GitHub topics: pricing-strategy
chrisayyildiz/dynamic-pricing-engine
ML system for profit maximisation featuring frontend adapters, scrapers, user modelling, and behavioural economics
Language: Python - Size: 11.2 MB - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 0 - Forks: 0
inaborges/Pricing-Analytics
Pricing Analytics: Como os Dados Guiam Estratégias de Mercado de Cobre Trabalho apresentado para obtenção do título de especialista em Business Intelligence & Analytics na ECA-USP Pricing Analytics: How Data Guides Copper Market Strategies Work was presented to attain the Specialist in Business Intelligence & Analytics title at ECA-USP
Language: Jupyter Notebook - Size: 193 KB - Last synced at: 13 days ago - Pushed at: 14 days ago - Stars: 0 - Forks: 0
EthanChungBU/BU_MSBA_830
Business Experimentation: A/B Testing
Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0
zahramh99/dynamic-pricing-strategy
Dynamic Pricing is an application of data science that involves adjusting the prices of a product or service based on various factors in real time. It is used by companies to optimize revenue by setting flexible prices that respond to market demand, demographics, customer behaviour and competitor prices.
Language: Python - Size: 33.2 KB - Last synced at: 15 days ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
Aytaj9/Online-Sport-Retail-Analysis
This report presents a detailed analysis of an online sport retail business, focusing on revenue metrics, product performance, customer engagement, pricing strategy, brand analysis, and seasonal trends. Through Python and SQLite, various aspects of the business were examined and revealing key insights into revenue generation.
Language: HTML - Size: 124 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
tirthgala/Cluster-Analysis-for-Game-Selection
In this repository through advanced data analytics and market research assessed financial viability, customer behaviors, and market trends to form a strategic game acquisition recommendation. Process included market share simulation, cluster and factor analysis, GaborGranger pricing strategy, and customer segmentation.
Language: Jupyter Notebook - Size: 1.08 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
