Towards a Big Data Recommender
EngineFor Online and Offline Marketplaces
Martin Kahr (Blanc-Noir)
Christoph Trattner (Know-Center)
INHALT
Background and Introduction About Blanc-Noir│ Our Vision │ What we do
Partnership with Know-CenterPartnership │ Challenge and Goal│ Output
Recommender Enginexxxx │ xxxx
Q&A
ABOUT BLANC-NOIR
Headquarter: Graz (Austria)
Subsidiaries: Ingolstadt (Germany)
Vienna, Klagenfurt,
Founded: 2012
Experience: More than 18 years in IT & Marketing
Employees: 60
ABOUT BLANC-NOIR
Blanc-Noir combines Know-How in
marketing and technology
to create innovative and trendsetting
solutions for online and stationary
trade.
OUR VISION
We want to change the buying
behavior of customers and to realize
a unique and sustainable shopping
experience.
WHAT WE DO
• We develop analogue and digital marketing
strategies and campaigns
• Consulting, conception and programming of
E-Commerce and Multi-Channel platforms.
• Development of powerful promotion tools to
increase customer loyalty and shopping
experience.
• Pioneer in the area of Location Based Marketing
and Beacon-Technology
• Cross-Channel Order-Management System
WHAT WE DO (EXAMPLES)
Digital Loyality CardOn- and offline collection and redeem
of bonus points
Mobil
PaymentNFC, Beacon
(Bluetooth 4.0)
Endless-aisleMobile catalogue and
Mobil shopping
WHAT WE DO (EXAMPLES)
App for sellers
• Sales support
• Customer service
• Product information
• Endless-aisle
• Cross- & Upsell
• Coupon via Blue-tooth
to customer´s mobile
PARTNERSHIP 1+1=3
By combining the resources and
competences of Know-Center with our
market-driven input,
we are able to realize a tailored and state-of-
the art solution that provides competitive
advantages for us and our clients.
Unique shopping experience and higher conversions
assumes:
• Understanding and analytics of customer needs,
behaviour and preferences based on historic and live
transactions
• Personalized and real-time communication across all
customer touch points
• No spam - Only relevant and useful information
OUR CHALLENGE AND GOAL
Knowing what the customer
thinks, and desires!
OUTPUT
Cross-Channel
customer understanding
and realtime targeting
How did we manage to handle this
challenge?
RECOMMENDER SYSTEMS
14
WHY SOLR?
• „High-performance, full-featured text search engine library“
… but more precise …
• „High-performance, fully-featured token matching and scoring library“
[Grainger, 2012]
… which provides ….
– full-text searches (content-based)
– powerful queries (e.g., MoreLikeThis or Facets)
– (near) real-time data updates (no pre/re-calculations)
– easy schema updates (social data integration)
• Established open-source software (Apache license) with big
community
15
THE FRAMEWORK
HOW does the thing perform?
Dataset of virtual world SecondLife: Marketplace and social data
17
FOLLOW-UP (2)
RECSIUM FRAMEWORK
...CURRENTLY WORKING ON
• Location-based services shopping malls, train-
stations
• Technology: iBeacons
• Task: indoor navigation, indoor marketing, etc...
...CURRENTLY WORKING ON
DEMO - RECSIUM
http://recsium.know-center.tugraz.at/recsium/
ANY QUESTIONS?
THANK YOU