Seeing Both Sides of the Coin

Customer interactions today produce an unprecedented amount of rich data, from a host of channels and across periods of time. That’s got to be a good thing, right? ​

Yes, but. 

We need to know what we’re looking at. To get the most out of these waves of structured and unstructured information (phone calls, emails, chat, and feedback forms), we need the most comprehensive analysis possible. That means understanding both the customer’s behavior and that of our agents. 

Interaction analytics is the only tool to transform customer interactions – all types of them – into coherent, actionable metrics. Yet, without an idea of how effective our agents really are, or could be, the picture is very incomplete.  That’s where desktop analytics comes in.  

In combining desktop analytics and interaction analytics, the value of each is multiplied. The quality of the connection between ‘said’ and ‘done’, between customer expectations and experience, is revealed. The result is the ability to fully meet customer needs and improve business processes. 

That’s the theory, anyway.  But how do these two analytics technologies reinforce each other in practice? 

As it turns out, in very many ways…

Increasing Sales
Sales effectiveness cannot be determined by conversion data alone, as attractive a measuring stick as that may be. Because it may completely miss things like long-term customer satisfaction, which types of customers are not converting and why, policy or regulation compliance issues, and possible procedural weaknesses. 

In order to best support our agents, which will increase sales, we need to distinguish between ‘will’ and ‘skill’ gaps. For that, we must correlate the strengths and weaknesses of our agents, policies, procedures and software. This can only be objectively accomplished with a combination of interaction and desktop analytics. 

Better Regulatory Compliance
For compliance record-keeping, desktop monitoring is an excellent tool. But only interaction analytics can identify customer language that might indicate complaints that were ignored or incorrectly logged as a compliance issue. The consequences for not having such a failsafe can be penalties, ruined customer experiences, and a tarnished reputation. In addition, an automated library of complaints that can be cross-referenced with desktop analytics data provides regulators evidence of our efforts to adhere to relevant regulations. Even better, it can raise red flags for impending regulatory infractions before they happen.

Have you ever had a professional surprise seeing both sides of the customer service coin? Tell us about it. In our next post, we’ll look at a few more examples of how a combined approach works in a typical contact center.  

And if you’re interested in learning more about how interaction and desktop analytics can change the way data is used, click here to download our free white paper​.​