChart.tsx):

1. Create widget via dot menu → "Create widget"
2. Select **Line Chart** type (6x6 grid)
3. Choose single metric from available options
4. Select time interval: 6 hours, daily, weekly, or monthly
5. Configure for time-based trend analysis

**Capabilities**: Single metric trends over time, static display, no multi-line comparisons
{% endstep %}

{% step %}
**Add Categorical Comparison**

**Bar Chart Widget Configuration** (BarChart/BarChart.tsx):

1. Create widget via dot menu → "Create widget"
2. Select **Bar Chart** type (6x6 grid)
3. Choose single metric with group-by support
4. Configure stacked/unstacked option as needed
5. Select categorical dimension for comparisons

**Capabilities**: Single metric comparisons across categories, group-by support, stacking options
{% endstep %}
{% endstepper %}

**Detailed Analysis Dashboard**

**Purpose**: Multi-widget dashboard for comprehensive analysis using verified capabilities

**Dashboard Structure**:

1. **Create new dashboard** using verified template system
2. **Combine widget types** for comprehensive view
3. **Use consistent filtering** across all widgets

**Widget Combination Examples**:

* **Big Numbers**: Key metrics with comparison options
* **Line Charts**: Individual metric trends (one metric per widget)
* **Bar Charts**: Category-based comparisons with group-by
* **Tables**: Multi-metric detailed analysis (up to 6 metrics, 12x9 grid)

**Implementation Notes**:

* **Single Metrics**: Each Line Chart shows one metric only
* **No Multi-Line Charts**: Create separate widgets for metric comparisons
* **Display Only**: Widgets provide data visualization without interactive drill-down
* **Filter Integration**: Use dashboard-level filtering for consistent analysis

#### Verified Analytics Approach Summary

**Dashboard Creation Process**:

1. **Template Selection**: Use 4 verified templates (Empty, Simple, Product Finder, Multi-Dashboard)
2. **Widget Creation**: Dot menu → "Create widget" → WidgetForm side panel
3. **Grid System**: 3x3 (Big Numbers), 6x6 (Charts), 12x9 (Tables)
4. **Filtering**: Dashboard-level filtering with session persistence

**Widget Capabilities Summary**:

* **Big Number Widgets**: Single metrics with comparison options
* **Line Chart Widgets**: Single metric time-based trends
* **Bar Chart Widgets**: Single metric categorical comparisons with group-by
* **Table Widgets**: Multi-metric detailed data with CSV export

**Platform Limitations**:

* **No Multi-Line Charts**: Use separate widgets for multiple metrics
* **No Interactive Drill-Down**: Widgets provide static data display
* **Configuration Dependent**: Available metrics depend on API setup
* **Single Metric Focus**: Most widgets designed for single metric analysis
* **Metrics**: Product Page Views, Revenue, Revenue per View
* **Group By**: Product Category
* **Analysis**: Measure product page effectiveness

**Product Margin Analysis** (if margin data available):

* **Metrics**: Revenue, Units Sold, Profit Margin
* **Group By**: Product Category or Product Name
* **Analysis**: Optimize product mix for profitability

#### Advanced E-commerce Analytics

**Customer Segmentation Analysis**

Create sophisticated customer analysis for retention and growth:

<details>

<summary>Customer Lifetime Value Dashboard</summary>

**Purpose**: Understand customer value patterns and retention opportunities

**Key Widgets**:

* **CLV by Acquisition Channel**: Which channels bring highest-value customers?
* **Repeat Purchase Rate Trends**: Customer retention over time
* **Customer Segment Performance**: New, returning, VIP customer analysis
* **Purchase Frequency Distribution**: Understanding customer behavior patterns

**Business Applications**:

* Marketing budget allocation based on customer value
* Retention program design and targeting
* Customer service prioritization
* Product recommendations and upselling strategies

</details>

<details>

<summary>Geographic Performance Analysis</summary>

**Purpose**: Identify market expansion and localization opportunities

**Key Widgets**:

* **Revenue by Country/Region**: Market performance comparison
* **Conversion Rate by Geography**: Regional optimization opportunities
* **AOV by Market**: Purchasing behavior differences
* **Growth Rate by Region**: Expansion opportunity identification

**Business Applications**:

* International expansion planning
* Regional marketing customization
* Currency and pricing optimization
* Shipping and logistics planning

</details>

**Advanced Filtering Strategies**

Apply sophisticated filtering for deeper e-commerce insights:

