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The Personalization 
Machine 
Driving revenue through 
personalized user engagement
WHO WE ARE 
PERSONALIZATION PLATFORM PROVIDER 
One of the largest third-party provider in the world 
AWARD-WINNING and WORLDWIDE PATENTED algorithms with 
75-80 man-years of technical development behind 
THOUGHT LEADERSHIP in the RecSys scientific community 
TRACK RECORD in various industries
SCIENTIFIC ACHIEVEMENTS 
Team members won several awards in competitions: 
• Machine learning: 
 Netflix Prize 
 KDD Cup 2006 
 Gomoku Open Tournament 2006 
 GE flight quest 2013 
• Text mining: 
 i2b2 2008 
 BioNLP 2009 
 DDI Challenge 2011 
• Programming: 
 ITech Challenge 2006 
 ch24.org 
• Mathematics: Int. Mathematics Competition 2001 
• 13 student-recognitions 
Conferences: 
• Co-organization of international competitions (KDD Cup 2007, Recsys Challenge 2012) 
• Invited membership at the Netflix Prize Panel (2009), Context-awareness in industry panel 
(2012) 
• ACM Recsys 2012 best paper award honourable mention 
• Tutorial at ACM Recsys 2012 on the evaluation of recommending systems
GRAVITY AROUND THE CLOCK - CUSTOMERS 
BY BUSINESS LINES 
Holidays 
Travel 
Classified Media 
Daily Deal 
OTT Video on Demand 
Dating 
E-commerce 
Mobile 
Marketing 
IPTV 
Retail 
Music 
Auction and 
Online 
Market Place 
Gravity SW 
integrated 
with 
B2B customer 
infrastructure 
Media
FEATURED REFERENCES 
The largest online classifieds 
sites worldwide 
#1 WW Video Chat, 2% of 
WW internet traffic, Alexa<50 
One of the leading video-sharing 
site worldwide 
NASDAQ listed mobile 
marketing company 
Increased page views, time spent on 
site, contact requests by up to 125% 
Extremely massive traffic served, in 
peak time 6000 recommendations to 
deliver per second 
Increased ad revenues and user 
satisfaction up to 25% in 5 countries 
Increased response in SMS gaming 
by 7%
The Challenge 
Millions of products, thousands of visitor dreams but only one 
screen… 
1000s of products, 100s of different visitor dreams, but only one screen.
What if… 
You could predict each of your visitor’s intention and 
behavior?
Personalized User Journeys - Understand your 
users and exploit the potential in BIG DATA 
Based on Interest Seasonality 
Purchases Holidays 
Searches Continuous 
Devices used Working hours 
Last activity peak Every year 
• Predicting not just the primary, but the secondary, tertiary, etc. interests 
• Apart from history and behavior, focusing on the current context
COLLABORATIVE 
FILTERING 
CONTENT-BASED 
FILTERING 
CONTEXT 
AWARENESS 
SOCIAL 
RECOMMENDATIONS
C2C CLASSIFIEDS 
Business objective: 
 Improve general sales-related 
Key Performance Indicators 
(KPIs) 
Norwegian media conglomerate, 
has operations in 29 countries. 
2 400 million USD revenues in 
2012, 25% came from classifieds. 
KPI 
Increase of 
KPI 
Testing method 
Ad detail page views 125% A/B (in-house solution) 
Total page views 4% A/B (in-house solution) 
CTR 368% 
A/B (in-house solution, random 
placement) 
Time spent on site 3% 
A/B (in-house solution, random 
placement) 
Results: 
Schibsted Hungary and Gravity R&D were the 2012 Show me the Money 
Award winners for their Dynamic Personalization Innovation.
CONTENT RECOMMENDATION 
Business objective: 
 Improve the click through 
rate (CTR) 
KPI CTR 
Increas 
e of KPI 
On average 
50% 
Testing 
method 
A/B (in-house 
solution) 
Results: 
The media group’s portal portfolio 
covers the 77% of the Hungarian 
internet users. Origo is the leading 
news portal in Hungary. 
20% 
15% 
10% 
5% 
0% 
CTR evolution compared to the inhouse solution 
With RECO 
Using in-house solution 
1st month 2nd month
VIDEO STREAMING 
Business objective: 
 Increase ad revenue by increasing page 
impression (PI) 
 Increase click through rate (CTR) of 
recommended content 
 Increase user satisfaction (measured by 
long term CTR) 
 Increase average video watch length 
One of the leading sites 
for sharing videos, 
attracts over 112 million 
unique monthly visitors 
and 2,5 billion videos 
views worldwide. 
