> ## Documentation Index
> Fetch the complete documentation index at: https://docs.trendteller.com.br/llms.txt
> Use this file to discover all available pages before exploring further.

# Multi-Brand Analytics

> Analyzing and comparing data across multiple brands

## Overview

Trendteller's multi-brand analytics capabilities allow you to consolidate data from 11 brands across 9 e-commerce platforms, enabling powerful cross-brand insights and comparisons.

## Brand Selection

Select one or more brands to analyze:

<Steps>
  <Step title="Access Brand Selector">
    Click the brand selector dropdown in the top navigation bar.
  </Step>

  <Step title="Choose Brands">
    * Select individual brands
    * Use "Select All" for portfolio view
    * Create brand groups for common comparisons
  </Step>

  <Step title="Apply Selection">
    Dashboard automatically updates with combined or comparative data.
  </Step>
</Steps>

## Consolidated View

### Portfolio-Wide Metrics

When multiple brands are selected, view aggregated metrics:

* **Combined Revenue**: Total revenue across all selected brands
* **Aggregate Orders**: Total order count
* **Weighted AOV**: Composite average order value
* **Unified Customer Base**: Deduplicated customer count

<Info>
  Customers who purchase from multiple brands are deduplicated to provide accurate unique customer counts.
</Info>

## Comparative Analysis

### Side-by-Side Comparison

Compare performance metrics across brands:

<Tabs>
  <Tab title="Sales Performance">
    | Brand   | Revenue | Orders | AOV   | Growth |
    | ------- | ------- | ------ | ----- | ------ |
    | Brand A | \$60K   | 500    | \$120 | +15%   |
    | Brand B | \$50K   | 400    | \$125 | +8%    |
    | Brand C | \$40K   | 350    | \$114 | +12%   |
  </Tab>

  <Tab title="Product Performance">
    Compare top products across brands:

    * Best sellers by brand
    * Category performance
    * Margin comparison
    * Stock turnover rates
  </Tab>

  <Tab title="Customer Metrics">
    * Customer acquisition cost
    * Lifetime value by brand
    * Retention rates
    * Cross-brand purchasing patterns
  </Tab>
</Tabs>

### Benchmarking

Benchmark individual brand performance against portfolio averages:

```
Brand A vs Portfolio Average:
✓ Revenue: +25% above average
✓ AOV: +12% above average
✗ Order Volume: -5% below average
✗ Margin: -3% below average
```

## Cross-Brand Insights

### Customer Overlap

Identify customers who purchase from multiple brands:

<CardGroup cols={2}>
  <Card title="Multi-Brand Customers" icon="users">
    **15% of customers** purchase from 2+ brands

    * Higher lifetime value (2.3x average)
    * Better retention (85% vs 60%)
    * Lower acquisition cost (amortized)
  </Card>

  <Card title="Brand Affinity" icon="heart">
    Common brand combinations:

    * Brand A + Brand B: 45% overlap
    * Brand A + Brand C: 32% overlap
    * Brand B + Brand C: 28% overlap
  </Card>
</CardGroup>

<Tip>
  Target multi-brand customers with cross-promotional campaigns to increase wallet share.
</Tip>

### Inventory Optimization

Cross-brand inventory insights:

* **Shared Products**: Products sold by multiple brands
* **Inventory Transfer Opportunities**: Move stock between brands
* **Consolidated Purchasing**: Bulk ordering opportunities
* **Seasonal Patterns**: Identify complementary seasonal cycles

## Unified Reporting

### Executive Dashboard

Portfolio-level executive view:

* Total portfolio revenue and growth
* Brand contribution percentages
* Key performance drivers
* Strategic recommendations

### Brand-Specific Deep Dives

Drill down into individual brand performance while maintaining portfolio context:

1. Click on any brand in comparative view
2. View detailed brand-specific metrics
3. Compare against other brands
4. Return to portfolio view

## Data Segmentation

### By Platform

Analyze performance by e-commerce platform:

<AccordionGroup>
  <Accordion title="Bling Integrations (3 brands)">
    * Combined Bling platform revenue
    * Platform-specific trends
    * Integration health
  </Accordion>

  <Accordion title="VNDA Integrations (2 brands)">
    * VNDA fashion platform performance
    * Category-specific insights
  </Accordion>

  <Accordion title="Other Platforms (6 brands)">
    * Individual platform analysis
    * Integration comparison
  </Accordion>
</AccordionGroup>

### By Category

Cross-brand category performance:

* Apparel across all fashion brands
* Electronics category comparison
* Home goods performance
* Seasonal category trends

## Forecasting

### Portfolio Forecasting

Generate forecasts at the portfolio level:

* Consolidated sales forecast
* Brand-specific predictions
* Category-level forecasts
* Inventory requirements

### Cross-Brand Trends

AI identifies trends affecting multiple brands:

* Market-wide shifts
* Shared customer behavior changes
* Seasonal pattern similarities
* Competitive landscape changes

## Next Steps

<CardGroup cols={2}>
  <Card title="AI Insights" icon="brain" href="/guides/ai-insights">
    Learn about AI-generated cross-brand insights
  </Card>

  <Card title="Data Exports" icon="download" href="/guides/data-exports">
    Export multi-brand data for analysis
  </Card>

  <Card title="Dashboard Guide" icon="chart-line" href="/guides/dashboard">
    Master the dashboard interface
  </Card>

  <Card title="API Reference" icon="code" href="/api-reference/introduction">
    Access multi-brand data programmatically
  </Card>
</CardGroup>