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.
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 
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.