NEW YORK -- (BUSINESS WIRE) -- Context Relevant announced version 2 of its Predictive Machine Learning software and integration with leading CRM applications at Strata Conference + Hadoop World. CRM integration provides version 2 users with better visibility into their own customer purchases as well as the ability to feed actionable insights such as prioritized opportunities back into a CRM platform. This new offering helps companies use predictive machine learning to identify customers who are ready to buy now and quickly act upon it.
“Context Relevant delivers a significant advancement for faster and more automated analytic insight,” said Michael Cafarella, Hadoop co-founder. Version 2 provides integration with Salesforce, SAP, Oracle and other CRM applications.
“By integrating CRM data with data stores from web logs, financial market data, SQL transaction data, other company data, and even social media, Context Relevant’s machine learning software lets companies predict who wants what products at what cost and lets their account teams take action,” said Stephen Purpura, Context Relevant co-founder and CEO.
Automate predictive machine learning
Context Relevant’s software with CRM integration is used by a number of the world’s largest banks, US retailers and global web brands to better predict what customers want.
“We’re seeing tremendous demand among customers to accelerate the manual and iterative processes of using data for profit,” said Purpura. “Our customers want analytics in near real-time so they can engage the right customers at the right time and increase revenue.”
How it works
Context Relevant works with data from anywhere and in any format. The predictive machine learning software seamlessly fits into the existing workflow. Pre-built applications address specific business opportunities such as optimizing pre-sales engagements with prospects and customers and detecting flash fraud & anomalies. The applications enable profit maximization on existing data stores, using the teams and tools that companies already have.
The software is built on a distributed, scale-out architecture designed specifically for computationally intensive machine learning tasks. Context Relevant scales to fit the size of any dataset, from an analyst's laptop to the entire datacenter.
On premise or in the cloud
Context Relevant predictive machine learning software accesses data from leading applications and map reduce engines in multiple formats and leverages distributed computing platforms. Context Relevant software can be deployed on the customer’s on premise servers or in the cloud. The software is highly scalable, with the primary scale drivers being dataset size and feature complexity during automated model building.
Customers can schedule one-on-one, live web demonstrations from Context Relevant data scientists by requesting a presentation by email (BigData@contextrelevant.com), phone (800-980-DATA) or online (www.contextrelevant.com).
About Context Relevant
The analytics software market is expected to grow at a 9.7 percent compound annual growth rate through 20172. Context Relevant combines data science with software development to let customers find actionable insight from huge stores of data faster and with less expense than ever before. Context Relevant’s predictive machine learning software automates analytics at blazing fast speed, making customers more nimble and accelerating their return on investment.
1 Gartner. (January 13, 2013). Gartner Predicts CRM Will
Be A $36B Market By 2017. Retrieved from http://www.forbes.com/sites/louiscolumbus/2013/06/18/gartner-predicts-crm-will-be-a-36b-market-by-2017/
2 International Data Corporation. (June 25, 2013). IDC Forecasts Business Analytics Software Market to Continue on Its Strong Growth Trajectory Through 2017. Retrieved from http://www.idc.com/getdoc.jsp?containerId=prUS24194613
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