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mukulsinghal001 /customer-lifetime-prediction-using-python

Star141

What is CLV or LTV? CLV or LTV is a metric that helps you measure the customer's lifetime value to a business. In this kernel, I am sharing the customer lifetime value prediction using BG-NBD, Pareto, NBD & Gamma Model on top of RFM in Python.

python machine-learning ecommerce data-analysis e-commerce customer-lifetime-value clv ltv customer-lifetime customer-segmentation marketing-analytics customer-analytics e-commerce-project bg-nbd

UpdatedDec 4, 2022
Jupyter Notebook

roscibely /MPC-control-with-LMIs

Sponsor

Star39

MODEL PREDICTIVE CONTROL (MPC) CONTROL BASED ON THE QUASI-MIN-MAX ALGORITHM WITH RELAXATION IN LMIS

optimization matlab mpc relaxation lmis linear-matrix-inequalities yalmip ltv boost-converter model-predictive-control mpc-control dc-dc-converter mpc-lmi offline-mpc mpc-matlab

UpdatedDec 14, 2024
MATLAB

zboris12 /zgapdfsigner

Star30

A javascript tool to sign a pdf in web browser, google apps script and nodejs.

javascript typescript google-apps-script tsa ltv pdf-encryption pdf-signature pdf-sign

UpdatedAug 24, 2024
JavaScript

akulumbeg /awesome-clv-models

Star18

🎓📚📈 Collection of scientific publications that explore, model and predict customer churn and lifetime value (CLV)

marketing collection models prediction papers customer customer-lifetime-value clv ltv

UpdatedFeb 11, 2024

harveyjhuang777 /ecommerce_analysis_tools

Star6

Brief introduction of ecommerce tool including life time value (LTV), net promoter score (NPS) and cohort analysis table.

ecommerce python3 ipynb nps cohort ltv

UpdatedNov 24, 2017
Jupyter Notebook

akr /pdftimestamp

Star6

pdftimestamp add a document timestamp signature for a PDF file.

java pdf signature pdfbox sign timestamp pades ltv

UpdatedDec 10, 2021
Java

ARUNJOGLE /clvpulseplus

Star4

CLV PULSE - A DYNAMIC CUSTOMER LIFETIME VALUE PREDICTOR MODEL USING MACHINE LEARNING

dynamic-programming clv ltv customersegmentation

UpdatedNov 13, 2024
JavaScript

sadikkuzu-mba /SegmentationPLSQL

Star2

Segmentation test plsql

test plsql segmentation ltv segmentation-test-plsql

UpdatedOct 8, 2018
PLSQL

MartinCastroAlvarez /django-data-analytics

Star2

Data Analytics, PnL, LTV & retention analysis with Django

visualization d3 django analytics rest-api data-analysis d3js ltv beautifulsoup4

UpdatedApr 14, 2022
Python

nikita-data /Unit_economics_projects

Star1

unit economics & cohort analysis projects

python statistics math numpy conversion eda data-visualization seaborn scipy data-analysis segmentation matplotlib roi hypothesis-testing cac ltv retention-rate unit-economics churn-rate create-function

UpdatedMay 28, 2024
Jupyter Notebook

nikita-data /EDA_projects

Star1

Exploratory data analysis projects

python statistics math numpy plotly eda data-visualization seaborn scipy data-analysis regular segmentation matplotlib roi hypothesis-testing cac ltv folium-maps unit-economics

UpdatedMay 28, 2024
Jupyter Notebook

bdbacik /Predicting-Customer-Churn

Star1

Machine learning model to predict churn of credit card customers. Demonstration of novel XGBoost configuration for noisy, imbalanced data.

python sklearn xgboost recall roi ltv false-positive tomek-link-elimination

UpdatedMar 4, 2021
Jupyter Notebook

oguzerdo /flo-cltv-prediction

Star1

FLO wants to determine a roadmap for its sales and marketing activities.

data-science segmentation ltv cltv customer-segmentation cltv-prediction

UpdatedSep 18, 2022
Jupyter Notebook

APAC-GOLD /BusinessAcquisitions

Star0

Python Program to Calculate Which Roles a Business Needs to Grow and How Many FTEs are in a Particular Role. To Calculate "Customer Lifetime Value." To Test Logic Over Time. Ultimately, to Optimise a Business. This information is relevant to Business Acquisitions, New Business Owners, and Business Owners Looking to Expand.

saas python3 finance-application ltv businessoptimization

UpdatedJun 16, 2024

thiagonazario /Project_AnaliseDespesasMarketing_Cohort

Star0

💻 Neste Projeto com Análise de Cohort dos Usuários, meu foco está em desvendar padrões através do comportamento dos usuários, registros de acesso e despesas. Exploro dados de janeiro de 2017 a dezembro de 2018, compreendendo os dados, pontos de conversão e dedicando identificar o valor do cliente para otimizar as despesas. 📈💡

data-science framework exploratory-data-analysis jupyter-notebook data-visualization seaborn data-analysis boxplot cac ltv romi cohort-analysis roi-analysis