Multi-Experience Enablers Part 2: Communication Analytics
While omnichannel focuses on touchpoints and channels, multi-experience is about doing the right things for customers at the right moments in their journeys.
It might sound simple, but it’s not. To be able to anticipate customer behaviors and needs, to personalize engagement at the micro level, to preemptively resolve issues, to proactively offer the next best action, organizations must entirely master their data. The ability to collect, process and react to data is the most important component of multi-experience.
And one of the best sources of data on customer behavior can be found in s the conversations that customers have with company representatives across various channels. Valuable information is hidden in thousands of hours of phone call recordings and gigabytes of textual conversation transcripts. The difficulty comes in leveraging that data to improve customer experience.
This is where communications analytics solutions come in. Complemented by related data and root cause mining modules, these solutions convert the enormous datasets concealed in customer conversations into actionable insights that organizations can leverage for making decisions and executing actions.
The Role of Communications Analytics
Indeed, communications analytics represent one of the key technologies for enabling multi-experience. Taking one example, predictive analytics systems, which represent the brain of multi-experience, rely on high-quality data to identify customer wants and needs, and to propose the next best action that the agent or organization can take to address those needs. Communications analytics solutions provide that high-quality data.
Communications analytics can also quickly uncover the root causes behind customers’ complaints and compliments, providing organizations with clear directions on where to focus their CX-related efforts. Communications analytics can also surface the differences between successful and unsuccessful sales contacts, helping organizations to improve agent training and remove any gaps from their processes and procedures. The same goes for customers that experience (or do not) first-contact resolution.
Communications analytics also represents a game changer in both workforce engagement and CX management, which are themselves critical for the successful delivery of multi-experience.
In short, communications analytics helps companies to manage their performance on an entirely new level.
Going beyond NPS
Today, the majority of organizations use the Net Promoter Score (NPS) to measure customer satisfaction, loyalty and overall experience. While NPS provides a solid numeric indication of an organization’s ability to fulfill its customers’ expectations, it doesn't specify the reasons why customer give particular scores. This means that NPS cannot tell the company what to do in order to improve the experience of its customers.
It’s the same story with voice-of-customer surveys, the most common method for the assessment of CX today. If we take for granted that CX happens on three distinctive levels – effectiveness, ease and emotion – then we can see where these surveys work well. On the effectiveness level, for example, it is easy to ask customers if a particular product or service meets their needs. And on the ease level, we can ask customers to rate how easy it was for them to interact with the company.
However, surveys don't work well on the emotional level for a number of reasons. For many individuals, it can be difficult to define and rate their emotions, while some don't remember how they felt, or simply don’t want to discuss their feelings. But guess what: According to Forrester, emotion influences loyalty much more than other two levels of CX, so we need a way to measure it.
As it clearly identifies the root causes behind customers' satisfaction and dissatisfaction, communications analytics answers this need. Not only this, but it determines good and bad practices, and provide straight-forward guidance for CX management, dramatically improving existing processes.
Because of this, it is my view that, in the coming years, communications analytics will be the difference companies leading CX and those who are lagging.
An excellent example of the game-changing nature of these capabilities can be found in the realm of traditional quality management. The problem here is that quality specialists can only evaluate a very limited number of contacts (usually less than 1%), meaning large numbers of important insights are lost. By combining communications analytics with a traditional QM solution, organizations are able to automatically analyze and evaluate all customer interactions. Consequently, relevant decisions are based on full operational insights without losing important information because of sampling.
In the multi-experience world, CX depends not on a platform’s features (features are everywhere) but on a platform’s ability to collect data, process it and react to it. Communications analytics enables organizations to master their data and to, consequently, excel in the multi-experience economy.