This presentation focuses on the use of graph databases to gain competitive advantage within the retail industry. We start with an overview of graph databases and Neo4j, and then discuss how to leverage the connections in your data, looking beyond product-related data to build effective recommendation engines and creating the optimal customer experience.

1. Driving Digital Transformation With Neo4j
GRAPHS IN RETAIL
June 23, 2016
Neo4j Webinar

2. Alessandro Svensson
Solutions @ Neo Technology

3. AGENDA
• Quick intro to graphs
• Graphs in Retail
• Real-Time Recommendations
• Delivery & Logistics
• Summary

4. A quick definition of graphs

5. A way of representing data
DATA DATA

6. Relational
Database
A way of representing data
Structured
Pre-computed
Based on rigid rules

7. Graph
Database
Relational
Database
A way of representing data
Highly Flexible
Real-Time Queries
Highly Contextual
Structured
Pre-computed
Based on rigid rules

8. Neo4j is the world’s first “off the shelf” graph database
designed to derive value from data relationships

9. Finance Social networks RetailHR &
Recruiting
Manufacturing
& Logistics
Health Care Telco
Today we see graph-projects in virtually every industry

10. Retail

11. NEO4j solves retail-related challenges for some
of the largest companies in the world
Adidas uses Neo4j to combine
content and product data into a
single, searchable graph database
which is used to create a
personalized customer experience
“We have many different silos, many
different data domains, and in order
to make sense out of our data, we
needed to bring those together and
make them useful for us,”
– Sokratis Kartelias, Adidas
eBay Now Tackles eCommerce
Delivery Service Routing with Neo4j
“We needed to rebuild when growth
and new features made our slowest
query longer than our fastest
delivery - 15 minutes! Neo4j gave us
best solution”
– Volker Pacher, eBay
Walmart uses Neo4j to give
customer best web experience
through relevant and personal
recommendations
“As the current market leader in
graph databases, and with
enterprise features for scalability
and availability, Neo4j is the right
choice to meet our demands”.
- Marcos Vada, Walmart

12. Real-Time Recommendations

13. End Consumers
Component
Manufacturers
Logistics
Traditional Retail Value Chain
RetailersWholesalers
Assembly
Plants

14. PAYMENTS
SALES-
CHANNELS
SUPPLY
CHAIN
PRODUCTS MARKETING
CRM
CUSTOMER
EXPERIENCE
THE ONLINE
RETAIL VALUE
CHAIN

15. PAYMENTS
SALES-
CHANNELS
SUPPLY
CHAIN
PRODUCTS MARKETING
CRM
CUSTOMER
EXPERIENCE
Store
Mobile
Webstore

16. PAYMENTS
SALES-
CHANNELS
SUPPLY
CHAIN
PRODUCTS MARKETING
CRM
CUSTOMER
EXPERIENCE
Store
Mobile
Shipping
Inventory
Express goods
Home delivery
Webstore

17. PAYMENTS
SALES-
CHANNELS
SUPPLY
CHAIN
PRODUCTS MARKETING
CRM
CUSTOMER
EXPERIENCE
Store
Mobile
Shipping
Inventory
Express goods
Home delivery Ratings
Price-range
Category
Webstore

18. PAYMENTS
SALES-
CHANNELS
SUPPLY
CHAIN
PRODUCTS MARKETING
CRM
CUSTOMER
EXPERIENCE
Store
Mobile
Shipping
Inventory
Express goods
Home delivery Ratings
Price-range
Category Content
Promotions
Online advertising
Webstore

19. PAYMENTS
SALES-
CHANNELS
SUPPLY
CHAIN
PRODUCTS MARKETING
CRM
CUSTOMER
EXPERIENCE
Store
Mobile
Shipping
Inventory
Express goods
Home delivery Ratings
Price-range
Category Content
Promotions
Online advertising
Loyalty Programs
Returns
Feedback
reviews
Tweets
Emails
Customer support
Webstore

20. PAYMENTS
SALES-
CHANNELS
SUPPLY
CHAIN
PRODUCTS MARKETING
CRM
CUSTOMER
EXPERIENCE
Store
Mobile
Shipping
Inventory
Express goods
Home delivery Ratings
Price-range
Category Content
Promotions
Online advertising
Loyalty Programs
Returns
Feedback
reviews
Tweets
Emails
Customer support
Credit Card
Cash
Mobile Pay
Purchase History
PAYMENTS
Webstore

