Skip to content

Web Apps / SaaS

Commerce Insights Dashboard

Unified Merchandising & Margin Analytics

An analytics platform consolidating orders, inventory, advertising and returns into one margin-accurate view of product performance.

  • Next.js
  • TypeScript
  • Python
  • PostgreSQL
  • Docker
Abstract analytics dashboard layout with charts and product performance panels

Overview

Project Overview

A multi-channel retailer was making buying decisions on revenue because true margin was spread across five systems and reconciled by hand each month. We built a warehouse-backed analytics platform that consolidates orders, cost of goods, advertising spend, fees and returns into a single contribution-margin figure per product — updated daily rather than monthly.

Services provided

  • Web Application Development
  • Custom Software Development
Client
Confidential — multi-channel retailer
Industry
E-commerce & Retail
Timeline
12 weeks
Year
2024
Platforms
Web application
Team
2 engineers, 1 data engineer, 1 designer

Challenge

The Challenge

Merchandising decisions were made on revenue because margin was only known a month in arrears, after a manual reconciliation across five systems.

  • Cost, fee, advertising and return data lived in five separate systems.

  • Reconciliation was a multi-day manual process performed monthly.

  • Products that looked profitable on revenue were loss-making after returns and ad spend.

  • Existing reporting timed out on queries spanning more than a quarter.

Solution

What We Built

We built the margin model once, in the warehouse, and made every view read from it — so no team maintains its own version of the truth.

  • Built scheduled ingestion from each platform with schema validation and drift detection.

  • Modelled contribution margin explicitly, with each cost component traceable to its source.

  • Pre-computed rollups and materialised views to keep large queries interactive.

  • Replaced monthly reconciliation with a daily refresh and a visible data-freshness indicator.

  • Added saved views and threshold alerts so teams are notified rather than having to check.

Capabilities

Key Features

What Commerce Insights Dashboard does in day-to-day use.

  • True contribution margin

    Cost of goods, fees, shipping, advertising and returns combined into one figure per product.

  • Multi-channel consolidation

    Marketplace, direct and wholesale performance normalised into a comparable model.

  • Inventory intelligence

    Sell-through, cover and reorder signalling based on velocity rather than static thresholds.

  • Return rate analysis

    Returns attributed to product, variant and channel to expose hidden margin loss.

  • Saved views & alerts

    Teams save their own segmentation and receive alerts when a metric crosses a threshold.

  • Fast aggregate queries

    Pre-computed rollups keep multi-year, multi-million-row queries interactive.

Stack

Technology Stack

The tools this system runs on, grouped by the role they play.

  • Frontend

    • Next.js
    • React
    • TypeScript
    • Tailwind CSS

  • Backend

    • Python
    • FastAPI
    • Scheduled ETL

  • Data

    • PostgreSQL
    • Materialised views
    • Columnar aggregates

  • Integrations

    • Commerce platform APIs
    • Ad platform APIs
    • REST

  • Infrastructure

    • Docker
    • Vercel
    • GitHub Actions

Architecture

How It Works

The path a single request takes through the system, end to end.

    INGEST01

    Scheduled extraction

    Each platform is pulled on schedule with schema validation.

    MODEL02

    Normalise

    Orders, costs, fees and ad spend mapped into one comparable model.

    COMPUTE03

    Derive margin

    Contribution margin calculated per product, variant and channel.

    ROLLUP04

    Pre-aggregate

    Materialised views keep interactive queries fast at scale.

    SERVE05

    Explore & alert

    Saved views, segmentation and threshold notifications.

Outcome

Results

What changed for the business after launch.

  • 5 → 1

    Data sources consolidated

    One margin model, one refresh, one source of truth.

  • Monthly → daily

    Margin reporting cadence

    Manual reconciliation removed from the finance calendar.

  • < 2s

    Typical dashboard query

    Across multi-year, multi-million-row datasets.

  • 18%

    Catalogue found loss-making

    Products profitable on revenue but negative after fees and returns.

Interface

A Closer Look

Screens from the delivered system.

  • Product margin overview dashboard
    Contribution margin per product across every channel.
  • Inventory cover and sell-through view
    Sell-through and cover based on live velocity.
  • Return rate breakdown by variant
    Return attribution down to variant and channel.

More work

Related Projects

Other systems built on similar foundations.

View all projects
  • Abstract layout of a customer relationship platform with linked record panels

    SaaS / AI

    Smart CRM

    A multi-tenant CRM with AI assistance built into the record, summarising history and surfacing the next action for every account.

    • Next.js
    • TypeScript
    • PostgreSQL
    • OpenAI
    • +1

    View Case Study

  • Abstract representation of document parsing into structured candidate profiles

    AI / Web Application

    AI Resume Platform

    A web platform that parses resumes into structured data, matches candidates to roles with an explainable score, and generates tailored documents.

    • Next.js
    • Python
    • FastAPI
    • OpenAI
    • +1

    View Case Study

Next step

Want a System Like This?

Tell us what your business needs to automate and we'll map out a practical build.

Book a Free ConsultationContact Us

hello@devrox.comWe reply to every enquiry within one business day.