Mapping Visitors’ Behavior to Business Goals through Click Stream Analysis
Click Stream Analysis
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Transcript of Click Stream Analysis
Bisen Vikrantsingh
Kodamasimham Pridhvi
Vaibhav Singh Rajput
1
Intro
Dataset
Analysis
Approach
2
The goal To design models
To support web-site personalization and
To improve the profitability of the site by increasing customer response.
3
SET - I
Session, cookies ID, date, time
Customer ID, visit count, gender, age, martial
status,Income, occupation, home market value , howDidYouHearAboutUs, HowDidYouFindUs, U.S. state
Page View View count of 80+ different
pages/product, last page view, assortment path with level
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SET - II
Session ID, date, time
Customer ID, visit count, gender, age, martial
status,Income, occupation, home market value , howDidYouHearAboutUs, HowDidYouFindUs, U.S. state
Order Date,time, amount, tax, discount,
shipping amount, promotion code
Questions - When given a set of page views,will the visitor view another page on the site or leave?
which product brand will the visitor view in the remainder of the session?
characterize heavy spenders
characterize killer pages
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Stage-I Data cleaning
Filtering attributes
Load into RDBMS
Stage-II Classification of users
RFV analysis
Classify users into potential or not
Decision tree algorithm
Clustering of products
Dimension to be consider Product, age group, location, purchase amount
Fuzzy clustering
Find correlation
Correlation between {advertise,gender,income,brand} and {product view/purchase}
Stage-III Answer question mention in previous slides 6
Technology Stack:• Python• MYSQL
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