Predict how much GStore customers will spend. The project is built to participate in the competition on Kaggle.com
The 80/20 rule has proven true for many businesses–only a small percentage of customers produce most of the revenue. As such, marketing teams are challenged to make appropriate investments in promotional strategies.
In this project, we are going to analyze a Google Merchandise Store (also known as GStore) customer dataset to predict revenue per customer. Hopefully, the outcome will be more actionable operational changes and a better use of marketing budgets for those companies who choose to use data analysis on top of GA data.
The prediction is evaluated on the root mean squared error. RMSE is defined as:
where y hat is the natural log of the predicted revenue for a customer and y is the natural log of the actual summed revenue value plus one.
- You will need to download train.csv and test.csv. These contain the data necessary to make predictions for each fullVisitorId listed in sample_submission.csv. All information below pertains to the data in CSV format.
Download here (https://www.kaggle.com/c/10038/download-all)
Both train.csv and test.csv contain the columns listed under Data Fields. Each row in the dataset is one visit to the store.
We are predicting the natural log of the sum of all transactions per user. For every user in the test set, the target is:
train.csv - the training set
test.csv - the test set
sampleSubmission.csv - a sample submission file in the correct format. Contains all fullVisitorIds in test.csv.
fullVisitorId - A unique identifier for each user of the Google Merchandise Store.
channelGrouping - The channel via which the user came to the Store.
date - The date on which the user visited the Store.
device - The specifications for the device used to access the Store.
geoNetwork - This section contains information about the geography of the user.
sessionId - A unique identifier for this visit to the store.
socialEngagementType - Engagement type, either "Socially Engaged" or "Not Socially Engaged".
totals - This section contains aggregate values across the session.
trafficSource - This section contains information about the Traffic Source from which the session originated.
visitId - An identifier for this session. This is part of the value usually stored as the utmb cookie. This is only unique to the user. For a completely unique ID, you should use a combination of fullVisitorId and visitId.
visitNumber - The session number for this user. If this is the first session, then this is set to 1.
visitStartTime - The timestamp (expressed as POSIX time).
Some fields were censored to remove target leakage. The major censored fields are listed below.
hits - This row and nested fields are populated for any and all types of hits. Provides a record of all page visits.
customDimensions - This section contains any user-level or session-level custom dimensions that are set for a session. This is a repeated field and has an entry for each dimension that is set.
totals - Multiple sub-columns were removed from the totals field.