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Case study · Mau Brands

How we built Mau Brands' Amazon analytics platform

Mau Brands is an ecommerce analytics and operations platform designed to give Amazon sellers and agencies complete visibility into their business performance. The platform consolidates data from multiple sources including sales, inventory, advertising, and pricing into a single, unified dashboard. We built the SP-API and Ads API pipelines, warehouse and dashboards behind it.

  • Amazon marketplace · Ecommerce analytics
  • Ongoing partnership
  • Amazon Seller Central
  • Amazon SP-API
  • Amazon Ads

Results

What changed, in numbers.

25%

Reduction in time spent on manual reporting and analysis.

15%

Improvement in campaign performance through data-driven decisions.

Inside the build

Screens, flows and designs from the build.

6 images from the Mau Brands project. Select any image to see it larger.

Mau Brands dashboard overview with sales, inventory and advertising panels
Mau Brands dashboardSelect an image to open the viewer, then use the arrow keys or swipe to move through all 6 images.
Mau Brands user flow diagram from login to business action
User flowFrom data ingestion and structuring to visualization, every step was designed to ensure accuracy, scalability, and real-time decision-making.
High-fidelity Mau Brands dashboard screens
High-fidelity designData is cleaned, modeled, and transformed into actionable dashboards that provide clear insights into performance, risks, and opportunities.
Mau Brands inventory and operations dashboard on a laptop
Operations intelligence dashboard
Mau Brands screens for Buy Box monitoring, advertising performance and alerts
Buy Box, advertising and alerts
Mau Brands product architecture flow diagram
Product architecture flow

About the project

About Mau Brands.

Mau Brands is a data-driven ecommerce analytics platform that helps Amazon brands optimize performance, manage inventory, and make faster business decisions.

TechEsthete designed and developed the system to solve key operational challenges such as fragmented data, delayed decision-making, and lack of actionable insights.

Client
Mau Brands
Industry
Amazon marketplace · Ecommerce analytics
Engagement
Ongoing partnership
Services
Data engineering, Analytics platform, Inventory intelligence, Advertising insights

The challenge

  • Ecommerce brands and agencies often struggle with data scattered across multiple tools (Seller Central, Ads Manager, spreadsheets), lack of real-time insights for decision-making, difficulty tracking inventory risks and forecasting demand, inefficient campaign optimization due to poor visibility, and Buy Box losses without clear root cause analysis.
  • These challenges lead to delayed actions, revenue loss, and operational inefficiencies.

What we built

TechEsthete designed and built a centralized analytics platform focused on clarity, speed, and actionability.

  • Unified Dashboard: integrated sales, inventory, advertising, and pricing into a single view
  • Inventory Intelligence: built forecasting, Weeks of Supply tracking, and risk detection (understock / overstock)
  • Advertising Insights: enabled performance tracking for ACOS, ROAS, spend, and campaign efficiency
  • Buy Box Monitoring: introduced competitor pricing comparison and Buy Box risk analysis

The result

Improved decision-making speed with real-time dashboards, reduced dependency on spreadsheets, increased visibility into inventory and revenue risks, and provided scalable analytics infrastructure for growing brands.

Architecture

From the source data to the system on top.

Sources

  • Amazon Seller Central
  • Amazon SP-API
  • Amazon Ads
  1. 01Amazon SP-API
  2. 02Amazon Ads API
  3. 03ETL pipelines
  4. 04Data warehouse
  5. 05BI dashboards
  6. 06Inventory forecasting
  7. 07Buy Box monitoring

The difference

Before and after.

Before

  • Data scattered across Seller Central, Ads Manager and spreadsheets
  • No real-time insights for decisions
  • Inventory risks and demand hard to track
  • Buy Box losses without a clear root cause

After

  • Faster decisions with real-time dashboards
  • Less dependency on spreadsheets
  • Visibility into inventory and revenue risks
  • Analytics infrastructure that scales with the brand

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