E-com Price Optimization

Gautam Naik

Posted in Data Science • Jul 7, 2024 • 5 min read

In retail, price optimisation is an art form that aims to strike a harmonious balance between the cost of products and the willingness of customers to purchase them. The ultimate objective is to establish a price that generates substantial revenue and attracts a significant customer base. Through the intelligent analysis of data and the implementation of strategic pricing approaches, businesses can determine the optimal price point. This meticulous process enables them to maximize sales and profits while ensuring customer satisfaction and loyalty. In the following case study, we will analyse different price optimization strategies for a company.

Business Problem

TrendElite is a clothing retailer specializing in a diverse selection of apparel and accessories, operating both physical stores and an online e-commerce platform. To enhance its revenue and market competitiveness, the company aims to optimize its pricing strategy.

TrendElite faces several challenges in effectively pricing its products.

Competitive Landscape: With numerous rivals offering similar products, the retail industry is highly competitive. TrendElite aims to stand out by offering attractive prices while ensuring profitability.
Inventory Management: Ensuring effective inventory management is vital for TrendElite, as pricing strategies must balance supply and demand. Optimizing prices based on inventory levels can help prevent overstocking or understocking of products.
Seasonal and Trend Variations: The fashion industry's rapid trend changes and fluctuating demand throughout the year present challenges for TrendElite. Adjusting prices to reflect seasonal and trend shifts is crucial to capitalize on sales opportunities.

Solution

Price optimization can address the challenges mentioned above by implementing the following strategies:

Demand-based pricing: This strategy involves analyzing the demand for each product over time to determine the optimal price for each product. The approach includes setting a base price for each product and then adjusting the price based on the demand for the product.
Competitor-based pricing: This strategy entails analyzing the prices of competitors for the same product and adjusting the price based on the competitor’s pricing.
Price elasticity-based pricing: This strategy involves analyzing the price elasticity of each product to determine the optimal price. It includes setting a base price for each product and then adjusting the price based on the price elasticity of the product.

Metric

We will use the revenue earned as a metric.

Data Description

The dataset consists of monthly sales data of products, freight charges, product score, competitor price and their product score data

Field	Description
product id	A unique identifier for each product in the dataset.
product category name	The name of the product category to which the product belongs.
month year	The month and year of the retail transaction or data recording.
qty	The quantity of the product sold or purchased in a given transaction.
total price	The total price of the product, including any applicable taxes or discounts. Calculated using qty*unit price
freight price	The average freight price associated with the product.
unit price	The average unit price of a single unit of the product.
product name length	The length of the product name in terms of the number of characters.
product description length	The length of the product description in terms of the number of characters.
product photos qty	The number of photos available for the product in the dataset.
product weight g	The weight of the product in grams.
product score	Average product rating associated with the product’s quality, popularity, or other relevant factors.
customers	The number of customers who purchased the product in a given category.
weekday	Number of weekdays in that month.
weekend	Number of weekends in that month.
holiday	Number of holidays in that month.
month	The month in which the transaction occurred.
year	The year in which the transaction occurred.
s	The effect of seasonality.
Volume	Product Volume
Comp 1	Competitor1 price
Ps1	Competitor1 product rating
Fp1	Competitor1 freight price
Comp 2	Competitor2 price
Ps2	Competitor2 product rating
Fp2	Competitor2 freight price
Comp 3	Competitor3 price
Ps3	Competitor3 product rating
Fp3	Competitor3 freight price
Lag price	Previous month price of the product.

Presentation

My Recommendations For TrendElite

Pricing Strategy

The Price Elasticity to Demand strategy appears to be the most effective pricing strategy. This strategy bases pricing decisions on customer demand and their reaction to changes in price.
With this strategy, we've only adjusted the prices of products with inelastic demand, meaning that changes in price do not significantly impact customer demand.
As a result, we've observed increased sales consistently.

Holidays play a crucial role, as months with more holidays tend to have higher sales.
With the higher influx of customers during holidays, it's an opportune time to introduce new products and raise awareness.
Aim for product descriptions to be around 1000 characters in length.