Twenty-first century retailers are facing an increasingly challenging and competitive environment. Given the rise of ecommerce and pressure on margins, retailers are looking for innovative services as well as ways to improve customer service, loyalty and engagement. Leading organizations in retail are choosing MongoDB because of its ability to help them compete, providing superior customer experience and accelerated time to market. In this webinar, hear how MongoDB enables retailers to develop: Enriched Product Catalog Management Distribution and Logistics Management Solutions Real time Analysis of Customer Behavior The use cases are specific to retail, but the patterns of usage - agility, scale, and global distribution - will be applicable across many industries.

1. #mongodbretail
Senior Solutions Architect, MongoDB Inc.

2. “The art of commerce is to buy goods for
5 when they are worth 10 and sell for 10
what is worth 5”

3. 3
• Norberto Leite
• Solutions Architect
– Technical Account Manager
– Engineer
• Barcelona, Spain
• norberto@mongodb.com
• @nleite
Presenter Notes

4. 4
• Introduction
• Retail Challenges
• Why MongoDB
• Common Use Cases
• References
Agenda

5. Introduction

6. 6
MongoDB
The leading NoSQL database
Document
Database
Open-
Source
General
Purpose

7. 7
To provide the best database for how we build and
run apps today
MongoDB Vision
Build
–New and complex data
–Flexible
–New languages
–Faster development
Run
–Big Data scalability
–Real-time
–Commodity hardware
–Cloud

8. 8
Agile
MongoDB Overview
Scalable

9. 9
4,000,000+4,000,000+
MongoDB DownloadsMongoDB Downloads
100,000+100,000+
Online Education RegistrantsOnline Education Registrants
20,000+20,000+
MongoDB User Group MembersMongoDB User Group Members
20,000+20,000+
MongoDB Days AttendeesMongoDB Days Attendees
15,000+15,000+
MongoDB Management Service (MMS) UsersMongoDB Management Service (MMS) Users
Global Community

10. 10
Big Data Content Mgmt & Delivery Mobile & Social
MongoDB Solutions

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• 10 of the Top Financial Services Institutions
• 10 of the Top Electronics Companies
• 10 of the Top Media and Entertainment
Companies
• 8 of the Top Retailers
• 6 of the Top Telcos
• 5 of the Top Technology Companies
• 4 of the Top Healthcare Companies
Fortune 500 & Global 500

12. Retail Challenges

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• Old School
– Evolving Landscape
– Customer Loyalty
– New Competitors
– New Markets
• Avant-garde
– Seamless Experience
– Online + Offline
– Buying Patterns
– Predict Trends
Challenges

14. http://www.blendwerk-freiburg.de/wp-content/uploads/2010/08/jai-vu-jai-lu-kukuxumusu-ovolution.jpg
Evolving Landscape

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• Extended Offering
• Home delivery
• Online only supermarkets
– Lots of new companies
– Lots of traditional retailers populating the web
• Physical stores as complements
– Show rooms
– Pick up locations
Evolving Landscape

16. http://s.wsj.net/media/cards_E_20111020111733.jpg
Customer Loyalty

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• Understand your customer
• “Customize” what customer needs and wants
– And when he want’s it!
• Reward the your “fans”
• Make sure everyone knows they have been
rewarded
– Gamification is a strong powerful driver!
– points + points + points
Customer Loyalty

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• How easy it is nowadays to open a web shop?
• How many are approaching a need that you do
not attend?
• Is your market share growing or shrinking?
– Time to get a Vietnamese translator ?
• How fast can I react to habits and perception
change ?
New Competitors and Markets

19. http://www.sinbadesign.com/wp-content/uploads/2011/07/Tesco-Homeplus-Subway-Virtual-Store-in-South-
Korea01.jpg
Seamless Experience

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• It’s all about knowing your Customer
• Make better customized offers
• Avoid useless promotions
– Not valuable for your customers
– Degradation of your brand
• Make use of the network effect
• Analytics anyone?
Buying Patterns + Trends Prediction

21. Why MongoDB?

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• Flexible Datastore
• Horizontal Scalability
• Multi Platform
• Polyglot
• Cost Efficient
• Large Community
• Talent War?
MongoDB = Good Stuff

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RDBMS
Flexible Datastore
MongoDB
{
_id : ObjectId("4c4ba5e5e8aabf3"),
employee_name: "Dunham, Justin",
department : "Marketing",
title : "Product Manager, Web",
report_up: "Neray, Graham",
pay_band: “C",
benefits : [
{ type : "Health",
plan : "PPO Plus" },
{ type : "Dental",
plan : "Standard" }
]
}

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Horizontal Scalability
Auto-Sharding
• Increase capacity as you go
• Commodity and cloud architectures
• Improved operational simplicity and cost visibility

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Multi Platform
http://images7.alphacoders.com/333/333230.jpg

