Big Data Market Sees CSC Buy Infochimps, NICE Buy Causata
In other big data market news, NICE Systems announced that it reached an agreement to acquire Causata, a provider of real-time big data analytics technology. The acquisition will allow NICE to offer solutions that provide greater visibility into a customer's activities on the Web and apply the insights from that data in real time, across other touch points such as the contact center. These solutions are further augmented by Causata's Web-based predictive analytics and machine learning technologies, which, when applied to terabytes of information, enable organizations to improve real-time decision making and guidance. NICE will benefit from Causata's real-time Hadoop-based interaction repository, dynamic customer profiles and Web personalization, the company said. "The acquisition of Causata demonstrates the high demand we are witnessing for big data applications," said Omer Trajman, vice president of operations at WibiData, a big data applications provider. "Consumers are interacting with brands across platforms, and it is imperative that enterprises deliver a relevant and personalized experience across channels to remain competitive in today's market. Companies like Google, Amazon and Netflix have successfully leveraged customer data to serve their users better, and big data applications are the enterprise tools that can create this dynamic brand experience."The integration of Causata's Hadoop-based technologies into NICE's Customer Engagement Analytics platform generates new capabilities, including:
"One of the biggest challenges enterprises face today is the difficulty breaking barriers between the Web and assisted-service channels, such as the contact center," said Keith Dawson, principal analyst at Ovum, in a statement. "In order to truly understand the customer journey and get the most value from that understanding, companies must know what their customers are doing on the Web, as they do it. The key is to then share that insight with the sales, services, and marketing organizations, so that they can act in real time to deliver outstanding, personalized customer service and realize more sales opportunities."
- Creation of dynamic customer profiles based on real-time analysis of current and past activities over multiple channels;
- Convergence of self-service digital channels, such as Web and mobile, with assisted-service channels to better manage the customer journey;
- Ability to provide contact center agents with the complete context of an interaction, based on a customer's activities prior to and during that interaction; and
- Improved real-time decision making, using predictive analytics and machine learning, to guide employees to the next best action.