Webinar: Expanding Retail Frontiers with MongoDB
 

Webinar: Expanding Retail Frontiers with MongoDB

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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 ...

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.

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 Webinar: Expanding Retail Frontiers with MongoDB Webinar: Expanding Retail Frontiers with MongoDB Presentation Transcript

  • #mongodbretail Senior Solutions Architect, MongoDB Inc.
  • “The art of commerce is to buy goods for 5 when they are worth 10 and sell for 10 what is worth 5”
  • 3 • Norberto Leite • Solutions Architect – Technical Account Manager – Engineer • Barcelona, Spain • norberto@mongodb.com • @nleite Presenter Notes
  • 4 • Introduction • Retail Challenges • Why MongoDB • Common Use Cases • References Agenda
  • Introduction
  • 6 MongoDB The leading NoSQL database Document Database Open- Source General Purpose
  • 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 Agile MongoDB Overview Scalable
  • 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 Big Data Content Mgmt & Delivery Mobile & Social MongoDB Solutions
  • 11 • 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
  • Retail Challenges
  • 13 • Old School – Evolving Landscape – Customer Loyalty – New Competitors – New Markets • Avant-garde – Seamless Experience – Online + Offline – Buying Patterns – Predict Trends Challenges
  • http://www.blendwerk-freiburg.de/wp-content/uploads/2010/08/jai-vu-jai-lu-kukuxumusu-ovolution.jpg Evolving Landscape
  • 15 • 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
  • http://s.wsj.net/media/cards_E_20111020111733.jpg Customer Loyalty
  • 17 • 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
  • 18 • 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
  • http://www.sinbadesign.com/wp-content/uploads/2011/07/Tesco-Homeplus-Subway-Virtual-Store-in-South- Korea01.jpg Seamless Experience
  • 20 • 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
  • Why MongoDB?
  • 22 • Flexible Datastore • Horizontal Scalability • Multi Platform • Polyglot • Cost Efficient • Large Community • Talent War? MongoDB = Good Stuff
  • 23 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" } ] }
  • 24 Horizontal Scalability Auto-Sharding • Increase capacity as you go • Commodity and cloud architectures • Improved operational simplicity and cost visibility
  • 25 Multi Platform http://images7.alphacoders.com/333/333230.jpg
  • Polyglot
  • 27 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
  • 28 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
  • 29 Cost Efficient Dev. and Admin Compute – Scale-Up Servers Storage - SAN Dev. and Admin Compute – Scale-Up Servers Storage - SAN
  • http://i.smimg.net/13/33/usain-bolt_1.jpg Race forTalent
  • Common Use Cases
  • 32 • Rich Catalog Management • Customer Data Management • Customer Interaction and Sentiment Analysis • Digital Coupons • Inventory Management • Demand Chain Optimization • Real-Time Price Optimization Use Cases
  • 33 • Flexibility – External + Internal information – Evolving Product Data – Different Buying Process – Funnels – Promotions && Campaigns – Hierarchy of Products and Sections Rich Catalog Management
  • 34 • Multiple Geographies • Online + Offline • Engagement Process • Preferences • Permissions • Privacy and other regulation Customer Data Management
  • 35 • Realtime analytics – Aggregation Framework – MapReduce • KPI calculation – CTR – Bounce Rates – Conversion Rates • Automation of Price Margins • DSL Realtime Price Optimiation Optimum Price
  • References
  • 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
  • 38 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
  • 39 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
  • 40 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%
  • 41 Leading Organizations Rely on MongoDB
  • How do we help?
  • 43 MongoDB Business Value Enabling New Apps Better Customer Experience Lower TCOFaster Time to Market
  • 44 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
  • 45 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