marketing-mix-modeling

There are 15 repositories under marketing-mix-modeling topic.

• facebookexperimental / Robyn

  Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.

  marketing-mix-modelingmarketing-mix-modellingmmmmarketing-scienceeconometricsadstockingcost-response-curvebudget-allocationhyperparameter-optimizationevolutionary-algorithmridge-regressiongradient-based-optimisation
  Language:Jupyter Notebook 1022

• sibylhe / mmm_stan

  Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS

  stanpystanbayesian-regressionconstrained-regressionmarketing-mix-modelingmedia-mix-modelingroas
  Language:Jupyter Notebook 321

• Nikhilkohli1 / Digital-Marketing-Analytics

  This contains projects based on Algorithmic Marketing like Marketing Mix Modeling, Attribution Modeling & Budget Optimization, RFM Analysis, Customer Segmentation, Recommendation Systems, and Social Media Analytics

  digital-marketing-analyticsmarketing-dashboardattribution-modeluplift-modelingrfm-analysismarketing-mix-modeling
  Language:Jupyter Notebook 180

• Better-Boy / Market-Mix-Modelling

  This repository contains the code and explanation for market mix modelling technique in economics

  marketing-mix-modelingpythonr
  Language:HTML 51

• DoktorMike / dammmdatagen

  Marketing Mix Modeling Data Generator

  benchmarkdatadata-generatormarketing-mix-modeling
  Language:R 40

• SooyeonWon / customer_analytics_fmcg

  Customer & Purchase Analytics using Segmentation, Targeting, Positioning, Marketing Mix, Price Elasticity

  segmentationtargetingpositioningprice-elasticityfmcgcustomer-analyticsdata-analysis-pythonjupyter-notebooksmarketing-mix-modeling
  Language:Jupyter Notebook 35
• Marketing-Mix-Models

  iamcici0424 / Marketing-Mix-Models

  This repo contains the project details of the Applied Data Science Course, which is Marketing Mix Models regarding the advertising response measurement.

  marketing-mix-modelingadtechmarketing-analytics
  21

• annalectnl / weibull-adstock

  Modeling adstock in media mix modeling using Weibull transformations.

  weibull-transformationmarketing-mix-modelingtime-series-analysisadstock
  16

• edwinnglabs / karpiu

  Karpiu is a package designed for marketing mix modeling by calling Orbit from the backend. Karpiu is still in its beta version. Please use it at your own risk.

  bayesianbudget-optimizationmarketing-analyticsmarketing-mix-modelingpythontime-series
  Language:Python 16

• annalectnl / ml-in-mmm

  In this paper we researched the accuracy and usability of machine learning models for MMM analyses.

  machine-learningmarketing-mix-modelingweibull-transformationgenetic-algorithmshapley-valuestime-series-analysis
  11

• abhinav1024 / Marketing_Mix_Modelling-MMM-

  A Marketing Mix Modelling project for an E-Commerce company

  machine-learningmarketing-mix-modelingpythonregression
  Language:Jupyter Notebook 8

• imnikhilanand / Bayesian-Marketing-Mix-Modeling

  The project analyses the impact of different marketing tactics on the sales of items. The problem is a multivariate-modeling problem as there are 3 different tactics of marketing. Since, the impact of marketing medium cannot be negative we will be using Bayesian model for regression.

  bayesian-regressionmarketing-mix-modelingols-regressionstatistics
  Language:Python 4

• RyanAugust / PySiMMMulator

  PySiMMMulator is an open source Python adaption of the R-package siMMMulator, which allows users to generate simulated data to use in testing Marketing Mix Models (MMMs).

  marketing-mix-modelingmarketing-sciencemmmpythonmarketing
  Language:Python 4

• nitinjosephrepo / Marketing-Mix-Modeling-MMM-Using-Robyn

  A New GeneratUsing Robyn aims to reduce human bias in the modeling process, esp. by automating modelers decisions like adstocking, saturation, trend & seasonality as well as model validation. Moreover, the budget allocator & calibration enable actionability and causality of the results

  adstockingfacebook-prophetmarketing-mix-modelingmarketing-sciencemmmnevergrad
  Language:R 2

• majd30 / Marketing-Mix-Modeling-project-with-Multiple-Regression

  In order to inform decisions about an optimal marketing budget, the project uses multiple regression analysis to assess the impact of TV, radio, and newspaper ad budgets on Company X's sales.

  excelmarketing-mix-modelingmultiple-linear-regressionpowerpoint-presentations
  1