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Calculating ROI with Innovative E-Commerce Platforms
Enabling Omni-Channel Retailing
#mongodbretail
Global Business Architect, MongoDB
Director, Solution Architecture, MongoDBEdouard Servan-Schreiber
Rebecca Bucnis
“Amazon.com strives to be the e-commerce
destination where consumers can find
and discover anything they want to be buy
online. - Jeff Bezos, founder
Presenters
Rebecca Bucnis
Global Business Architect- Business Strategy
- Former Retailer
Amsterdam, The Netherlands
@rebeccabucnis
Edouard Servan-Schreiber
Director, Solution Architecture
- Delivery of Solutions, Pre-Sales
- North America
New York, NY
@edouardss
@rebeccabucnis @edouardss
• Introduction
• Demands of Modern E-Commerce
• Why Use MongoDB for E-Commerce
• Technical Capabilities and Enablers
• Innovative Case Studies with ROI
• Wrap Up & Next Steps
Agenda
Introduction
Retail in a World with Amazon.com
7
Customer-Centric E-Commerce
1. Product Available? Product Anywhere• Order Management & Fulfillment
2. Continually Fresh Content & Information
• Detailed product, pricing & UGC
3. Multi-Channel Integration • Back-end systems inclusive
Based upon Forrester Wave - BtoC Commerce, 2013
8
Disconnected Ecommerce > ROI
Speed to Innovation is Slow….
Inventory & Fulfillment
more complex
Single Channel Systems
(or Siloed)
Unable to Execute in Real-Time
Static Informatio
n
MongoDB Strategic Advantages
Horizontally Scalable-Sharding
AgileFlexible
High Performance &Strong Consistency
Application
HighlyAvailable-Replica Sets
{ customer: “roger”, date: new Date(), comment: “Spirited Away”, tags: [“Tezuka”, “Manga”]}
10
Information Management
Merchandising
Content
Inventory
Customer
Channel
Sales & Fulfillment
Insight
Social
Retail Architecture Overview
Customer
ChannelsAmazon
Ebay…
StoresPOSKiosk
…
MobileSmartphone
Tablet
Website
Contact Center
APIData and Service
Integration
SocialFacebook
Twitter…
Data Warehouse
Analytics
Supply Chain Management
System
Suppliers
3rd Party
In Network
Web Servers
Application Servers
1. Order Management & Fulfillment
Theme: Product location and availability up-to-minute
Business Benefits: Ability to make a sale!
Modern Ecommerce
12
Inventory
Inventory
MongoDB
External Inventory
Internal Inventory
Regional Inventory
Purchase Orders
Fulfillment
Promotions
13
Demonstration Document Model
Definitions• id: p0
Variations• id: sku0• pId: p0
Summary• id: p0• vars: [sku0,
sku1, …]
Stores• id: s1• Loc: [22, 33]
Inventory• store: s1• pId: p0• vars:
[{sku: sku0, q: 3},{sku: sku2, q: 2}]
Product
14
> db.inventory.findOne()
{ "_id": "5354869f300487d20b2b011d",
"storeId": "store0",
"location": [
-86.95444,
33.40178
],
"productId": "p0",
"vars": [
{ "sku": "sku1", "q": 14 },
{ "sku": "sku3", "q": 7 },
{ "sku": "sku7", "q": 32 },
{ "sku": "sku14", "q": 65 },
...
]
}
Inventory - Quantities
Order Management & Fulfillment
Technical Challenges MongoDB Solution
• Cannot see the up to date inventory by store as inventory is updated in batch processes
• Inventory details are stored in systems which cannot handle the load of massive distributed reads
• Need efficient geospatial lookups to find cheap fulfillment options
• Fast in-place updates able to handle heavy load of real-time changes
• Leveraging RAM for hot data systematically and able to fulfill massive concurrent reads
• Geospatial indexing enabling easy search of inventory through nearby stores
2. Latest Information in Content & Product
Theme: Fresh and Engaging Content Low(est) Latency Business Benefits: Converting sale, ‘discover’ product,
drive revenue
Modern Ecommerce
Merchandising
Merchandising
MongoDB
Product Variation
Product Hierarchy
Pricing
Promotions
Ratings & Reviews
Calendar
Semantic Search
Product Definition
Localization
18
Price: {
_id: <unique value>,
productId: "301671", // references product id
sku: "730223104376", // can reference specific sku
currency: "us-dollar",
price: 89.95,
storeGroup: "0001", // main store group
storeId: [ "1234", "2345", … ] // per store pricing
lastUpdated: Date("2014/04/01"), // last update time
…
}
Indices: productId + storeId, sku + storeId,
storeId + lastUpdated
Merchandising – Pricing
19
• Get Variation from SKU
db.variation.find( { sku: "730223104376" } )
• Get all variations for a product, sorted by SKU
db.variation.find( { productId: "301671" } ).sort( { sku: 1 } )
• Find all variations of color "Blue" size 6
db.variation.find( { attributes: { $all: [ { color: "Blue" }, { size: 6 } ] } )
• Indices
sku, productId + sku, attributes, lastUpdated
Merchandising - Pricing
Continually Fresh Content & Information
Technical Challenges MongoDB Solution
• Enabling numerous price changes intra day and high granularity (per store/channel pricing)
• Collecting and rendering users’ product reviews
• Welcoming new content and be able to serve it right away
• Changing the site structure and content within hours of decision
• Fast updates to a pricing structure within a rich JSON document for maximum flexibiity
• Able to take massive writes of loosely structured data
• Storing of content using GridFS for high availability and fast retrieval
• Flexible schema for easy custom changes.
