📌 In this section, we will perform customer segmentation using pyspark in the Flo dataset.
📌 FLO, an online shoe store, wants to segment its customers and determine marketing strategies according to these segments. For this, the behaviors of the customers will be defined and groups will be formed according to the clusters in these behaviors.
📌 The dataset consists of information obtained from the past shopping behaviors of customers who made their last purchases on OmniChannel (both online and offline) in 2020 - 2021.
📌 20,000 observations, 13 variables
master_id: Unique client number
order_channel : Which channel of the shopping platform is used (Android, ios, Desktop, Mobile, Offline)
last_order_channel : The channel where the last purchase was made
first_order_date : The date of the first purchase made by the customer
last_order_date : The date of the last purchase made by the customer
last_order_date_online : The date of the last purchase made by the customer on the online platform
last_order_date_offline : The date of the last purchase made by the customer on the offline platform
order_num_total_ever_online : The total number of purchases made by the customer on the online platform
order_num_total_ever_offline : Total number of purchases made by the customer offline
customer_value_total_ever_offline : The total price paid by the customer for offline purchases
customer_value_total_ever_online : The total price paid by the customer for their online shopping
interested_in_categories_12 : List of categories the customer has shopped in the last 12 months
store_type : It represents 3 different companies. If the person who shopped from company A made it from company B, it was written as A, B.