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Revenue Compass

Bringing science to the art of revenue management

Overview

Revenue Compass is the fastest, most advanced and most user friendly commercial intelligence platform designed to enable fast moving consumer good (FMCG) manufacturers to reduce enterprise wide price leakages, optimize trade spending and maximize value capture by charging every channel partner prices that are uniquely right for them. Simply put, the platform allows FMCGs to weaponize their data into a competitive advantage.

Goal

To create tool that would allow Consumer HealthCare products company have a visual analyses for revenue and pricing on monthly bases.

To design an app in such a way that it would enable the granular analysis of revenue, pricing and cost offsets to that revenue using a visual drill down approach at the customer and product level.

Problem

Our team dedicate her best science and math resources in order to complete this project successfully.

When client came to us we didn’t have ready to use solutions, formulas or prototypes. We’ve created, experimented and developed algos and formulas together.

The project got two biggest challenges:

  • using millions of rows of data about company sales to generate actionable reports and summarise it all for company analysts
  • make complex graphs and UI work fast and look slick. We used 2 different charts libraries to accommodate most of 25+ app graphs

Project Results

Speed

Query tens of millions of transactions in milliseconds

Data

A cutting-edge technology stack that leverages the latest advances in stream data processing

25 +

Actionalbe data graphs

MVP Development

Our team successfully developed two modules: Performance Analytics core module and Customer Trade Portfolio module which include:

  • More than 25 graphs and complex charts
  • Optimized performance with data mining and Python Pandas techniques and tools
  • Heavily customized D3.js widgets to meet project requirements

Core System Capabilities

  • Understand the “what” and the “why”. Evaluate commercial performance trends across your portfolio of BUs, markets, channels, and brands.
  • Find your Most and Least economically profitable customers. Know precisely which customers are driving versus dragging performance in each market and why.
  • Optimize the trade portfolio.

MVP Version Mockups

Performance summary
Multi-period performance summary
Portfolio performance
Anatomy of a market
Market concentration
Cause of adverse performance

MVP Summary

4 months

Duration

2 Members

Team:
- Full-Stack Web Developer
- Business Analyst

US

Location

The Team

Artem Likhvar

Developer

Vitaliy Podoba

Business Analyst

Key Technologies Used

        

Python & Django web framework

PostgreSQL database

React library

Celery for background tasks

D3.js library

Python Pandas

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