Offers 35 localized 
versions in 18 different 
languages 
KPI 
Increase of 
KPI 
Testing method 
CTR 12-22% 
Compared to other vendor, in-house 
development 
Long term CTR 6-17% 
Number of PIs 6-25% 
Results: 
* measured in 5 countries: France, Japan, USA, Germany, UK – minimum 
and maximum increase values are shown
AUCTION PORTALS 
Business objective: 
 Faster search & discovery by 
recommendations 
 Increase the bid value of goods 
 Facilitate the discovery of goods 
E-commerce leader in 
Central and Eastern 
Europe, a group of 
companies managing 
75 sites in over 20 
countries 
KPI 
Increase of 
KPI 
Testing method 
Banner conversion 5% 
Compared to other vendor, in-house 
development 
Bid value 6% 
Number of bids 110% 
Results:
E-COMMERCE 
Business objective: 
 Improve general sales-related 
Key Performance indicators 
(KPIs) 
KPI 
Increase of 
KPI 
Testing method 
Revenue coming 
through RECO 
7% A/B (in-house solution) 
Item page CTR 7% A/B (in-house solution) 
Results: 
E-commerce leader in 
Central and Eastern 
Europe, a group of 
companies managing 75 
sites in over 20 countries.
E-COMMERCE 
Business objective: 
 Improve general sales-related 
Key Performance indicators 
(KPIs) 
 Improve the shopping 
experience 
KPI 
Increase of 
KPI 
Testing method 
increase in banner 
conversion rates 
400% A/B (in-house solution) 
banner click-to-purchase 
conversion 
rate 
11,5% A/B (in-house solution) 
purchases made 
through RECO 
5% A/B (in-house solution) 
Results: 
Libri is a Superbrand 
award-winning online 
and retail bookstore with 
more than half a million 
registered users and 43 
retail locations across 
Hungary.
CTR increase by Gravity 
1st week 
250% 
200% 
150% 
100% 
50% 
0% 
% - daily moving average 
AD TARGETING 
Business objective: 
 Improve the click through rate 
 30+ million ads served daily 
 Creative targeting in 2 zones of a 
hub site 
KPI CTR 
Increase 
of KPI 
On average 
110% 
Testing 
method 
A/B (in-house 
solution) 
Results: 
Hungarian market leader 
in online marketing 
technologies. 
Provides 16 billions of ads 
on a monthly average. 
2nd week 
3rd week
ONLINE DATING 
Business objective: 
 Improve the discovery, increase 
the conversion of “Personal 
tips” box 
KPI 
Increase of 
KPI 
Testing method 
Banner clicks 143% A/B (in-house solution) 
Number of 
250% A/B (in-house solution) 
conversations 
Upsell to premium 
subscription 
26% A/B (in-house solution) 
Results: 
Randivonal.hu is Hungary’s 
leading online dating portal 
with 1.000.000+ registered 
users (freemium model) and 
800.000 daily page views.
DATA MINING ENGAGEMENTS 
 Scope: SMS sending time optimization 
 Objective: increase the number answers from users 
 Approaches and achievements: 
 Question recommendation: +7% increase 
 SMS - sending time recommendation: +5% (heavy users) 
 Scope: product placement suggestions 
 Objective: data analysis for agent support 
 Achievements: 
 Identification of similar shops and products 
 Replacement suggestions for out-of-stock 
 Scope: large scale data analysis of shoppers 
 Objective: predict purchases in different categories 
 Context-awareness: geo-location, basket content, weather 
 Potentially lead to implementation of Gravity on Tesco.com
CONSUMER GOODS 
Business objective: 
 Improve P&G’s in-house store clustering 
process 
 Provide store recommendations for agents 
at store level instead of channel level 
 Increase revenue through recommendations 
 Field test now in India (2014Q2), next in 
China (2014Q3-4) 
One of the world’s largest supplier of 
consumer goods 
KPI 
Increase of 
KPI 
Testing method 
Ratio of purchased 
recommended goods 
5–7 % Only new products can be 
recommended for a store (no 
replenishment) 
This means extra revenue 
Revenue ratio of 
recommended goods 
6-8% 
Results:
TOOLS TO MONETIZE THE VISITOR LIFECYCLE
Re-engage and convert high-intent 
prospects with personalized banners on 
sites you advertise on 
Unlimited number of custom landing pages 
generated real time and automatically (PPC 
and Adwords automatization tool) 
Outlined tools 
Recommend the most interesting 
content to your users 
Personalized 
Recommendation 
Send personalized newsletters, 
transactional emails and email alerts 
Personalized 
Retargeting 
Newsletter 
Personalization 
Rank search results based on personal 
interest, predictive search 
Smart Search 
Dynamic 
Landing Page
Tech details 
Everything about the integration process: 
https://developers.gravityrd.com/display/DEV/Integration+Overview 
Two major integration options: 
- server side 
- client side 
SaaS Based Solution: “Gravity solves everything for a monthly fee” 
Appliance/Hosted Solution: “Gravity provides license, training, 
integration and support”. Customers with Security, policy, political, geographical 
issues which prevent them to subscribe for a SaaS service 
Hybrid Solution: “Those special customers who need more”
JAVASCRIPT INTEGRATION
SERVER-SIDE INTEGRATION
KEY RECO FEATURES
Control Panel
Control Panel
Gravity Analytics
Thank you! 
