NICE is a longstanding provider of contact center systems. At the beginning of 2016 NICE acquired Nexidia, a provider of customer analytics, which raised questions about the future of the acquired company, its products and its customers. During a recent briefing SVP of product management Larry Skowronek discussed these issues. Nexidia now trades as “a NICE analytics company,” which is unusual because previous NICE acquisitions have been absorbed into the overall company and the brand effectively lost. This arrangement, Skowronek said, gives the company the benefit of retaining the Nexidia brand while taking advantage of the scale, financial strength and market presence of NICE. Several of Nexidia’s longstanding customers have remained customers and are benefiting from new developments and access to the wider NICE portfolio. The company also has a series of new wins, both as a result of direct efforts by its own staff and joint actions with NICE.
The business intelligence market is bounded on one side by big data and on the other side by data preparation. That is, to maximize their performance in using information, organizations have to collect and analyze ever increasing volumes of data while the tools available are constantly evolving in the big data ecosystem that I have written about. In our benchmark research on big data analytics, half (51%) of organizations said they want to access big data using their existing BI tools. At the same time, as I have noted, end users are demanding self-service access to data preparation capabilities to facilitate their analyses.
Price and revenue optimization (PRO) is a business discipline used to produce demand-based pricing; it applies market segmentation techniques to achieve strategic objectives such as increased profitability or greater market share. In essence, PRO enables companies to surf the demand curve using dynamic rather than fixed pricing to achieve the most desirable trade-offs between revenue volume and profit margins. The trade-off is defined by strategic factors such as the company’s market position, product and service portfolio, and marketing strategy.
Over the last few years the telecommunications and call center industries have undergone radical changes. Telecommunications was mainly in the hands of national and regional telecom companies, which essentially owned all the cables in the ground. The call center market was dominated by a small number of vendors that provided on-premises systems to manage and route calls when they arrived at a company’s offices. The telecom model was in effect the first cloud-based service, though almost no one stopped to think about how a call made on one device arrived at another. The arrival of the internet and wireless technologies and the telecom companies’ willingness to lease capacity on their lines changed both models. Now almost any company can provide communication services, and the majority of contact center systems are cloud-based. In this evolution some organizations that previously were hidden behind the telecoms have emerged as suppliers of communications and contact center services.
Topics: Customer Analytics, Customer Engagement, Customer Experience Management, Speech Analytics, cloud computing, Employee engagement, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Text Analytics, omnichannel, workforce optimization, analytics
Kofax offers Kapow, robotic process automation (RPA) software used to acquire information from a range of sources without human intervention and without having to write code. These sources include websites, applications, unstructured documents, data stores and desktop spreadsheets. RPA software does repetitive, low-value work that otherwise may be performed by person. It saves time in these tasks, completing them sooner and freeing skilled individuals to concentrate on work that utilizes their skills to the fullest. One of the earliest uses of software robots was “Web crawling,” which automated rapid collection of data posted on websites, for example, prices and locations. This was the Kofax Kapow’s original purpose, but its scope has expanded. When used to gather information from multiple applications, the software precludes the need for setting up and maintaining a separate data store. This saves time and money while ensuring that the information has come from the authoritative source and that there is no latency in the data. Rather than taking the time to write a program with broad applicability, a robot can be quickly configured to perform a specific task in a way that mimics how an individual does the job.