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Pricing and Promotion Strategy for Sporting Goods company

Tableau
Python
Snowflake
Apache Airflow
R
Challenges
  • Maximizing revenue while maintaining customer demand poses challenges in determining the most effective pricing strategy.
  • Setting the right price is crucial in competitive markets to maintain competitiveness.
  • Accurate revenue forecasting relies on understanding the impact of price changes on demand, which can be achieved through price elasticity modelling.
  • Price elasticity insights help organizations understand customer sensitivity to price changes, preventing potential negative impacts on sales and revenue.
Solutions
  • Data Collection and Analysis: Gather historical sales data and prices to establish the basis for price elasticity modeling.
  • Model Selection and Calibration: Choose suitable price elasticity models based on product, market, and data attributes. Adjust model parameters for accuracy and dependability.
  • Scenario Analysis: Perform scenario analysis to evaluate the effects of various price adjustments on demand and revenue.
  • Real-Time Monitoring:  Implement a system to monitor market dynamics and customer behavior in real-time, enabling prompt responses to changes in price sensitivity.
Benefits
  • Understand price-demand relationship.
  • Optimize pricing strategy.
  • Identify price-sensitive customer segment.
  • Make data-driven decisions on promotions and pricing strategies.
  • Assess the potential revenue impact of price changes.
  • Evaluate the impact of price adjustments on profit margins.

US based Leading retailer for sporting goods (ecommerce)

The challenge lies in devising an effective pricing strategy to maximize revenue while meeting customer demand, necessitating the implementation of robust data analysis techniques and real-time monitoring systems to adapt to dynamic market conditions and mitigate potential negative impacts on sales and revenue.