Python GitHub solutions to be combined

Cerrado Publicado hace 11 meses Pagado a la entrega
Cerrado Pagado a la entrega

I am looking to have several Python GitHub solutions tied together into one tool with some modifications to suit my use case. I am looking to modify a recommendation engine to use different inputs. I am open on pricing & solutions (this is fixed price with 3 phases).

Project Overview:

The goal of this project is to develop a recommendation engine for upselling & cross-selling products & services. The recommendation engine will utilize customer data, product information, & association analysis to generate personalized recommendations for customers.

Business Requirements:

1. Upsell & Cross-sell: The recommendation engine should identify opportunities for upselling & cross-selling products & services based on features, workload bundles, customer profiles & their purchase history.

2. Personalization: The recommendations should be personalized to each customer, taking into account their preferences, past interactions, & demographic information.

3. Data Integration: The system should integrate customer data, product information, & feedback to improve the accuracy & relevance of the recommendations.

4. Enhanced Customer Experience: The recommendation engine should enhance the overall customer experience by providing valuable & relevant product suggestions.

5. Easy Integration: The solution should be easy to integrate into existing systems & workflows, allowing seamless implementation & utilization.

Technical Requirements:

1. Data Preparation: The customer data, product information, & feedback need to be processed & prepared for analysis. This includes cleaning, formatting, & organizing the data into a suitable format for recommendation algorithms.

2. Association Analysis: The solution should leverage association analysis techniques to identify patterns & associations between customer preferences & product/service attributes. This analysis will help uncover potential upsell & cross-sell opportunities.

3. Machine Learning: The recommendation engine should utilize machine learning algorithms to generate personalized recommendations based on customer profiles & historical data.

4. Visualization: The results of the association analysis & recommendation generation should be visualized in an intuitive & interactive manner to aid in understanding & decision-making.

5. Integration with Existing Systems: The solution should provide APIs or other means of integration to seamlessly connect with existing customer databases & systems.

6. Scalability: The system should be able to handle a large volume of customer data & adapt to increasing data sizes as the customer base grows.

Tool sets for consideration:

1. Seasonality & Trends: Facebook's Prophet: A tool for time series forecasting & trend analysis. facebook/prophet

2. Customer Satisfaction & NPS Scores:

• Net Promoter Score (NPS) Calculation: A Python library for calculating NPS scores. ggunson/nps-python

3. Customer Journey Mapping:

• Customer Journey Python Library: A Python library for visualizing & analyzing customer journey data. outliercz/customer-journey-python

4. User Behavior Analytics:

• Cohort Analysis: A Python library for conducting cohort analysis on user behavior data. harishsg/cohort-analysis

5. Competitive Pricing Analysis: Price Comparison Tool: A Python script for scraping & comparing prices from different websites. estebanpw/price_comparison_tool

6. Customer Segmentation: Customer Segmentation with RFM Analysis: A Python script for segmenting customers based on RFM (Recency, Frequency, Monetary) analysis. rajat10/rfm-segmentation

7. Customer Lifetime Value (CLV): Customer Lifetime Value Calculation: A Python library for calculating CLV based on historical sales data. StevensHumans/clv-prediction

8. Competitor Analysis: Web Scraping Competitor Data: A Python script for scraping competitor data from websites. c-w-m/web-scraping

9 Gephi ([login to view URL])

10. Orange:

• [login to view URL]

Python Arquitectura de software Django PHP JavaScript

Nº del proyecto: #36729985

Sobre el proyecto

36 propuestas Proyecto remoto Activo hace 10 meses

36 freelancers están ofertando un promedio de $415 por este trabajo

helmot

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8.3
umg536

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7.3
pvsysgroupinc

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6.8
datascientist90

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dvcontact

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arkcrew1

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