Price Elasticity: Maximizing revenue without losing customers

Balancing promotional markdowns against margin health is a fundamental price elasticity challenge. Reckless, untargeted discounting degrades brand equity and creates a race to the bottom, whereas data-validated pricing models capture maximum consumer surplus. This mission serves the Propulsion pillar by providing the analytical foundation necessary to accelerate volume growth and maximize top-line revenue without triggering margin bleeding.

Core Project Architecture

bigbasket-data-analysis/

├── data/           # Processed and engineered data targets

│   └── bigbasket_cleaned.csv

├── scripts/        # Modular Python infrastructure for data jobs

│   ├── data_preprocessing.py

│   └── eda_analysis.py

├── docs/           # Analytical artifacts

visualization exports

and dashboards

└── README.md

Catalog Diagnostics & Data Trends

1. Pricing and Rating Distributions

A deep dive into inventory pricing reveals a heavy concentration targeting budget-conscious consumers

balanced by exceptionally stable satisfaction scores.

| Metric Evaluated | Empirical Findings | Strategic Business Insight |

| --- | --- | --- |

| Price Distribution | Most products are priced **under ₹1

000**. Sale values are heavily right-skewed. | The core inventory successfully anchors the mass-market demographic. However

clear whitespace exists for premium product-line extensions. |

| Average Rating | Overall platform rating sits at 3.99/5.0

with a dense concentration at 4.0+ or higher. | Products consistently hit quality benchmarks

establishing a strong trust baseline crucial for driving recurring customer retention. |

2. Discount Strategy vs. Category Performance

Analyzing allocation metrics reveals a massive disparity in how discounts are deployed across different business categories.

| Product Category | Total Stock Count | Average Applied Discount | Operational & Strategic Note |

| --- | --- | --- | --- |

| Beauty & Hygiene | 7

867 units (Largest) | Moderate | This represents the platform's flagship volume footprint; priorities must center on strict inventory velocity and rotation. |

| **Kitchen

Garden & Pets** | Scaled Segment | 22.2% (Highest Platform Markdown) | Critical Friction Point: Deep cuts indicate aggressive clearance maneuvers or heavy competitive pricing pressure. |

Business Applications & Strategic Rollout

1. Elasticity-Based Markdown Planning

BigBasket must transition away from sweeping categorical discounts. Markdowns should be surgically concentrated on high-rating

high-margin items to stimulate demand volumes without destroying brand equity or sacrificing net profitability.

2. Category Procurement Corrections

Launch an internal operational audit of the *Kitchen

Garden & Pets* segment. The business must identify if the 22.2% markdown rate stems from over-purchasing or supply chain inefficiencies

then realign procurement volumes to prevent margin erosion.

3. Price-Point Anchoring

Leverage the sale price distribution model to engineer highly competitive pricing tiers for fast-moving consumer goods (FMCG) sitting below the **₹1

000 threshold**

capturing price-sensitive customer segments.

4. High-Value Inventory Prioritization

Dynamically cross-reference velocity rates with user ratings. Ensure that products maintaining a 4.0+ score are prioritized in fulfillment centers to mitigate out-of-stock financial penalties on high-reputation lines.