Crito
Improving Business Performance based on multi-categories Customers through RealTime Analytics,
using Big Data Technologies.
CRITO Stream Computing enables predictive analytics of data in motion for real-time decisions allowing your company to capture and analyze data - all the time, just in time.
The end goal is to build Customer Intelligence Analytics is an innovative solution designed to enable your company to understand customer behavior and experience and leverage these insights to trigger personalized offers and customer care actions.
CRITO builds prediction capabilities in order to enhance the ability to prevent revenue loss, reduce operational cost and improve customer experience, thus further differentiating its offerings in the market.
Technology
CRITO uses advanced IBM cutting edge BIG DATA technologies to process, synchronize and analyze multiple feeds, as they flow into your business
The Streaming Engine developed to handle huge amount of Events and detect them against Rules to recommend about the Action to act.
The Learning Machine Module improves the Rules and enriches the Rule base by new Intelligent Rules
IBM Big Data
IBM is unique in having developed an enterprise class big data platform that allows you to address the full spectrum of big data business challenges.
Why a platform versus individual products to address big data pain points? The real benefit of the platform is leverage – the ability to start with one capability and easily add others over your big data journey. IBM is the only vendor with this broad and balanced view of big data with the needs of a platform – the benefit is pre-integration of its components to reduce your implementation time and cost.
The key platform capabilities include:
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Hadoop-based analytics: Processes and analyzes any data type across commodity server clusters.
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Stream Computing: Drives continuous analysis of massive volumes of streaming data with sub-millisecond response times.
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Data Warehousing: Delivers deep operational insight with advanced in-database analytics.
Crito uses advanced BIG DATA and Cloud based technologies to process, synchronize and analyze multiple real time feeds, as they flow into the Trading Floor.
Crito Automates “Best Practice” Algorithms and Business Rules, executed today manually by Traders or done “After the Fact” or not done at all.
Crito identifies and eliminates “Bad” Bets and “Bad” Customer as well as Good bets and profitable Customers.
Crito provides a set of prebuilt Dashboards to enable analysis of trading events and customer profiles “after the fact”.
Goal
To increase Bookies profitability by improving the Trading Floor performance:
Reduce loses by Identifying and eliminating “bad” bets and “bad” customers in real time, as bets are processed.
Increase revenue by relieving cross customer restrictions, due to poor ability to identify “Bad” Customers.
Cut operating costs by automating the majority of the on going work done today manually by Traders.
Personalized Networking
CRITO Stream Computing enables predictive analytics of data in motion for real-time decisions allowing Cellular providers to capture and analyze data - all the time, just in time.
CRITO provides a Customer Intelligence Network Analytics is an innovative solution designed to enable Cellular service providers to understand customer behavior and experience and leverage these insights to trigger personalized offers and customer care actions.
CRITO has prediction capabilities takes the SON (Self-organizing networks) and maximize the network for the needs of the customer, according to the profile of the customer, engineering considerations.
This provides the service providers with valuable assets:
Minimizing human errors
Enjoy a true 360° view of the customer encompassing customer and network data
Predict usage patterns and customer needs to create personalized offers to grow profitability
Measure and monitor Quality of Service to identify causes of poor customer experience
Trigger proactive care actions to ensure customer satisfaction
Effectively leverage Big Data volumes of network usage
Enhance the ability to prevent revenue loss
Reduce operational cost and improve customer experience
Differentiating its offerings in the market.
CRITO Components
The CRITO network analytics solution is based on following major components:
DPI:
A passive DPI to capture and aggregate real time video streaming and HTTP events
IBM InfoSphere Streams :
This platform is the heart of the solution. it uses to enrich network data with customer information and to populate the Data Warehouse database
Big Data BI Database:
Used to store aggregated data as well as customer profiles that can be used for the various business cases.
BSS Database:
Will be used as a source of customer data.
Hadoop:
stores all data in a special format to make the platform for Machine Learning.
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ICEQ implemented the CRITO platform for some businesses:
Using the most advanced technology to store the Huge amount of data, for the next BI solution and the Data Mining application.
Applications
Crito provides a Web Application to Manage Rules, Reports and Monitor.
The application is secured and can give access control to users according to their role (Admin, Trader, User…)
A Real-Time Monitor that display all Alerts and Actions Deployed by the Crito Engine.
Reports to discover the BI Database and analyze Historical Data.
Rules Management to define the parameters for the Rules and activating it.
Using various networks to collect data about our users and their friends and correlate it with our data, in order to create a profile for every user.
Analyze the DWH, Hadoop and Social Networking data to find patterns that can make new Rules, and discover “Bad” users by analyzing the Social Networking Media.
How it is done?
IBM Big Data Technologies
Data Science Analytics
Hadoop
Social Networking Media.
Data Mining application.
Using the IBM Big Data Platform for Data Streaming and Real-Time Analysis
Using the Watson API for on demand Analysis and Intelligent customer Analysis
Using the Bookies “best practice” and Data Analytics capabilities to create Dynamic Rule Base for alerts and actions.
Machine Learning mechanism for improving the Rules and creating more rules.