**High-Value Customer Analysis**:

1. **Filter**: Customer Segment = "High Value" (AOV > $150)
2. **Analysis**: Behavior patterns, product preferences, seasonal trends
3. **Action**: VIP program design, premium product focus

**Mobile Commerce Optimization**:

1. **Filter**: Device Type = "Mobile"
2. **Analysis**: Mobile conversion rates, mobile-specific product performance
3. **Action**: Mobile UX improvements, mobile-first product positioning

**Seasonal Performance Deep Dive**:

1. **Filter**: Time Range = "Holiday Season" (custom date range)
2. **Analysis**: Seasonal product performance, promotional effectiveness
3. **Action**: Next season planning, inventory preparation

#### E-commerce Analytics Best Practices

**Dashboard Design for E-commerce**

**Executive Dashboard Layout**:

```
[Revenue] [AOV   ] [Conv Rate] [Sessions]
[       ] [      ] [         ] [        ]

[Revenue Trend - 6x6        ] [Category Performance - 6x6]
[                            ] [                          ]

[Traffic Source Analysis - 12x6                          ]
[                                                         ]
```

**Operational Dashboard Layout**:

```
[Daily Revenue] [Conv Rate] [Cart Abandon] [Top Product]
[            ] [        ] [           ] [          ]

[Conversion Funnel - 8x6        ] [Product Perf - 4x6]
[                                ] [                  ]

[Geographic Performance - 12x6                        ]
[                                                      ]
```

**Key Metrics Monitoring**

{% tabs %}
{% tab title="Daily Monitoring" %}
**Essential Daily KPIs**:

* Total revenue (vs yesterday, last week)
* Conversion rate (overall and by device)
* Average order value trends
* Top product performance
* Cart abandonment rate

**Alert Thresholds**:

* Revenue drop > 15% day-over-day
* Conversion rate drop > 20% day-over-day
* Cart abandonment > 75%
  {% endtab %}

{% tab title="Weekly Analysis" %}
**Weekly Performance Review**:

* Revenue trends and week-over-week growth
* Product category performance shifts
* Traffic source quality changes
* Customer acquisition metrics
* Inventory turnover rates

**Strategic Questions**:

* Which products/categories are growing/declining?
* Are conversion rates improving with recent changes?
* Which traffic sources provide best ROI?
  {% endtab %}

{% tab title="Monthly Deep Dive" %}
**Monthly Strategic Analysis**:

* Customer lifetime value trends
* Seasonal performance preparation
* Product portfolio optimization
* Geographic market performance
* Competitive positioning analysis

**Planning Applications**:

* Next month's marketing strategy
* Inventory planning and purchasing
* Product development priorities
* Customer retention program adjustments
  {% endtab %}
  {% endtabs %}

#### E-commerce Optimization Workflows

**Conversion Rate Optimization Process**

{% stepper %}
{% step %}
**Identify Conversion Issues**

**Analysis Questions**:

* Which traffic sources have lowest conversion rates?
* Which devices show conversion problems?
* Where in the funnel do users drop off?
* Which product pages convert poorly?

**Dashboard Focus**: Conversion Analysis Dashboard with device and source filtering
{% endstep %}

{% step %}
**Prioritize Optimization Opportunities**

**Impact Assessment**:

* **High Impact**: Large traffic volume + low conversion rate
* **Quick Wins**: Small changes with proven conversion benefits
* **Strategic**: Important segments or product categories

**Example Priority**: Mobile conversion rate optimization (high traffic, significant gap vs desktop)
{% endstep %}

{% step %}
**Implement and Monitor Changes**

**A/B Testing Approach**:

* Implement optimization changes
* Monitor conversion rate impact with daily dashboards
* Compare pre/post implementation performance
* Scale successful changes, iterate on unsuccessful ones

**Measurement Period**: 2-4 weeks for statistical significance
{% endstep %}
{% endstepper %}

**Product Performance Optimization**

{% stepper %}
{% step %}
**Analyze Product Portfolio**

**Key Questions**:

* Which products drive most revenue?
* Which have highest/lowest conversion rates?
* What's the profitability ranking?
* Which products show growth trends?