3. Simplistic Back-End Integration
Theme: Connecting analytics to real-time execution
Business Benefits: Customer satisfaction, increased revenue
Modern Ecommerce
22
Insight
Insight
MongoDB
Advertising metrics
Clickstream
Recommendations
Session Capture
Activity Logging
Geo Tracking
Product Analytics
Customer Insight
Application Logs
23
Streams of User Activity
24
Activity logging - Architecture
MongoDB
HVDFAPI
Activity LoggingUser History
External Analytics:Hadoop,Spark,Storm,
…
User Preferences
Recommendations
Trends
Product MapApps
Internal Analytics:
Aggregation,MR
All user activity is recorded
MongoDB – Hadoop
Connector
Personalization
25
{ _id: ObjectId(),
geoCode: 1,
sessionId: "2373BB…",
device: { id: "1234",
type: "mobile/iphone",
userAgent: "Chrome/34.0.1847.131"
}
type: "VIEW|CART_ADD|CART_REMOVE|ORDER|…",
itemId: "301671",
sku: "730223104376",
order: { id: "12520185",
… },
location: [ -86.95444, 33.40178 ],
timeStamp: Date("2014/04/01 …")
}
User Activity - Model
26
Dynamic schema for sample data
Sample 1{ deviceId: XXXX, time: Date(…) type: "VIEW", …}
Channel
Sample 2{ deviceId: XXXX, time: Date(…) type: "CART_ADD", cartId: 123, …}
Sample 3{ deviceId: XXXX, time: Date(…) type: “FB_LIKE”}
Each sample can have
variable fields
27
Dynamic queries on Channels
Channel
Sample Sample Sample Sample
AppApp
App
Indexes
Queries Pipelines Map-Reduce
Create custom indexes on Channels
Use full mongodb query language to access samples
Use mongodb aggregation pipelines to
access samples
Use mongodb inline map-reduce to access samples
Full access to field, text, and geo
indexing
Multi-Channel Integration
Technical Challenges MongoDB Solution
• Original legacy source systems are rigid, inflexible and do not easily exchange information
• Need to add a new data source on very short notice to get larger view of customers
• Keep history of customer information in loosely structured form for deep analytics
• Ability to maintain original source systems, yet create a blended view without ‘rip and replace’
• Flexible schema for easy custom changes and enhancements to customer profile
• Massive scaling on demand to keep historical data for as long as needed.
Innovative Case Studies with ROI
• Built custom ecommerce platform on MongoDB in 8 Months
•Fast time to market
•Database can meet evolving business needs
•Superior user experience
ROI = Original innovation, performance & flexibility
Customer Examples
• Delivered agile automated supply chain service to online retailers powered by MongoDB
•Decreased supplier onboard time by 12x
•Grew from 400K records to 40M in 12 months
•Significant cost reductions
Customer Examples
Compatibility Matching System used to match potential partners
“With our...SQL-based system, the entire user profile set was stored on each server, which impacted performance and impeded our ability to scale horizontally.
MongoDB supports the scale that our business demands and allows us to generate matches in real-time.” Thod Nguyen, CTO, eHarmony
95% Faster Matches
33
• www.otto.de
• €2.5bn eCommerce site
• Largest web property for female and child clothing in Europe
• 1998 – 2013: based on Intershop
Otto Germany
34
Search & Navigate
Dynamic Product
Shop, Pages & Content
User Experience& Personalization
Customer Journey
Order Management
Focused Capabilities for E-Commerce
35
Press Release – Otto Germany
“With MongoDB, we chose a partner who could really support us in this process with MongoDB
consultants helping us in both design and training. As a result we have a modern, digitally-oriented application development environment which will allow us to implement our innovative ideas as
quickly as we create them.
We have made the right decision in opting for the leading NoSQL company in MongoDB.”- Mr. Peter Wolter – Head of Ecommerce Solutions
36
Executing Modern E-Commerce
R
even
ue P
ote
nti
al
Product Availability Unclear/ Can’t deliver
Product Available – Deliver without insight
Some products available
Unavailable; went to store
Product Available - Deliver Anywhere with insight
Time to Execution
Then
E-Commerce Island Integrated Fulfillment
Static Information Continual Refresh
Unknown Visitor Tailored Journey
Now
Enabling agile delivery of seamless interactions & selling
1. Assess your retail data and omni-channel capabilities
2. Join us and Engage:
• Big Data Analytics - London – 19 June
• MongoDB World - New York – June 23-25
• Customer Experience Exchange – London 2-3 July
3. Start one step at a time - with “prototype” capabilities
What’s Next?
Questions?
Resources
White Paper: Big Data: Examples and Guidelines for the Enterprise Decision Maker
http://www.mongodb.com/lp/whitepaper/big-data-nosql
Recorded Webinar Series: Thrive with Big Data
http://www.mongodb.com/lp/big-data-series
Recorded Webinar: What’s New with MongoDB Hadoop Integration
http://www.mongodb.com/presentations/webinar-whats-new-mongodb-hadoop-integration
Documentation: MongoDB Connector for Hadoop
http://docs.mongodb.org/ecosystem/tools/hadoop/
White Paper: Bringing Online Big Data to BI & Analytics
http://info.mongodb.com/rs/mongodb/images/MongoDB_BI_Analytics.pdf
Subscriptions, support, consulting, training
https://www.mongodb.com/products/how-to-buy
Resource Location
