Nexidia Advances Customer Interaction Analytics

Nexidia is best known as a vendor of speech analytics. It was one of the first in this market, and a key differentiator is that its product uses phonetics to identify words and phrases embedded in recordings of phone calls. This capability has the advantage over standard word and phrase spotting because users don’t have to create a dictionary of words they want to spot. Thus the software can analyze calls and identify their content without users having to predetermine what it should look for. The system can also index recordings based on the results of this analysis so that users can search back through the recordings to carry out more detailed analysis of calls they are interested in. Over the past few years Nexidia has advanced its product, now called Nexidia Interaction Analytics, to include other forms of text-based interactions such as text messages, chat scripts and social media posts. In addition to speech and text, it can include other customer and agent information to provide a full picture of interactions.

My research into contact center analytics, however, shows that the vr_bti_br_technology_innovation_prioritiesuse of analytics for interaction-handling is immature, with most companies using spreadsheets to produce their reports and analysis. Slightly more advanced companies have begun to adopt speech analytics to gain more insight from call recordings, but only the most mature companies can analyze text-based data such as email, letters, forms, chat messages and social media posts. But this situation is changing fast. My recent research into the contact center in the cloud shows that more companies are adopting analytics for text, agent desktops and social media, and more companies are looking for predictive capabilities.  This shift is further reflected in our research on business technology innovation, which shows that analytics is now considered the top  innovative technology trend to improve business performance.

Many companies have progressed from using manual processes to evaluate small, random sets of calls, to more targeted listening driven by speech analytics,  and now want deeper analysis of more interactions, including predictive modeling so they can focus on specific issues such as agents that need special training or at-risk customers. Nexidia has been tracking these changes, and the latest release of Interaction Analytics includes capabilities to analyze interactions without using a dictionary; instead the software determines the interactions to flag based on key words and trends it spots. This points users to interactions they should examine, with the system flagging those of high relevance and interest. Interaction Analytics also supports predictive capabilities that look behind the analysis to discover what caused the customer to interact with the company, determine whether the interaction is part of a trend and flag the required action.

Nexidia has worked to ensure that its software is highly reliable and returns accurate results, doing much of the work so that users can effectively pinpoint where they should focus. The software is designed to work in real or near-real time and process very large volumes of data, and it can be deployed on-premises or in the cloud. Our research shows that these types of capabilities benefit users by delivering results based on more up-to-date data and making information available in a more timely fashion.

But improving the use of analytics is not just about the software but also people and process. As well as showing that the dominant product used to analyze interaction-handling is spreadsheets, our research shows that the majority of companies don’t have a specialist team to carry out this task, relying instead on the contact center management team. To help companies overcome this lack of skills and experience, Nexidia has created a professional services team that has in-depth knowledge of analytics. It can help customers set up the software, identify areas to investigate and interpret the results. Better analytics is also about process, understanding why an interaction occurred and raising actions, alerts and workflows to ensure action is taken based on the analysis. For example, certain agents may need extra training, common product issues need fixing or user guides need improving. This is part of my focus into next generation customer analytics that will provide some insights on the latest on the required skills and processes.

My research into customer analytics shows that one of the primary reasons companies have been slow to adopt is advanced forms of analytics that the majority remain fixated on efficiency and therefore focus on low-value metrics such as wait times, average call-handling times and transfers. Here again, more mature companies recognize these measures are no longer sufficient and have begun to adopt more business- and customer-focused metrics such as first-contact resolution, net promoter scores and customer effort scores, and to link these to interaction-handling performance. These metrics are more complex to produce, which is driving the adoption of more advanced tools such as Nexidia Interaction Analytics. In today’s competitive business environment, companies need to use a balanced set of metrics, adopt the tools that can produce them and put in place processes to take action on the results. As companies do this, they should investigate how Nexidia’s products and services can help with these efforts.


Richard J. Snow

VP & Research Director

Pentaho Doubles Down on Unifying Big Data and Business Analytics

Pentaho recently announced Pentaho 5.0 which represents a major advancement for this supplier of business analytics and data integration software as well as for the open source community to which it contributes and supports. In fact, with 250 new features and enhancements in the 5.0 release, it’s important not to lose the forest for the trees. Some of the highlights are a new user interface that caters to specific roles within the organization, tight integration with emerging databases such as Mongo, and enhanced extensibility. With a funding round of $60 million coming less than a year ago and the growing market momentum around big data and analytics and it appears that Pentaho has doubled down at the right time in its efforts to balance the needs of the enterprise with those of the end user.

