TV watching: Not an easy job

Choosing smart

The Situation : Video viewing has evolved

Analogue TV

1950s-1970sLimited

programmingMass appeal contentPassive audienceOne way experience

Cable & SateliteMid 80s-

2000s500 channelsTargeted contentSelective audienceTwo- way experience

Digital>= NOW

unlimited channelsUnlimited, contentEngaged usersMulti - way experience

BROADCASTING MICROCASTING

Present: TV is just another platform

Screens are getting more diverse The CONSUMER is now in control Every little thumbnail counts !

The Problem : lost in content

RABT TO THE RESCUE IMPROVING EVERYDAY ENTERTAINMENT VIA HELPING MEDIA COMPANIES PERSONALIZE THE WAY THAT

THEIR USERS EXPERIENCE DIGITAL CONTENT WHILE AT HOME OR ON THE GO

An environment agnostic approach to personalized discovery.

State of the Art: Machine Learning + Big Data + Predictive Science.

And we deliver ... The most personalised experience …Page Views

$MonetizationEngagement RetentionRabtPersonalization

How Rabt is solving the problem…

The Market : Over-The-Top Snapshot

$9B

EUROPE

$21 BUS

$8B

LATAM

$16BAPAC

The Market : Over-The-Top Snapshot

20 billion online videos are going to be watched only today.

64% of the global mobile traffic is done for video. It will be 80% by 2019.

The opportunity : OTT Personalization

Annual Revenue$5.5Billion (2014)

Personalization budget $150Million (3% of

revenue)

Global OTT$54Billion (2019)

OTT Personalization$1.7Billion (3% of

revenue)

Rabt’s How does it work (1:1 )

Content monitoring

: Start – Stop

Impressions Feedback Calculati

on of content appeal

Personalised best list for every

user

More views per

visit= User

acquisition ROI

Extended shelf life = Content

ROI

Data & technology =Cheaper, faster and better

business decisions

Rabt = $ for Content Providers

Case StudyAbout Letv:

Largest digital content platform in China.On-demand platform draws 300+ Million unique users per month for long form content. 36,000 pieces of content across all categories.

Rabt became the A/B mechanism vs. the internal personalization engine developed by 20 engineers over 2 years.

Challenge: increase CTRs of recommended videos in different parts across the platform – landing page, inside the video player, outside the video player, etc.

Case StudyKey Results:

Rabt CTR: 15-22%Improvement vs. Letv: +10-30% dailyPrediction accuracy: 93%

Financial figures - Revenue model:

SaaS model charging per personalized user per month. ARR of $25K-$200K per client.

Total funding to date: $660K.

Business model & Financials

New York :

Easier access to media and technology partners

Easier accesss to funding

Approved for 10 years tax-free profits, 10 years tax-free salaries.

Athens :

High quality engineering talent

Small burn rate

Two-office location occasionally makes the communication difficult.

NY& Athens – Challenges Vs Benefits

Yiannis BroustasCo-Founder & CEO

Prof. George LentzasCo-Founder Chief Scientist

Anthony Milonas CTO

Bobby AlexisBusiness Development & Product

Team

See you soon in a video near you!