Work-In-Progress: conjoint analysis in Python
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Updated
Apr 29, 2018 - Python
Work-In-Progress: conjoint analysis in Python
Simple Conjoint Analyses, Tidying, and Visualization
A package for a more general, more straightforward, and more creative conjoint analysis
This repo contains files for the blog post about conjoint analysis
A companion plugin for Excel for charting Conjointly outputs (easy formatting for preference share and revenue charts from conjoint analysis simulations as well as colouring TURF analysis tables)
Syracuse University, Masters of Applied Data Science - MAR 653 Marketing Analytics
This project aims to conduct a random survey design for collecting responses regarding wine preferences of Italian consumers. Furthermore, it attempts to understand how preference share gets affected as we vary different attributes associated with wine with the use of a research method called Conjoint Analysis..
Tool: R. Conjoint analysis helps launch new products. This project helps us deeply understand how conjoint analysis gets consumers preference and segmentation, and how to simulate market to maximize profit and sustainability. It turns out that mutual cooperation yields better outcome than mutual defections.
This repo contains old academic project codes
This repository contains coursework for the Marketing Analytics course in the MS Applied Business Analytics program at Boston University.
Boiler template for creating conjoint choice based survey completely for free.
Choice-Based Conjoint Analysis, Multinomial Logit Model, Multinomial Logit Model with random coefficients
In this project we utilize Fine Needle Aspiration data and applied machine learning technique to improve classification of benign and malignant tumor. Thereafter we use Conjoint Analysis for market positioning
Simple Conjoint in Python
Conjoint Analysis on consumer preferences on Sunnyvale, California Housing Market
Used python machine learning to preform conjoint analysis on generated smartphone data
Used R to build a Conjoint Analysis from scratch, assessing the importance of different features of a Flat-Panel TV.
An app to help in the calibration of Vulnerability Scores for humanitarian assistance targeting
Explore consumer preferences & valuations for TV products with Conjoint & Bootstrapped Willingness-To-Pay analysis. Compare and analyze own design against competition for an edge! Enhance your product strategy!
Fall 2024 section of EMSE 6035: Marketing Analytics for Design Decisions @ GWU
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