Customer Segmentation for the Implementation of New Marketing Campaigns
GOAL
Customer segmentation is crucial for various marketing strategies, as it allows for targeted approaches based on specific customer groups, enhancing precision and effectiveness in reaching the intended audience.
In addition to simply having the data, one must also know how to extract information from it. A company provides its customers' information for segmentation to enhance the implementation of marketing strategies.
PROJECT DESCRIPTION
The project included exploratory data analysis (EDA), preparing the data, grouping data points, and understanding these groups. The clustering utilized the KMeans algorithm, validated through the silhouette score. Visualizing and interpreting these clusters yielded valuable insights for focused marketing efforts and product improvement. This approach is adaptable to other customer datasets, making it a flexible tool within the retail sector.
EXPLORATORY DATA ANALYSIS
An integral exploration of the initial data is vital for comprehending the dataset's arrangement, attributes, and possible anomalies prior to advancing into subsequent analysis or modeling stages.
UNDERSTANDING THE CLUSTERS
The identified clusters offer a distinct view of various customer groups delineated by their income and spending patterns. A simplified summary is presented below:
Low income, Low spending
ECONOMY CUSTOMERS
High income,
Low spending
THRIFTY CUSTOMERS
Medium income, Med. spending
MID-RANGE CUSTOMERS
Low income,
High spending
BIG CUSTOMERS
High income,
High spending
PREMIUM CUSTOMERS
Another valuable source of information is to classify customers according to their age and spending score, using the clusters previously identified.
ECONOMY CUSTOMERS
OLDER
THRIFTY CUSTOMERS
MIDDLE AGE
MID-RANGE CUSTOMERS
WIDE AGE RANGE
BIG CUSTOMERS
YOUNG
PREMIUM CUSTOMERS
MIDDLE AGE
DASHBOARD WEB APPLICATION