Automated Real-Time Competitor Price Analysis Tool for Stella Green

Desired outcome

The goal of this task is to develop an automated tool for monitoring competitor prices in Stella Green’s key markets. Students will develop a web scraper in Python that will collect daily price data from selected online stores and store it in a database. Additionally, the system will analyze the collected data, generate the average market price, create price trend charts, and send price alerts when promotions are detected.

Initial Problem Description

A one-time competitor price analysis quickly becomes outdated, as prices change dynamically due to seasonality, promotions, and competitor strategies. A lack of real-time pricing insights can result in ineffective price management for Stella Green, leading to a loss of market competitiveness.
Key challenges:
• Lack of systematic real-time price analysis of competitors.
• Price fluctuations in online stores, influenced by promotions and discount strategies.
• Diverse pricing strategies across different markets (e.g., Germany vs. UK vs. Scandinavia).
• Lack of a quick response mechanism to competitors’ price changes.
The solution is to develop an automated system for collecting and analyzing price data.

Context

This system will provide daily monitoring of competitor prices and deliver real-time insights, enabling Stella Green to:
• React quickly to price changes – dynamically adjust pricing strategies.
• Analyze price trends – track how prices evolve over time.
• Identify competitor discount strategies – monitor seasonal price adjustments and promotions.
• Improve pricing policy management – make data-driven pricing decisions rather than relying on intuition.

Connection to cross-cutting areas

• Circular Economy – The tool can analyze whether eco-friendly products have a different pricing strategy compared to standard plastic alternatives.
• Overall Sustainable Development – Do competitors apply additional charges for sustainable materials or eco-friendly packaging?
• Industry 4.0 & Digitization – Automating price data collection and analysis aligns with intelligent business solutions.

Input

Input Data
• List of Stella Green products and a list of competitor products to be monitored.
• List of online stores where competitor products are available.

Expectations

Students will develop a real-time competitor price monitoring system, which will include:
1. A Python-based web scraper that:
o Automatically collects price data for competitor products from selected online stores.
o Runs continuously, retrieving data on a daily basis.
o Handles dynamic websites (e.g., using Selenium or BeautifulSoup).
2. A database for storing price information, which will include:
o Daily price records for each product.
o Information on promotions and discounts.
o A historical record of price changes for each product.
3. A data analysis system that:
o Calculates the average market price for each product.
o Generates price trend charts (e.g., line graphs showing price fluctuations over time).
o Triggers price alerts when a promotion or significant price change is detected.
4. A user interface for data visualization, such as:
o A simple dashboard displaying pricing insights.
o Summary reports highlighting price changes over selected periods.

Desired Team Profile

• Students specializing in computer science, data analytics, programming, and business intelligence.
• Individuals proficient in Python (web scraping, data analysis, automation).
• Students experienced in working with SQL databases and analytical tools.
• Basic knowledge of data visualization tools (e.g., Matplotlib, Power BI, Tableau) is a plus.

Additional Information

• Price data must be collected in compliance with online store regulations, preferably via API when available. If no API is provided, the scraper should extract price data from elements labeled as "price," "cena," or similar, depending on the website’s structure.
• The tool must be optimized to avoid detection by anti-bot mechanisms.
• Price data should be stored in a structured format to allow historical trend analysis (e.g., SQL database).
• This task does not involve a one-time price analysis but the creation of a long-term solution that operates continuously.

Related Keywords

• Digitalization
• Computer related
• Electronics Related Market