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pricing-strategy

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This article reframes pricing as a negotiation rather than a prediction, showing how price emerges from tensions between product reality, market dynamics, and buyer behavior. It introduces negotiation-aware ML, value decomposition, and equilibrium modeling to build transparent, human-aligned pricing systems.

  • Updated Dec 11, 2025

Business consulting plugin for Claude — 16 skills, 24 commands, 5 industry overlays. Market research, competitive analysis, financial modeling, strategy frameworks, pricing, M&A, digital transformation, risk, talent, and more.

  • Updated Feb 28, 2026

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.

  • Updated Apr 7, 2025
  • Python

Analyze consumer preferences to segment products and guide product, pricing, and portfolio strategy using affinity-based data.

  • Updated Jun 16, 2026
  • Jupyter Notebook

A luxury retail analytics project utilizing Inferential Statistics (Confidence Intervals for Means & Proportions) to optimize diamond pricing strategies and forecast inventory distribution using Excel and Google Sheets.

  • Updated Mar 11, 2026

Machine Learning capstone project predicting used car prices using data preprocessing, feature engineering, and regression modeling. Includes EDA, model development, evaluation, and business insights for pricing strategy.

  • Updated Apr 28, 2026
  • Jupyter Notebook

🔔 Receive Apple App Store revenue notifications in real-time on your device with RevenueBell, a lightweight Cloudflare Worker script.

  • Updated Jun 16, 2026
  • JavaScript

Affinity-based consumer segmentation analysis linking product attributes to distinct customer personas, with strategic implications for pricing, positioning, and portfolio design.

  • Updated Feb 23, 2026
  • Jupyter Notebook

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.

  • Updated May 1, 2024
  • HTML

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