The 5.0 products have been completely redesigned for discovery analytics, content creation, accessibility and simplified administration. One key area of change is around roles, or what I  call personas. I recently discussed the different analytic personas that are emerging in today’s data-driven organization, and Pentaho has done a good job of addressing these at each level of the organization. In particular, the system addresses each part of the analytic value chain, from data integration through to analytic discovery and visualization.

I was surprised by the usability of the visual analytics tool, which offers a host of capabilities that enable easy data exploration and visual vr_ngbi_br_importance_of_bi_technology_considerationsdiscovery. Features such as drag-and-drop conditional formatting, including color coding, are simple, intuitive and powerful. Drop-down charting reveals an impressive list of visualizations that can be changed with a single click once. Users will need to understand the chart types by name, however, since no thumbnail visuals are revealed upon scrolling over and there is no chart recommendation engine. But overall, the release’s ease-of-use developments are a major improvement in an already usable system that our firm rated Hot in the 2012 Value Index on Business Intelligence, putting Pentaho on par with other best-in-class tools. According to our benchmark study of next-generation business intelligence systems, usability is becoming more important in business intelligence and is the key buying criterion 63 percent of the time.

Advances from an enterprise perspective include features that will help IT manage the large volumes of data being introduced into the environment through its support of big data sources and streamlining the automation of data integration. Capabilities such as job restart, rollback and load balancing are all included. For administrators, you can more easily configure and manage the system, including security levels, licensing and servers. In addition, new REST services APIs simplify the embedding of analytics and reporting into SaaS implementations. This last advancement in embedding is important, as I discussed in a recent piece that making analytics available anywhere is extremely important.

No discussion of big data integration and analytics is complete without the vr_infomgt_barriers_to_information_managementmention of Pentaho Data Integration (PDI), which I consider the crown jewel of the Pentaho portfolio. The value of PDI is derived from its ability to put big data integration and business analytics in the same workflow. The data integration through a user-friendly graphical paradigm helps a range of IT and analysts blend data from multiple platforms at the semantic layer rather than the user level. This enables centralized agreement around data definitions so companies can govern and secure their information environments. The Pentaho approach addresses the two biggest barriers to information management, as revealed in our benchmark research: data spread across too many systems (67%) and multiple versions of the truth (64%). While other tools on the market facilitate blending at the business-user level, there is an inherent danger in such an approach because each individual can create analysis according to the definition that best suits his or her argument. It is similar to the spreadsheet problem we have now, in which many analysts come together, each with a different understanding of the source data.

vr_bigdata_big_data_technologies_plannedIts depth in data integration is very robust and Pentaho  supports a range of big data which has been expanding rapidly to multiple data sources that are being used today and what our research found is planned to be used like Data Warehouse Appliances (35%), In-memory Database (34%), Specialized DBMS (33%) and Hadoop (32%) as found in our Big Data benchmark. Beyond these big data and RDBMS sources that are supported today, it has also expanded to non-SQL sources. The open source and pluggable nature of the Pentaho architecture allows community-driven evolution beyond traditional JDBC and ODBC drivers and gives an increasingly important leverage point for using its platform. For example, the just announced MongoDB Connector enables deep integration that includes replica sets, tag sets and read and write preferences, as well as first-of-its-kind reporting on the Mongo NoSQL database. MongoDB is a document database, which is a new class of database that allows a more flexible, object-oriented approach for accessing new sources of information. The emergence of MongoDB mirrors that of new, more flexible notation languages such as JavaScript Object Notation (JSON). While reporting is still basic, I expect the initial integration with MongoDB to be just a first step for the Pentaho community in optimizing information around this big data store. Additionally, Pentaho announced new integration with Splunk, Amazon Redshift and Cloudera Impala, as well as certifications including MongoDB, Cassandra, Cloudera, Intel, Hortonworks and MapR.

Currently the analytics and BI market is bifurcated, with the so-called stack vendors occupying entrenched positions in many organizations and visual discovery selling to business users through a viral bottom-up strategy. Both sides are moving to the middle in their development efforts and addressing the lack of data integration that is integrated in the Pentaho approach. The challenge for the traditional enterprise BI vendors is to build flexible, user-friendly visual platforms, while for the newcomers it’s applying structure and governance to their visually oriented information environment. Arguably, Pentaho is building its platform from the middle out. The company has done a good job of balancing usability aspects with the governance and security models needed for a holistic approach that both IT and end users can support. Organizations that are looking for a unified data integration and business analytics approach for business and IT, including advanced analytics and embedded approaches to information-driven applications, should consider Pentaho.


Ventana Research