IT Labs Corporate Presentation

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Service &
Product-oriented
Development
Company
FOUNDED
Los Angeles - 2005
PRESENCE
Worldwide
TALENT
200+ Full
time Team
EXTERNAL TALENT
1,000+ Network
Team
We say: ‘You spend
70% of your day
creating, you better
make it count’ J
CERTIFICATIONS
- ISO 9001
- ISO 14001
- ISO/IEC 27001
- ISO/IEC 20000-1

3. Focus
§ Consultancy
§ Technology Strategy, Business Development, Investments
§ Technology
§ System architecture design and integrations
§ Custom software solutions & products
§ Analytics & Big Data
§ Website design & development
§ Mobile Apps
§ Hosting & Support
§ Online Promotion
§ SEO & Social Media
§ Paid Advertising
§ Content Aggregation & Creation
§ Education
§ Molding the next world-class talent [no exaggeration]
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4. Clients/Partners [short list]
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5. Technology Service Areas
§ Technology Strategy
§ Project Management
§ Assessments & Evaluations
§ Systems Design & Integration
§ Functionality Design
§ Architecture Design
§ Documentation
§ Programming & Quality Assurance
§ Graphic Design & User Experience
§ Maintenance, Hosting & Support
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6. Solution Process
Product
Scope
Architecture
Design
User
Experience
Graphic
Design
Programming
&
Development
Quality
Assurance
Support &
Maintenance
Online
Promotion
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Agile/Scrum
Waterfall
Hybrid

7. Locations
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Management & Sales
West Palm Beach, FL
Menlo Park, CA
New York, NY
Las Vegas, NV
London, UK
Tallin, Estonia
Kuwait City, Kuwait
Sydney, AU
Development
USA
Macedonia
Croatia

8. Edu Lab
§ IT Labs’s Educational Lab is one of the most important parts
of its intellectual power. It creates new experts with fresh and
ambitious visions. Its goal is to educate the future of the
company’s talent in order to serve the new and current
services & products.
§ The Director of IT Labs Education is Zoran Mitev, MBA
§ He focuses on:
§ Managing the Edu Lab
§ Research, Marketing & Advertising
§ Organization & Coordination
§ Leader of Edu Research & Innovation
§ Main contact for the students
§ To be the ‘cool guy’
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9. Big Data
Case studies per industry
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10. Big Data Focus
u Internal improvements
u Automation of Business Processes
u Process Improvements
u Cost Reduction
u Business Process Mining
u Analytics
u Decision Making Analytics
u Data Warehousing, Management & Manipulation
u Data Repurposing
u Predictive Analytics, Real-time Analytics, Pattern-based Analytics
u Customer Behavior
u Customer Profiling
u Customer Upsell
u Customer Management
u Gaming: Sports Betting
u Complex Big Data Processing Manipulation
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11. Cosmetics
u Solutions:
u End user profiling and analysis with traditional data and social
networks in relation to company brands.
u Brand key attributes identification, awareness and engagement
levels.
u Matching market sentiment with personality characteristics of
celebrity influencers. Real time champion discovery.
u Real time re-sellers/end customers/influencers discovery.
u Answers to questions:
u What make-up artists use which products.
u What champion (celebrity) would fit which target audience.
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12. Insurance
u Solutions
u Fraud detection - End user classification algorithms and behavior
deviation detection, coupled with key process indicators to flag
potential irregularities.
u Repositioning support – research the landscape (demographics &
competition), gain understanding of targeted end users and their
preferences and develop tactical suggestion to support repositioning
of portfolio of products.
u End user retention and targeted sales/up-sales discovery, monitoring,
analytics and prediction. Understating end users and providing
suggestions on retention and contract renegotiation. Sales team
support by calculating probabilities of end user’s positive reaction to
campaigns.
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13. Telecom
u Solutions:
u Fighting churn on products with low loyalty indexes. Gaining insight on
end user roles and behavior by innovative use of social network
analysis and thus recognizing the influencers and key players.
Focusing marketing on influencers and other key end users that have
best overall positive yield to network. Agile refocusing of
communication on detection of deviance and “early warning” churn
detection. Minimizing the negative effects of churners (that we did
not manage to stop from churning) to the overall network.
u Brand awareness and penetration to specific market segments,
competition analysis and marketing campaign support.
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14. Retail
u Solutions
u Customer loyalty – using loyalty program data coupled with analysis
of social networks, relevant sites (blogs and portals) and introspective
brands and products to increase sales, suggest up-sales, understand
and use end user purchase seasonality to offer relevant products in
the just right moment, create campaigns on special dates and
periods (Valentine’s day, Christmas, school season, summer vacation
period and alike) that communicate message with highest probability
of end user’s positive curiosity coupled with suggestion of appropriate
products and bundles that will resonate best with client preferences
(and their needs & expected budget/spending positioning).
u Significantly reducing inventory by predicting sales on individual shop/
city/region basis (based on end users research coupled with machine
learning based on understanding previous sales). Minimizing end user
churn by ensuring desired products are available on-site, at the
proper time and in quantities that are just right.
u Up-sell prediction and execution with measurable success rate
References are under strict NDA 14

15. Banking
u Solutions
u Behavioral finance – ensuring end user’s risk exposure is in proper
correlation with end user risk appetite.
u Analysis of specific market segments vs brands (in example students or
young adults), listening on social media (and blogs etc) to determine
key communication topics and decision triggers to influence their
decision on what bank to use (or switch to). Supporting targeted
marketing campaigns that strive to increase gravitation of chosen
segment toward specific bank/brand.
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16. Sports Betting
u Solutions
u Analyzing end users, their preferences and habits and key decision
triggers to attract them to the specific site and maximize their overall
experience. Combining tracking of competition to ensure offering
relevance with tracking on end user interest trends (in respect to
overall sport season events) to maximize customer retention.
u Models and algorithms that carefully balance management of
company risk exposure vs end user’s experience. Combating fraud,
both in house and on market.
References are under strict NDA
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17. Welcome!
Welcome to the IT Labs family!
www.it-labs.com
contact@it-labs.com
+1 323.384.7368
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