Problem Statement:
In retail, optimizing shelf space directly impacts product visibility, customer experience, and sales.
Develop a tool that optimizes product allocation to limited shelf space considering factors like popularity, seasonality, and profit margins.
Product Popularity Algorithm:

• Assess product popularity based on historical sales, customer reviews, and real-time trends.
• Utilize machine learning and sentiment analysis for accurate predictions.

Seasonal Variation Analysis:

• Identify and adapt to seasonal changes in demand using predictive models.

Profit Margin Optimization:

• Prioritize products with higher profit margins for prime shelf space.
• Create an intuitive dashboard displaying key metrics and recommendations.
• Allow retailers to experiment with shelf layouts using drag-and-drop functionality.

Augmented Reality Shelf Simulation:

• Visualize different shelf layouts in-store using augmented reality technology.
• Predict customer traffic and visibility impact for each layout.

Predictive Stock Replenishment:

• Detect out-of-stock products in real-time and generate replenishment orders.
• AI Retail Assistant, helps you as a data analyst and one stop solution for all our business development
  queries eg : what product i should place on my first shelf to maximize profitability

Smart Retail AI Customer Engagement Analytics:

• Integrate customer engagement metrics for targeted product marketing.