This document discusses Gilt Groupe's use of MongoDB for real-time ecommerce analytics. It describes two key uses: 1) capturing product page view data in real-time to calculate scores to determine which products to feature, and 2) using Node.js to capture site traffic data and visualize it with Hummingbird. The system captures data, runs map-reduce to analyze it, and updates transactional systems to improve conversions and optimize product promotions.

1. Real Time Ecommerce Analytics at Gilt Groupe Michael Bryzek, CTO & Founder Michael Nutt, Senior Engineer Mongo SF - April 30, 2010 We’re hiring: michael@gilt.com www.gilt.com/invite/michael

2. What is Gilt Groupe? The world’s best brands at up to 70% off Sales start every day at noon Simple, luxurious online experience Relentless focus on the customer . . . A fast growing young company

4. What does noon look like in Tech?

5. What does noon look like?

6. MongoDB at Gilt Groupe Real time analytics is a sweet spot for MongoDB Two production examples we’ll share today at Gilt Groupe: Selecting product to sell based on real time data Hummingbird: Real time visualization of site traffic

7. Using MongoDB for Real Time Analytics Goal: Improve conversion of our gifts section (www.gilt.com/gifts) by ensuring good products are being promoted at the right time Challenge: High traffic makes it hard to collect and analyze data in a scalable and fast way Approach: Capture data in real time in MongoDB Analyze w/ Map Reduce Update txn systems Repeat

9. Each page view receive a list of every item on the page and its position via AJAX

11. Step 2: Map Calculate a score for each item based on page views, conversion, inventory, and merchandising input m = function(){ [snip] if ( hourly.visits > 0 && this.quantity_sold > 0 ) { var rate = this.quantity_sold / hourly.visits; points = parseInt(100*rate); v += points; explanation += "Conversion rate of " + points + "% ”; } else if ( hourly.visits == null || hourly.visits == 0 ) { v += 500; explanation += "Product has never been seen (500 points). "; } [snip] emit( { gift_product_look_guid : this._id }, { score : v, explanation : explanation}}); }

12. Step 2: Reduce Reduce is a passthrough r = function( pid , values ){ return values[0]; } Map Reduce run every 15 minutes via CRON – results stored in a collection named “scores” res = db.gift_product_looks.mapReduce( m , r , { out : "scores" } );

14. Send “scores” collection back to our primary data center, storing latest scores in our primary relational database

16. Tracking Pixels /tracking.gif?events=&prop1=women&server=www.gilt.com&products=&pageName=sales%3A+women&channel=sale&prop4=sale+category+page&u=http%3A%2F%2Fwww.gilt.com%2Fsale%2Fwomen&guid=418237ca-2bc6-932e-84c2-d4f02d9fd5bf&gen=f&uid=25423567&cb=443460396

17. Omniture GILT Data Warehouse Users

18. Omniture 24 hours later... GILT Data Warehouse Users

19. Node.js Asynchronous, evented web framework http://nodejs.org

20. var mongo = require(’lib/mongodb’); var db = new mongo.Db('hummingbird', new mongo.Server('localhost', 27017, {}), {}); db.createCollection('visits', function(err, collection) { db.collection('visits', function(err, collection) { collection.insert(env); }); });

21. DEMO