Revolution R Enterprise Demonstration BDBA Cellular Improves Customer Retention through Churn Analytics and Relevant Web Content Placement

Corporate Overview & Quick Facts

Founded 2008 (as REvolution Computing)

Office Locations Palo Alto (HQ), Seattle (Engineering) Singapore London

CEO David Rich

Number of customers

200+

Investors •  Northbridge Venture Partners •  Intel Capital •  Platform Vendor

Web site: •  www.revolutionanalytics.com

Revolution – “Contender” The Forrester Wave™: Big Data Predictive Analytics Solutions, Q1 2013

Confidential to Revolution Analytics 2

In the big data analytics context, speed and scale are critical drivers of success, and Revolution R delivers on both

Revolution R Enterprise is the leading commercial analytics platform based on the open source R statistical computing language

Revolution R Enterprise

§ High Performance, Scalable Analytics § Portable Across Enterprise Platforms § Easier to Build & Deploy Analytics

is…. the only big data big analytics platform based on open source R the defacto statistical computing language for modern analytics

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How is RRE used in this demo?

Build & Deploy Consume in BI Real-time Scoring §  ScaleR Big Data-ready

algorithms §  Explore data in Hadoop §  Build & score model in

Hadoop

§  DeployR integration to BI Solution

§  RRE model-generated customer churn scores, other calculated fields & additional data used for customer retention strategy decisions

§  DeployR web services interface provides real-time churn propensity scores to rules engine, which prescribes specific offers

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Highlights Build & deploy Consume in BI Real-time scoring

§  ScaleR Big Data Big Analytics-ready algorithms §  Logistic regression

§  Specify Hadoop compute context

§  In-Hadoop model scoring

§  Customer Analysis

§  DeployR Web services interface to BI Solution

§  DeployR Web services interface to rules engine

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Revolution R Enterprise & Hadoop §  How Does RRE Play Inside Hadoop §  How Does RRE 7 Achieve Scale

Internally

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Simplicity Goal: Leverage Hadoop As An R Engine.

§ Plus: –  Run RRE Analytics In Hadoop

Without Change –  Eliminate Need To Design Parallel

Software or “Think In MapReduce” –  Leverage All Revolution R

Enterprise Pre-Parallelized Algorithms

–  Enable Users To Build Custom Apps That Leverage Hadoop’s Parallelism

–  Slash Data Movement by Analyzing HDFS Data In place

–  Expand Deployment and Integration Options

Rapid Adoption of R

Performance, Scale, Portability and Enterprise Assurance

Broad Adoption of Hadoop for Big Data Analytics

Hadoop

Hadoop Cluster

Edge Node

Data Nodes

Mapper Mapper Mapper

Parallel Algorithms Running Hadoop Transparent Distribution of Computation

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Master Process

Reducer

Mapper

Desktops & Servers

Revolution R Enterprise

Demo

www.revolutionanalytics.com 1.855.GET.REVO Twitter: @RevolutionR

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Analytics Ingestion by BI Solution

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Review – What you just saw § RRE as an analytic engine § Built a model § Generated scores – likelihood to churn § Scores are shared with BI Solution using DeployR

–  Enhanced customer understanding via visualization § Scores can be used to optimize offers presented to customers

–  Customer retention offers, up sell/ cross sell, etc. § Retain your customers and increase their value

Thank you.