Sailthru's smart data hackathon challenge.
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README.md

Sailthru Data Challenge

Background

There are lots of awesome APIs to play with at every hackathon. We wanted to give you something different: A huge set of data for you to hack on. The hack can be anything: a tool, an algorithm, a visualization, anything that our data can power. Mine it for whatever you’d like.

Prizes

  • The Pixel
  • A guest post on the Sailthru engineering blog

Judging

We'll be taking a look at the following criterion:

  • Easy of use
  • Creativity
  • Insightfulness

Data

The data can be located here: http://tinyurl.com/sailthru-hack-data

The data is gziped. When you extract it you will find a serialized JSON file.

Extracting the Data and Importing into Mongo

tar -xzvf hackathon_data.tar.gz
mongoimport --collection hackathon --file hackathon_data.json

You can import the data into MongoDB by running: mongoimport --type json --file hackathon_data.json --collection hackathon

You can then use the MongoDB Shell, or your favorite client library to hack our data.

Schema

‘_id’: Sequential numeric ids

‘browser’: The browsers a user opens email with

‘browser_site’: The browsers a user opens links with

‘click_count’: Total link clicks the user has made

‘click_time’: Time of user’s last click

‘daily_click’: YYMMDD, number of clicks on that day

‘daily_message’: YYMMDD, number of emails the user received that day

‘daily_open’: YYMMDD, the number of email opens the user made that day

‘daily_pv’: YYMMDD, the number of pageviews a user generates that day

‘email_hour’: Number of opens within that GMT hour

‘geo’ : Email location user opened email from’, number of opens from that location

‘geo.count’ : Total number of email opens with geo-data’

‘geo.country’ : Total number of email opens per country

‘geo.state : Total number of email opens per state

‘geo.zipcode’ : Total number of email opens per zipcode

‘horizon’: Number of pageviews on pages with that interest tags. 

‘horizon_count’: Total pageviews

‘horizon_month’ : Total pageviews per month per tag. YYYYMM format for months

‘horizon_time’ : Last pageview date time

‘lifetime_click’ : Total clicks for the user

‘lifetime_message’ : Total email sent to the user

‘mobile_email_hour" : Mobile email opens per GMT hour bucket

‘mobile_site_hour" : Mobile website visits per GMT hour bucket

‘open_count’ : Total open count

‘open_time’ : Last open time

‘signup_time’ : When the user signs up for emails and on-site tracking

‘site_hour’ : Website visits per GMT hour bucket

‘urls_count’ : Total number of dynamic urls

Submitting

To submit entries make a pull request to: https://github.com/zencephalon/sailthru-data-challenge

Legal

Thank you for taking part in the Sailthru Challenge.

As part of the Sailthru Challenge, you will be able to download data from the link we provide. This data is Sailthru's Confidential Information.

By downloading this data, you agree that you will treat this information as confidential, and proprietary to Sailthru, and that you will not use the Confidential Information other than for this event. In addition, you shall not copy, disclose, publish, share or otherwise reveal any of the Sailthru's Confidential Information with any other party whatsoever, except as authorized by law, or with the specific prior written authorization of Sailthru. You agree not to use such Confidential Information for your own benefit or for the benefit of any other person or business entity.

You acknowledge and agree that any disclosure of the Confidential Information except as provided here may cause serious and irreparable damage to Sailthru for which there may be no adequate remedy at law. Without limiting Sailthru's rights and remedies which are otherwise available, Sailthru will be entitled to equitable relief including, without limitation, an injunction, restraining order or specific performance if you breach this agreement in any way.