21. PAYMENTS
SALES-
CHANNELS
SUPPLY
CHAIN
PRODUCTS MARKETING
CRM
CUSTOMER
EXPERIENCE
Store
Mobile
Shipping
Inventory
Express goods
Home delivery Ratings
Price-range
Category Content
Promotions
Online advertising
Loyalty Programs
Returns
Feedback
reviews
Tweets
Emails
Customer support
Credit Card
Cash
Mobile Pay
Purchase History
BEYOND
MOBILE
Augmented Reality
Smart products
Connected homes
Webstore

22. Digital transformation in retail today
requires to put all this data into good use

23. SHOPPING EXPERIENCE

25. Related products
People who bought X
also bought Y
Recommendations
(In Real-Time)
The main
product

26. LOOKS_AT
KITCHEN AID
SERIES

27. LOOKS_AT
Complaints
reviews
Tweets
Emails
KITCHEN AID
SERIES

28. LOOKS_AT
Returns
Complaints
reviews
Tweets
Emails
KITCHEN AID
SERIES

29. LOOKS_AT
Returns
Inventory
Complaints
reviews
Tweets
Emails
KITCHEN AID
SERIES

30. LOOKS_AT
Returns
Home delivery
Inventory
Express goods
Complaints
reviews
Tweets
Emails
Location/
KITCHEN AID
SERIES
Promotions
Bundling

31. LOOKS_AT
Returns
Purchase History
Price-range
Home delivery
Inventory
Express goods
Complaints
reviews
Tweets
Emails
Category
Promotions
Bundling
Location/
KITCHEN AID
SERIES

32. LOOKS_AT
Returns
Purchase History
Price-range
Home delivery
Inventory
Express goods
Complaints
reviews
Tweets
Emails
Category
Promotions
Bundling
Location
KITCHEN AID
SERIES

35. Shifting To Graphs
You can’t solve graph problems efficiently,
with a non-graph technology

36. Data stored as a graph

37. TECHNICAL LEGACY

38. Product
RDBMS
CRM
RDBMS
Payment
RDBMS
Marketing
RDBMS
Logistics
RDBMS
TECHNICAL LEGACY

39. Product
RDBMS
CRM
RDBMS
Payment
RDBMS
Marketing
RDBMS
Logistics
RDBMS

40. Pre-computed
Purpose has to pre-determined
Limited Context
Static
Non-graph approach
RDBMS
Real-Time Recommendations
Dynamic
Highly contextual
Flexible and Scalable
Graph approach

41. To get results, in real time,
from a dataset that is highly
interconnected – you need a
graph database!

42. Logistics (Delivery)

43. Physical Stores Web/Mobile
+ Instant access
+ Physical Experience
– Requires visits
– Limited inventory
+ Purchase from home/office/remote
+ “Unlimited” inventory
– Delivery time & fees
– Non-physical experience
User Experience

44. “Same Day Delivery”-Demo

48. Same day
1-4 hours
2-4 hours

49. Store Location

50. Store Location

51. Store Location
T-shirt
Summer
Clothes

52. Store Location
Zip Code
T-shirt
Summer
Clothes

53. Zip Code
T-shirt
Summer
Clothes
Store Location
Truck
Bike

54. Zip Code
T-shirt
Summer
Clothes
Store Location
Truck
Availability slots
Bike

55. Same day
1-4 hours
2-4 hours

56. Delivery within 2 hours
at your location.

57. Stores CategoriesProductsInventoryCouriersTimetable
• No need to change existing data-sources
• You will need a graph database
layer to leverage the relationships in
the data
• You need to query this in real-time

58. Summing up

59. Data-relationships are extremely powerful
Graphs are intuitive to understand
Neo4j is easy to implement
Neo4j solves complex problems 1000x faster than RDBMS
Provide you with a dynamic structure for the future
Have significant impact on results!
Reasons for adopting Neo4j

60. Proven, low risk solution

61. Neo4j Adoption by Selected Verticals
RETAILSOFTWARE
FINANCIAL
SERVICES
MEDIA & OTHER
SOCIAL
NETWORKS
TELECOM HEALTHCARE

62. 01
Valuable Resources!
neo4j.com/developer neo4j.com/use-cases neo4j.com/product
Developers Use Cases Product

63. THANK YOU!
Alessandro Amidani Svensson
Senior Solutions Marketing Manager, Neo Technology