26. Polyglot

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Shell
Command-line shell for
interacting directly with
database
Polyglot
Drivers
Drivers for most popular
programming languages and
frameworks
> db.collection.insert({product:“MongoDB”,
type:“Document Database”})
>
> db.collection.findOne()
{
“_id” : ObjectId(“5106c1c2fc629bfe52792e86”),
“product” : “MongoDB”
“type” : “Document Database”
}
Java
Python
Perl
Ruby
Haskell
JavaScript

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Developer/Ops Savings
•Ease of Use
•Agile development
•Less maintenance
Hardware Savings
•Commodity servers
•Internal storage (no SAN)
•Scale out, not up
Software/Support Savings
•No upfront license
•Cost visibility for usage growth
Cost Efficient
DB Alternative

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Cost Efficient
Dev. and Admin
Compute – Scale-Up Servers
Storage - SAN
Dev. and Admin
Compute – Scale-Up Servers
Storage - SAN

30. http://i.smimg.net/13/33/usain-bolt_1.jpg
Race forTalent

31. Common Use Cases

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• Rich Catalog Management
• Customer Data Management
• Customer Interaction and Sentiment Analysis
• Digital Coupons
• Inventory Management
• Demand Chain Optimization
• Real-Time Price Optimization
Use Cases

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• Flexibility
– External + Internal
information
– Evolving Product Data
– Different Buying
Process
– Funnels
– Promotions &&
Campaigns
– Hierarchy of Products
and Sections
Rich Catalog Management

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• Multiple Geographies
• Online + Offline
• Engagement Process
• Preferences
• Permissions
• Privacy and other
regulation
Customer Data Management

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• Realtime analytics
– Aggregation Framework
– MapReduce
• KPI calculation
– CTR
– Bounce Rates
– Conversion Rates
• Automation of Price
Margins
• DSL
Realtime Price Optimiation
Optimum Price

36. References

37. 37
MongoDB enables Gilt to roll out new revenue-
generating features faster and cheaper
Case Study
Problem Why MongoDB Results
• Monolithic Postgres
architecture expensive
to scale
• Limited ability to add
new features for
different business silos
• Spiky server loads
• Dynamic schema makes it
easy to build new features
• Alignment with SOA
• Cost-effective, horizontal
scaling
• Easy to use and maintain
• Developers can launch
new services faster, e.g.,
customized upsell emails
• Stable, sub-ms
performance on
commodity hardware
• Reduced complexity
yields lower overhead

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Serves variety of content and user services on
multiple platforms to 7M web and mobile users
Case Study
Problem Why MongoDB Results
• MySQL reached scale
ceiling – could not cope
with performance and
scalability demands
• Metadata management
too challenging with
relational model
• Hard to integrate
external data sources
• Unrivaled performance
• Simple scalability and
high availability
• Intuitive mapping
• Eliminated 6B+ rows of
attributes – instead
creates single document
per user / piece of content
• Supports 115,000+
queries per second
• Saved £2M+ over 3 yrs.
• “Lead time for new
implementations is cut
massively”
• MongoDB is default
choice for all new
projects

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Delivers agile automated supply chain service to
retailers powered by MongoDB
Case Study
Problem Why MongoDB Results
• RDBMS poorly-
equipped to handle
varying data types (e.g.,
SKUs, images)
• Inefficient use of
storage in RDBMS (i.e.,
90% empty columns)
• Complex joins degraded
performance
• Document-oriented model
less complex, easier to
code
• Single data store for
structured, semi-structured
and unstructured data
• Scalability and availability
• Analytics with MapReduce
• Decreased supplier
onboard time by 12x
• Grew from 400K records to
40M in 12 months
• Significant cost reductions
on schema design time,
ongoing developer effort,
and storage usage

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Social e-commerce application built on MongoDB
offers 100M+ products from over 30K brands
Case Study
Problem Why MongoDB Results
• MySQL could not
accommodate growth
• Significant optimization
required to tune MySQL
performance
• Database maintenance
inhibited development
• Flexible data model to
handle varying product
attributes
• Scalability for global reach
• Ease of maintenance
• Consistent performance
even when adding data
and new features
• Boosted developer
productivity
• Scaled from 5M to
100M products with
minimal work
• Decreased product
import time by 90%

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Leading Organizations Rely on MongoDB

42. How do we help?

43. 43
MongoDB Business Value
Enabling New Apps Better Customer Experience
Lower TCOFaster Time to Market

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MongoDB Products and Services
Training
Online and In-Person for Developers and Administrators
MongoDB Management Service (MMS)
Cloud-Based Suite of Services for Managing MongoDB Deployments
Subscriptions
MongoDB Enterprise, MMS (On-Prem), Professional Support,
Commercial License
Consulting
Expert Resources for All Phases of MongoDB Implementations

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For More Information
Resource Location
MongoDB Downloads mongodb.com/download
Free Online Training education.mongodb.com
Webinars and Events mongodb.com/events
White Papers mongodb.com/white-papers
Case Studies mongodb.com/customers
Presentations mongodb.com/presentations
Documentation docs.mongodb.org
Additional Info info@mongodb.com
Resource Location