CRM (Customer Relationship Management) Analytics

Customer Segmentation with RFM (Recency, Frequency, Monetary) Analysis using FLO's Dataset

GitHub Repository:

Business Problem

FLO, an online shoe store, wants to segment its customers and determine marketing strategies according to these segments. To this end, the behaviors of the customers will be defined and groups will be formed according to the clusters in these behaviors.

Predictive Segments

Frequency
5 can't loose them loyal customers champions
4 at risk
3 need attention potential loyalists
2 hibernating about to sleep
1 promising new customers
  1 2 3 4 5
Recency Score
Dataset Story

The dataset consists of the information obtained from the past shopping behaviors of customers who made their last purchases from FLO as OmniChannel (both online and offline shopper) in 2020-2021.

Variables
  • master_id: Customer ID
  • order_channel: Shopping platform (Android, ios, Desktop, Mobile, Offline)
  • last_order_channel: The channel where the most recent purchase was made
  • first_order_date: Customer's first order date
  • last_order_date: Customer's last order date
  • last_order_date_online: Customer's last offline order date
  • last_order_date_offline: Customer's last online order date
  • order_num_total_ever_online: The total number of orders made by the customer online
  • order_num_total_ever_offline: The total number of orders made by the customer offline
  • customer_value_total_ever_offline: The total price paid by the customer for offline orders
  • customer_value_total_ever_online: The total price paid by the customer for online orders
  • interested_in_categories_12: List of categories the customer has shopped in the last 12 months
Requirements
  • pandas==1.5.1

CLTV (Customer Lifetime Value) Prediction with BG-NBD and Gamma-Gamma using FLO's Dataset

GitHub Repository:

Business Problem

FLO wants to set a roadmap for sales and marketing activities.

In order for the company to make a medium-long-term plan, it is necessary to estimate the potential value that existing customers will provide to the company in the future.

Dataset Story

The dataset consists of the information obtained from the past shopping behaviors of customers who made their last purchases from FLO as OmniChannel (both online and offline shopper) in 2020-2021.

Variables
  • master_id: Customer ID
  • order_channel: Shopping platform (Android, ios, Desktop, Mobile, Offline)
  • last_order_channel: The channel where the most recent purchase was made
  • first_order_date: Customer's first order date
  • last_order_date: Customer's last order date
  • last_order_date_online: Customer's last offline order date
  • last_order_date_offline: Customer's last online order date
  • order_num_total_ever_online: The total number of orders made by the customer online
  • order_num_total_ever_offline: The total number of orders made by the customer offline
  • customer_value_total_ever_offline: The total price paid by the customer for offline orders
  • customer_value_total_ever_online: The total price paid by the customer for online orders
  • interested_in_categories_12: List of categories the customer has shopped in the last 12 months
Requirements
  • lifetimes==0.11.3
  • matplotlib==3.7.1
  • pandas==1.5.1