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Data Analysis & Visualization

Competitor Store Analysis Platform

A price and market tracking system for e-commerce

data-store.streamlit.app
Competitor Store Analysis Platform — desktop view
3 pazaryeri
Sources
Otomatik
Collection
Power BI
Reporting

Overview

For a business selling on marketplaces, the most expensive missing piece of information is the competitor's price. When you notice a price change late, you lose not just that sale but your position in search rankings.

This platform grew out of a concrete need I encountered while working as a data analyst at Asylove. Product and price data from competing stores on Amazon, Etsy and eBay is collected regularly, normalised into a single data model and made comparable. Matching the same product across different stores makes it possible to compute the real price gap.

Through the Streamlit interface, the user picks a category, store and date range and sees price distribution, assortment breadth and change over time. Analysis results were also fed into Power BI and folded into management reporting. The system's real gain is speed: a competitor sweep that previously took days by hand became an automated pipeline.

Highlights

  • Regular data collection from multiple marketplaces
  • Matching the same product across stores
  • Price distribution and time series visualization
  • Feeding into Power BI management reporting

Objectives

  • Notice competitor price changes early, not late
  • Automate the manual competitor sweep
  • Ground pricing decisions in data

Solution

  • Normalising marketplace data into one schema
  • Building the product matching logic
  • An interactive filtering interface with Streamlit
  • Merging analysis output into Power BI

Approach

  1. 01Identifying with the sales team which decisions get made
  2. 02Building the collection and normalisation pipeline
  3. 03Interface development and hooking it into reporting

Outcomes

  • A competitor sweep that took days became an automated pipeline
  • Pricing decisions became data-supported
  • Gaps in assortment became visible
  • Analysis results were integrated into management reporting

Challenges

  • Reconciling data formats across different marketplaces
  • The same product listed under different names
  • Keeping data collection sustainable and regular

Selected Work

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