Dataset: Online Customers Intention

About this Dataset

Online Customers Intention

Response variable: Revenue

Scenario

Online shopper's purchase intention is a difficult problem to predict, given the very large number of factors that can potentially affect an individual's decision to buy or not buy an item. It gets worse because most online stores can only obtain analytics information to facilitate such predictions, but not full-fledged individual-level information. Nevertheless, determining primary factors related to the site visits which lead to an efficacious transaction occurring enables retailers to maximize site layout and marketing campaigns, in an attempt to
generate increased levels of sales.

This data set contains entries of a high volume of website visits, and the corresponding analytics information. The task is to forecast the value for the Revenue variable, with the models that can be applied to classification problems. Determine which features have the highest indication of a user's buying intention.

Attributes' Description
Administrative: Number of administrative pages visited by the user

Administrative_Duration: Length of time spent on administrative pages, measured in seconds

Informational: Number of informational pages visited by the user

Informational_Duration: Length of time spent on informational pages, measured in seconds

ProductRelated: Number of product related pages visited by the
user

ProductRelated_Duration: Length of time spent on product related pages, measured in seconds

BounceRates: Proportion of users who leave the site after only
interacting with a single page

ExitRates: Proportion of views to a particular page that were
the last in a user’s session

PageValues: Average number of pages visited by a user prior to
a transaction taking place

SpecialDay: Closeness of the visit to a notable day of the year
(e.g., Christmas Day, Mother’s Day, Valentine’s
Day)

Month: Month in which the site visit took place

OperatingSystems: Operating system of the user
Browser: Browser of the user

Region: Geographical region of the user

TrafficType: Traffic type of the user

VistorType: Whether the user is new or returning

Weekend: Whether the site visit took place on a weekend

Revenue: Whether the site visit resulted in a transaction
taking place

Tables

Online Shoppers Intention

@kaggle.aritra100_online_customers_intention.online_shoppers_intention

315.36 KB
12330 rows
18 columns


CREATE TABLE online_shoppers_intention (
  "administrative" BIGINT,
  "administrative_duration" DOUBLE,
  "informational" BIGINT,
  "informational_duration" DOUBLE,
  "productrelated" BIGINT,
  "productrelated_duration" DOUBLE,
  "bouncerates" DOUBLE,
  "exitrates" DOUBLE,
  "pagevalues" DOUBLE,
  "specialday" DOUBLE,
  "month" VARCHAR,
  "operatingsystems" BIGINT,
  "browser" BIGINT,
  "region" BIGINT,
  "traffictype" BIGINT,
  "visitortype" VARCHAR,
  "weekend" BOOLEAN,
  "revenue" BOOLEAN
);