Machine Learning project for Retail Price Optimization

In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.

START PROJECT

Project Template Outcomes

  • Understanding the retail price optimization machine learning problem
  • In depth understanding of price elasticity
  • Settings for Jupyter notebook to enablefaster coding
  • Importing Libraries
  • Connecting Postgres database to Python
  • Importing datasets and initial understanding with the help of visualizations
  • Understanding business context with the help of data
  • Combining data
  • Making inferences from plots
  • Learning to segregate data based on analysis
  • Implementing model to identify price elasticity of items
  • Creating generic code to identify price elasticity of all items
  • Understand criteria to select model
  • Walkthrough of price optimization for one product and visualizing the outputs
  • Generic code for price optimization for all products

Get started today

Request for free demo with us.

white grid

Architecture Diagrams

Unlimited 1:1 Live Interactive Sessions

  • number-icon
    60-minute live session

    Schedule 60-minute live interactive 1-to-1 video sessions with experts.

  • number-icon
    No extra charges

    Unlimited number of sessions with no extra charges. Yes, unlimited!

  • number-icon
    We match you to the right expert

    Give us 72 hours prior notice with a problem statement so we can match you to the right expert.

  • number-icon
    Schedule recurring sessions

    Schedule recurring sessions, once a week or bi-weekly, or monthly.

  • number-icon
    Pick your favorite expert

    If you find a favorite expert, schedule all future sessions with them.

  • number-icon
    Use the 1-to-1 sessions to
    • Troubleshoot your projects
    • Customize our templates to your use-case
    • Build a project portfolio
    • Brainstorm architecture design
    • Bring any project, even from outside ProjectPro
    • Mock interview practice
    • Career guidance
    • Resume review
squarebox svg

Customers sharing their love on online platforms

user review

Source: quora

user review

Source: quora

user review

Source: trustpilot

user review

Source: quora

user review

Source: quora

user review

Source: quora

user review

Source: trustpilot

user review

Source: quora

user review

Source: quora

user review

Source: quora

user review

Source: quora

user review

Source: quora

user review

Source: quora

arrow left svg
arrow right svg

Benefits

250+ end-to-end project solutions

250+ end-to-end project solutions

Each project solves a real business problem from start to finish. These projects cover the domains of Data Science, Machine Learning, Data Engineering, Big Data and Cloud.

15 new projects added every month

15 new projects added every month

New projects every month to help you stay updated in the latest tools and tactics.

500,000 lines of code

500,000 lines of code

Each project comes with verified and tested solutions including code, queries, configuration files, and scripts. Download and reuse them.

600+ hours of videos

600+ hours of videos

Each project solves a real business problem from start to finish. These projects cover the domains of Data Science, Machine Learning, Data Engineering, Big Data and Cloud.

Cloud Lab Workspace

Cloud Lab Workspace

New projects every month to help you stay updated in the latest tools and tactics.

Unlimited 1:1 sessions

Unlimited 1:1 sessions

Each project comes with verified and tested solutions including code, queries, configuration files, and scripts. Download and reuse them.

Technical Support

Technical Support

Chat with our technical experts to solve any issues you face while building your projects.

7 Days risk-free trial

We offer an unconditional 7-day money-back guarantee. Use the product for 7 days and if you don't like it we will make a 100% full refund. No terms or conditions.

Payment Options

Payment Options

0% interest monthly payment schemes available for all countries.

listed companies

Testimonials

white grid

Comparison with other platforms

We provide ready-made project templates that solve real business problems, end-to-end and comes with solution code,
explanation videos, cloud lab environment and tech support.

End-to-end implementation
Real industry grade projects
by industry experts
Ready-made solutions to real
business problems
Detailed Explanations
kaggle
icon
Courses/ Tutorials
icon
icon
icon
icon
icon
icon
icon
icon
icon
icon
icon
icon
icon
icon
icon
icon
icon

Our expert panel

world bg

Project Description

Introduction to Price Optimization

Pricing a product is a crucial aspect of any business. A lot of thought process is put into it. There are different strategies to estimate prices for different kinds of products. There are products whose sales are pretty sensitive to their costs, and as such, a slight change in their price can lead to a noticeable difference in their sales. At the same time, there are also products whose sales are not much affected by their worth - these tend to be luxury items or necessities (like certain medicines). 

 

Price elasticity of demand (EPD), or elasticity, is the degree to which the compelling desire for something changes as its price changes. In general, people desire things less as those things become more expensive. However, for some products, the customers’ desire could drop sharply even with a bit of price increase, and for other products, it could stay almost the same even with a hefty price increase. Economists use the term elasticity to denote this sensitivity of sales to price fluctuations. More precisely, price elasticity gives the percentage change in quantity demanded when there is a one percent increase in price, holding everything else constant.

