Tag: Ecommerce

  • Walmart Weekly Sales Time Series Forecasting using SARIMAX & ML Models

    Walmart Weekly Sales Time Series Forecasting using SARIMAX & ML Models

    The blog post delves into Time Series Forecasting (TSF), using SARIMAX and Supervised Machine Learning algorithms to predict Walmart’s weekly store sales. Factors affecting sales are investigated for strategies to increase revenues. The study additionally covers data preparation, feature correlation analysis, SARIMAX diagnostics, and the training of supervised ML models like Linear Regression, Random Forest,…

  • Sales Forecasting: tslearn, Random Walk, Holt-Winters, SARIMAX, GARCH, Prophet, and LSTM

    Sales Forecasting: tslearn, Random Walk, Holt-Winters, SARIMAX, GARCH, Prophet, and LSTM

    The data science project involves evaluating various sales forecasting algorithms in Python using a Kaggle time-series dataset. The forecasting algorithms include tslearn, Random Walk, Holt-Winters, SARIMA, GARCH, Prophet, LSTM and Di Pietro’s Model. The goal is to predict next month’s sales for a list of shops and products, which slightly changes every month. The best…

  • An Overview of Video Games in 2023: Trends, Technology, and Market Research

    An Overview of Video Games in 2023: Trends, Technology, and Market Research

    The gaming industry is rapidly growing, projected to reach a revenue of $365.6 billion in 2023. Major trends include Web3 gaming, AI integration, and a push for consolidation. Fashion brands collaborate for virtual sales, and advances in gaming technology, such as AR/VR and cloud-based gaming, promise an even more immersive experience for gamers.

  • Unsupervised ML, K-Means Clustering & Customer Segmentation

    Unsupervised ML, K-Means Clustering & Customer Segmentation

    Table of Clickable Contents Motivation Methods Open-Source Datasets This file contains the basic information (ID, age, gender, income, and spending score) about the customers. Online retail is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail. The company mainly sells unique all-occasion…

  • Top Fast-Growing Apps in 2023

    Top Fast-Growing Apps in 2023

    The OKTA Business at Work report and blogs by Leon Zucchini discuss the fastest-growing and new app categories. Key trends include the growth of collaboration, communication, and travel apps, and the adoption of multi-cloud. Ten notable growing apps are Kandji, Grammarly, Bob, Notion, Prisma Access, Navan, GitLab, Ironclad, Terraform Cloud, and Figma. Emerging apps include…

  • Multi-Label Keras CNN Image Classification of MNIST Fashion Clothing

    Multi-Label Keras CNN Image Classification of MNIST Fashion Clothing

    Machine learning and deep learning are invaluable in optimizing supply chain operations in fashion retail. Even smaller retailers are leveraging ML algorithms to meet customer demands. Neural network models, particularly Convolution Neural Networks (CNN) are used to classify clothing images, like the Fashion-MNIST dataset, with high accuracy. Hyperparameter optimization using GridSearchCV and Nadam optimizer are…

  • Brazilian E-Commerce Showcase

    Brazilian E-Commerce Showcase

    This is a hands-on end-to-end Brazilian e-commerce use-case with detailed Exploratory Data Analysis (EDA) steps and business action items. We apply the RFM Segmentation and Customer Analysis to the Brazilian E-Commerce Public Dataset by Olist. It focuses on the lifetime value of customers, and it’s the preferred customer segmentation methodology for eCommerce businesses that focus…

  • K-means Cluster Cohort E-Commerce

    K-means Cluster Cohort E-Commerce

    K-means Clusters – Cohort Analysis applied to E-Commerce Understanding who your customers are and what they want is a fundamental part of any successful business. It can become increasingly challenging to create a one-size-fits-all customer profile. This is where the concept of cluster-based cohort analysis comes in. 

  • AI-Powered Customer Churn Prediction

    AI-Powered Customer Churn Prediction

    AI-Powered Customer Churn Prediction Churn is a good indicator of growth potential. Churn rates track lost customers, and growth rates track new customers—comparing and analyzing both of these metrics tells you exactly how much your business is growing over time. In this project, we explored the churn rate in-depth and examined an example implementation of…

  • E-Commerce Cohort Analysis in Python

    Cohort analysis (CA) is a beneficial tool in e-commerce marketing to monitor campaign health, particularly in customer retention rates. By grouping customers into cohorts, marketers can assess the effectiveness of their efforts, track customer behaviors, and identify the most valuable demographic segments. The article exemplifies how CA can be applied to customer transaction data using…

  • E-Commerce ML/AI Classification

    The article outlines the process of using TensorFlow to categorize clothing images. It involves pre-processing data, building an ML model, and making predictions. The application relies on Python and Jupyter Anaconda IDE, using the tf.keras high-level API. The dataset comprises 60,000 grayscale images in various fashion categories, with data divided into training and testing sets…