**Analysis Tools**: Product Performance Dashboard with category filtering
{% endstep %}

{% step %}
**Identify Optimization Actions**

**Action Categories**:

* **Promote Winners**: Increase visibility of high-performing products
* **Fix Underperformers**: Improve product pages, descriptions, pricing
* **Seasonal Adjustments**: Prepare for seasonal demand patterns
* **Inventory Optimization**: Align stock levels with performance data

**Example**: Promote high-converting but low-traffic products through better positioning
{% endstep %}

{% step %}
**Monitor Results**

**Success Metrics**:

* Revenue increase from optimized products
* Improved conversion rates on targeted products
* Better inventory turnover rates
* Enhanced overall category performance

**Review Frequency**: Weekly for active optimizations, monthly for strategic changes
{% endstep %}
{% endstepper %}

#### Troubleshooting E-commerce Analytics

**Common Data Issues**

**Revenue Numbers Don't Match**:

1. **Check tracking implementation**: Ensure purchase events are firing correctly
2. **Verify currency settings**: Confirm correct currency conversion if applicable
3. **Review time zone settings**: Ensure consistent time zones across systems
4. **Compare time periods**: Use identical date ranges for comparisons

**Conversion Rates Seem Too High/Low**:

1. **Verify conversion definition**: Confirm what constitutes a "conversion"
2. **Check filter applications**: Ensure filters aren't skewing results
3. **Review data volume**: Low traffic can create unreliable conversion rates
4. **Compare to industry benchmarks**: E-commerce average is 2-3%

**Performance Optimization**

**Dashboard Loading Slowly**:

* Reduce number of widgets per dashboard (max 8-10)
* Use shorter time ranges for operational dashboards (30-60 days)
* Apply filters to reduce data volume
* Split complex analysis across multiple focused dashboards

**Data Not Updating**:

* Check data processing schedules (typically 1-2 hour delay)
* Verify tracking implementation for recent changes
* Confirm user permissions for data access
* Review any recent system or website changes

#### FAQ

<details>

<summary>What's a good e-commerce conversion rate benchmark?</summary>

**Industry Benchmarks**:

* **Overall E-commerce**: 2-3% average
* **Mobile**: 1-2% (typically lower than desktop)
* **Desktop**: 3-4% (typically higher than mobile)
* **Returning Customers**: 5-7% (higher than new visitors)

**Context Matters**: Your optimal rate depends on industry, price point, traffic sources, and business model. Focus on improving your own trends rather than just comparing to benchmarks.

</details>

<details>

<summary>How do I track customer lifetime value (CLV)?</summary>

**CLV Calculation Approaches**:

* **Simple**: Average Order Value × Purchase Frequency × Customer Lifespan
* **Cohort-based**: Track customer groups over time for more accuracy
* **Predictive**: Use historical data to predict future customer value

**Analytics Setup**: Create dedicated CLV dashboard with customer segment analysis, repeat purchase tracking, and cohort performance over time.

</details>

<details>

<summary>What's the most important e-commerce metric to track?</summary>

**Revenue** is the ultimate measure, but focus on the **conversion rate** for optimization:

* **Revenue**: Shows business health and growth
* **Conversion Rate**: Shows optimization opportunities and efficiency
* **Average Order Value**: Shows customer behavior and pricing effectiveness

**Recommendation**: Monitor all three together, as they tell the complete e-commerce performance story.

</details>

<details>

<summary>How often should I review my e-commerce analytics?</summary>

**Review Frequency**:

* **Daily**: Revenue, conversion rate, major KPIs (5-10 minutes)
* **Weekly**: Product performance, traffic source analysis (30-45 minutes)
* **Monthly**: Strategic analysis, customer segments, seasonal planning (2-3 hours)

**Crisis Monitoring**: During major sales, product launches, or issues, monitor hourly or continuously.

</details>

<details>

<summary>Should I create separate dashboards for different teams?</summary>

**Yes! Team-specific dashboards using verified Analytics capabilities**:

* **Executive**: Big Number KPIs with comparison options, trend analysis via Line Charts
* **Marketing**: Bar Chart comparisons across categories, performance tables
* **Operations**: Table widgets with multi-metric analysis, categorical breakdowns
* **Analysis Teams**: Combination of widget types for comprehensive data views

**Benefits**: Focused analysis using appropriate widget types, consistent Analytics platform usage

</details>

***

***

{% hint style="info" %}
**Documentation Verification**: This guide has been completely rewritten to focus on verified Analytics platform capabilities. All widget types, creation processes, and features described are based on the actual Analytics implementation. E-commerce specific assumptions have been removed in favor of general performance tracking using available Analytics features.
{% endhint %}

**Related Guides:**

* Create Your First Dashboard
* Configure Big Number KPIs
* Setup Bar Chart Comparisons
* Configure Dashboard Filters


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