Context Relevant yesterday introduced version 2 of its Predictive Machine Learning software and integration with leading CRM applications.
Version 2 provides integration with Salesforce, SAP, Oracle, and other CRM applications. These CRM integrations provide 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 their CRM platforms. 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 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 and 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.
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-premises 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.
"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, in a statement.
"We're seeing tremendous demand among customers to accelerate the manual and iterative processes of using data for profit," Purpura continued. "Our customers want analytics in near real time so they can engage the right customers at the right time and increase revenue."