Contact us: 
www.gravityrd.com 
sales@gravityrd.com 
For the latest trends and insights: 
www.facebook.com/gravityrd

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Introduction

  • 1. The Personalization Machine Driving revenue through personalized user engagement
  • 2. WHO WE ARE PERSONALIZATION PLATFORM PROVIDER One of the largest third-party provider in the world AWARD-WINNING and WORLDWIDE PATENTED algorithms with 75-80 man-years of technical development behind THOUGHT LEADERSHIP in the RecSys scientific community TRACK RECORD in various industries
  • 3. SCIENTIFIC ACHIEVEMENTS Team members won several awards in competitions: • Machine learning:  Netflix Prize  KDD Cup 2006  Gomoku Open Tournament 2006  GE flight quest 2013 • Text mining:  i2b2 2008  BioNLP 2009  DDI Challenge 2011 • Programming:  ITech Challenge 2006  ch24.org • Mathematics: Int. Mathematics Competition 2001 • 13 student-recognitions Conferences: • Co-organization of international competitions (KDD Cup 2007, Recsys Challenge 2012) • Invited membership at the Netflix Prize Panel (2009), Context-awareness in industry panel (2012) • ACM Recsys 2012 best paper award honourable mention • Tutorial at ACM Recsys 2012 on the evaluation of recommending systems
  • 4. GRAVITY AROUND THE CLOCK - CUSTOMERS BY BUSINESS LINES Holidays Travel Classified Media Daily Deal OTT Video on Demand Dating E-commerce Mobile Marketing IPTV Retail Music Auction and Online Market Place Gravity SW integrated with B2B customer infrastructure Media
  • 5. FEATURED REFERENCES The largest online classifieds sites worldwide #1 WW Video Chat, 2% of WW internet traffic, Alexa<50 One of the leading video-sharing site worldwide NASDAQ listed mobile marketing company Increased page views, time spent on site, contact requests by up to 125% Extremely massive traffic served, in peak time 6000 recommendations to deliver per second Increased ad revenues and user satisfaction up to 25% in 5 countries Increased response in SMS gaming by 7%
  • 6. The Challenge Millions of products, thousands of visitor dreams but only one screen… 1000s of products, 100s of different visitor dreams, but only one screen.
  • 7. What if… You could predict each of your visitor’s intention and behavior?
  • 8. Personalized User Journeys - Understand your users and exploit the potential in BIG DATA Based on Interest Seasonality Purchases Holidays Searches Continuous Devices used Working hours Last activity peak Every year • Predicting not just the primary, but the secondary, tertiary, etc. interests • Apart from history and behavior, focusing on the current context
  • 9.
  • 10. COLLABORATIVE FILTERING CONTENT-BASED FILTERING CONTEXT AWARENESS SOCIAL RECOMMENDATIONS
  • 11. C2C CLASSIFIEDS Business objective:  Improve general sales-related Key Performance Indicators (KPIs) Norwegian media conglomerate, has operations in 29 countries. 2 400 million USD revenues in 2012, 25% came from classifieds. KPI Increase of KPI Testing method Ad detail page views 125% A/B (in-house solution) Total page views 4% A/B (in-house solution) CTR 368% A/B (in-house solution, random placement) Time spent on site 3% A/B (in-house solution, random placement) Results: Schibsted Hungary and Gravity R&D were the 2012 Show me the Money Award winners for their Dynamic Personalization Innovation.