Retail Price Optimization in Python

In this machine learning pricing optimization case study, we will take the data of a cafe and, based on their past sales, identify the optimal prices for their items based on the price elasticity of the items. The data is stored in a PostgreSQL database hosted on Amazon RDS. First, you will calculate the price elasticity for each item, then figure out the optimal price. While taking a particular cafe data, one can extend this work to price any product. This machine learning retail price optimization project will focus on the former products.

Machine Learning project for Retail Price Optimization

Dynamic Pricing Dataset

The data is contained in three CSV files.

Cafe - Sell MetaData.csv This file has details about sales made by the cafe. 

Columns: Sell ID, Sell Category, Item ID, Item Name

Cafe - Transaction - Store.csv This file contains information about transactions and sale receipts of the cafe.

Columns: Calendar Date, Price, Quantity, Sell ID, Sell Category

Cafe - DateInfo.csv This has date information corresponding to the transactions performed.

Columns: Date, Year, Holiday, Weekend, School Break, Temperature, Outdoor

 

Also, We will learn to fetch the data from Postgres database to python using psycopg2 library. 

Topics Covered in Price Optimization Machine Learning Project

In detail, let us discuss all tools and techniques you will explore in this project.

 

Price Optimization Algorithms

Understanding customer behavior through sales data is crucial for the growth of any business. Not only it contributes to improved quality of products, but it additionally assists in determining the right price for the different products. For instance, products perceived as luxury items by the masses are sold at unreasonably high prices. In this dynamic pricing python project, you will use previous sales data to estimate the cost of different food items in a cafe. Additionally, you will learn about other price optimization methods like cost-less pricing, competition-based pricing, perceived value pricing, and demand-based pricing. This project will also introduce you to price elasticity, a concept that plays a critical role in determining price estimates.

 

Exploratory Data Analysis

Before the price optimization dataset is used for modeling, it must be processed. The dataset may contain redundancy that one must remove, and one must bring on all the variables of different data types on the same foot. In this project, you will work on the dataset of a burger cafe and use their three datasets related to sales, transactions, and corresponding dates. You will learn how to analyze the dataset using data visualization libraries of Python: matplotlib and seaborn. This price optimization machine learning project will also guide you on merging the datasets and preparing them to apply machine learning algorithms using Pandas dataframes.

 

Machine Learning Algorithms

Instead of traditional statistical methods of price estimation, this project will perform price optimization using machine learning in Python. You will learn how to use the regression trees and ordinary least square method to estimate the price elasticity for different products. Furthermore, you will understand how statistical parameters like the r-squared value are interpreted for analysis. The project will also teach you how to improve the accuracy of the models by eliminating specific variable values. Additionally, you will explore maximizing profit using the results of price elasticities evaluation.

 

Application of Machine Learning for Pricing Optimization in Python Project

Primarily, this project focuses on optimizing the prices of various items available in a burger cafe. The solution of this pricing optimization in Python project can be easily used by experts of different industries like medical, hospitality, insurance, etc. For example, an analyst can recommend changes to the prices of various services offered by a hotel depending on the previous residents’ feedback.

FAQs for Pricing Optimization with Machine Learning

1) How do you do Price Optimization?

One can apply different types of price optimization techniques like reducing cannibalization for inter and intra products of the same company, reducing cost drastically while playing a volume game etc.   

2) What is Price Optimization Machine learning?

Price Optimization can be achieved using regression machine learning algorithms like linear regression. One can first estimate the price elasticity for each product using the past sales data and then use that coefficient for price optimization.

Latest Blogs

Data Engineer’s Guide to 6 Essential Snowflake Data Types

Data Engineer’s Guide to 6 Essential Snowflake Data Types

From strings to timestamps, six key snowflake datatypes a data engineer must know for optimized analytics and storage | ProjectPro

Learning Artificial Intelligence with Python as a Beginner

Learning Artificial Intelligence with Python as a Beginner

Explore the world of AI with Python through our blog, from basics to hands-on projects, making learning an exciting journey.

30+ NumPy Interview Questions and Answers for Data Analysts

30+ NumPy Interview Questions and Answers for Data Analysts

Prepare for success in data analyst interviews with our curated list of 30+ NumPy Interview Questions and Answers. | ProjectPro

View all blogs

We power Data Science & Data Engineering
projects at

projectpro i trusted leader projectpro i trusted leader projectpro i trusted leader

Join more than
115,000+ developers worldwide

Get a free demo