Cluster Analysis

Depending on the reasons for a person to be online, consumers can be clustered into homogeneous groups.

The various attributes used in CLUSTER Analysis have been coded as follow:

V1: News or Information
V2: Websites of company regarding product
V3: Travel and leisure
V4: Spent time in social media sites like Facebook
V5: Online shopping sites such as Flipkart
V6: Education related sites
V7: Official works, email

The three resulting clusters can be described as follow:

Cluster 1: internet users who are Leisure Hunter (relatively high values on variables V1, V4 and V5)
Cluster 2: internet users who are Regular Web Person (medium values on the variables)
Cluster 3: internet users who are Dedicated Surfer (relatively high values on variables V2, V3 and V6)

Users can further be clustered on the basis of factors which influence them while making an online purchase:-

The various attributes used in CLUSTER Analysis have been coded as follow:

V1: Brand Name
V2: Service delivery time
V3: Website Content
V4: Recommendation by friends
V5: Online Ads – posters/banners
V6: Online reviews by users of product
V7: Ease of payment and security

The four resulting clusters can be described as follow:

Cluster 1: The Surgical Shopper (relatively high values on variables V4 and V6)
Cluster 2: The Enthusiast Shopper (relatively high values on variables V1, V2, V3, V5, and V7)
Cluster 3: The Casual Shopper (relatively high values on variables V1, V2, V3, and V7)
Cluster 4: The Reluctant Shopper (relatively low values on all the variables)