  • 12. CONTENT RECOMMENDATION Business objective:  Improve the click through rate (CTR) KPI CTR Increas e of KPI On average 50% Testing method A/B (in-house solution) Results: The media group’s portal portfolio covers the 77% of the Hungarian internet users. Origo is the leading news portal in Hungary. 20% 15% 10% 5% 0% CTR evolution compared to the inhouse solution With RECO Using in-house solution 1st month 2nd month
  • 13. VIDEO STREAMING Business objective:  Increase ad revenue by increasing page impression (PI)  Increase click through rate (CTR) of recommended content  Increase user satisfaction (measured by long term CTR)  Increase average video watch length One of the leading sites for sharing videos, attracts over 112 million unique monthly visitors and 2,5 billion videos views worldwide. Offers 35 localized versions in 18 different languages KPI Increase of KPI Testing method CTR 12-22% Compared to other vendor, in-house development Long term CTR 6-17% Number of PIs 6-25% Results: * measured in 5 countries: France, Japan, USA, Germany, UK – minimum and maximum increase values are shown
  • 14. AUCTION PORTALS Business objective:  Faster search & discovery by recommendations  Increase the bid value of goods  Facilitate the discovery of goods E-commerce leader in Central and Eastern Europe, a group of companies managing 75 sites in over 20 countries KPI Increase of KPI Testing method Banner conversion 5% Compared to other vendor, in-house development Bid value 6% Number of bids 110% Results:
  • 15. E-COMMERCE Business objective:  Improve general sales-related Key Performance indicators (KPIs) KPI Increase of KPI Testing method Revenue coming through RECO 7% A/B (in-house solution) Item page CTR 7% A/B (in-house solution) Results: E-commerce leader in Central and Eastern Europe, a group of companies managing 75 sites in over 20 countries.
  • 16. E-COMMERCE Business objective:  Improve general sales-related Key Performance indicators (KPIs)  Improve the shopping experience KPI Increase of KPI Testing method increase in banner conversion rates 400% A/B (in-house solution) banner click-to-purchase conversion rate 11,5% A/B (in-house solution) purchases made through RECO 5% A/B (in-house solution) Results: Libri is a Superbrand award-winning online and retail bookstore with more than half a million registered users and 43 retail locations across Hungary.
  • 17. CTR increase by Gravity 1st week 250% 200% 150% 100% 50% 0% % - daily moving average AD TARGETING Business objective:  Improve the click through rate  30+ million ads served daily  Creative targeting in 2 zones of a hub site KPI CTR Increase of KPI On average 110% Testing method A/B (in-house solution) Results: Hungarian market leader in online marketing technologies. Provides 16 billions of ads on a monthly average. 2nd week 3rd week
  • 18. ONLINE DATING Business objective:  Improve the discovery, increase the conversion of “Personal tips” box KPI Increase of KPI Testing method Banner clicks 143% A/B (in-house solution) Number of 250% A/B (in-house solution) conversations Upsell to premium subscription 26% A/B (in-house solution) Results: Randivonal.hu is Hungary’s leading online dating portal with 1.000.000+ registered users (freemium model) and 800.000 daily page views.
  • 19. DATA MINING ENGAGEMENTS  Scope: SMS sending time optimization  Objective: increase the number answers from users  Approaches and achievements:  Question recommendation: +7% increase  SMS - sending time recommendation: +5% (heavy users)  Scope: product placement suggestions  Objective: data analysis for agent support  Achievements:  Identification of similar shops and products  Replacement suggestions for out-of-stock  Scope: large scale data analysis of shoppers  Objective: predict purchases in different categories  Context-awareness: geo-location, basket content, weather  Potentially lead to implementation of Gravity on Tesco.com
  • 20. CONSUMER GOODS Business objective:  Improve P&G’s in-house store clustering process  Provide store recommendations for agents at store level instead of channel level  Increase revenue through recommendations  Field test now in India (2014Q2), next in China (2014Q3-4) One of the world’s largest supplier of consumer goods KPI Increase of KPI Testing method Ratio of purchased recommended goods 5–7 % Only new products can be recommended for a store (no replenishment) This means extra revenue Revenue ratio of recommended goods 6-8% Results:
  • 21. TOOLS TO MONETIZE THE VISITOR LIFECYCLE
  • 22. Re-engage and convert high-intent prospects with personalized banners on sites you advertise on Unlimited number of custom landing pages generated real time and automatically (PPC and Adwords automatization tool) Outlined tools Recommend the most interesting content to your users Personalized Recommendation Send personalized newsletters, transactional emails and email alerts Personalized Retargeting Newsletter Personalization Rank search results based on personal interest, predictive search Smart Search Dynamic Landing Page
  • 23. Tech details Everything about the integration process: https://developers.gravityrd.com/display/DEV/Integration+Overview Two major integration options: - server side - client side SaaS Based Solution: “Gravity solves everything for a monthly fee” Appliance/Hosted Solution: “Gravity provides license, training, integration and support”. Customers with Security, policy, political, geographical issues which prevent them to subscribe for a SaaS service Hybrid Solution: “Those special customers who need more”
  • 30. Thank you! Contact us: www.gravityrd.com sales@gravityrd.com For the latest trends and insights: www.facebook.com/gravityrd