Analyst Perspectives

NICE Systems is well known in the contact center market for its suite of workforce optimization products. However, over the past several months it has gradually been expanding out of the pure-play contact center market into back-office and mobile applications, as well as the broader market of customer interaction handling. My research on the contact center in the cloud shows that customer interaction processes are getting more complex as customers demand faster, more personalized responses, interactions occur through more communication channels, and more lines of business are involved with interaction handling. My recent benchmark research shows that companies are becoming increasingly reliant on analytics to monitor and assess how well they are performing these critical tasks and in what areas they need to improve.

NICE Systems recently announced that its interaction analytics product now incorporates IBM’s big data analytics platform, enabling it to process the increased volumes and types of data generated by newer forms of customer interactions such as text and social media. It was therefore somewhat surprising when it recently announced its intent to acquire Causata, which makes a customer experience management product. On the surface, the Causata product looks like a big data product that focuses on processing multiple forms of customer data and producing analysis of that data that can be visualized in many different ways. And again, on the surface, this is what it does. However, as with many acquisitions, this raises the question of how the product fits with NICE Systems’ existing systems and the company’s overall strategy. To help explain the move, the company emphasized during a recent briefing that it is not about acquiring market share. Rather, it said the acquisition is intended to expand the types of data NICE Systems can include in its interaction analytics and add predictive capabilities that are enhanced as the system learns from previous analysis, producing outputs that can be used to support a wider range of activities.

Two particular new sources of data are web clicks, which means the product can capture at a click level which fields a user uses on the company’s website, as well as machine events such as data produced by sensor equipment. It also can rationalize customer identities to tie together different interactions from different communication channels. For example, it can recognize that a tweet from a defined Twitter handle has been made by a known customer in the company’s CRM system. In this way, a customer’s past and current interactions can be processed by one of the specialized predictive models to produce an understanding of the customer journey, customer value and likely future behavior. The outputs can thus be personalized for the unique customer ID and input into personalized web experiences, targeted marketing campaigns, next-best offers, and highly targeted social and mobile marketing messages. All of these capabilities not only add to NICE Systems’ existing functionality, but also support its journey away from what has been seen as contact center activities.

However, the acquisition brings with it a number of challenges, including overall integration of the products and usability, as well as the question of which big data platform to standardize on. Apart from these issues, the eventual products will address a number of hurdles companies are now facing. My research on the contact center in the cloud shows that companies now support on average nearly five channels of communication, each with its own unique data formats and customer identifiers. Add those channels to all the other sources of customer data, such as CRM and ERP systems, and producing the so-called 360-degree view of the customer – let alone predictive models and personalized outputs – becomes extremely difficult.

As such, the Causata acquisition is a good step in the right direction for NICE Systems to continue to advance its offerings for a new generation of customer analytics. The company’s resulting analytics products are set to enable superior customer experiences, based on in-depth analysis of greater volumes and types of data that will help organizations engage with their customers.

Regards,

Richard J. Snow

VP & Research Director