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Conversation Analytics: What they are and what they can tell you

For companies implementing marketing strategies that drive phone calls, Call Analytics can measure where calls come from and the volume of calls received. This can be very useful in measuring the effectiveness of marketing campaigns, but these metrics don’t tell the whole story. You know what drove the call to your business, but do you know what happened during the call?

What are Conversation Analytics?

Conversation Analytics – metrics that analyze and measure the business impact of what callers and agents say – provide information into why the call was made, the skills of the agent, the sentiment of the caller, and the outcome of the call. These insights provide a level of understanding only recently made possible by artificial intelligence and natural language processing, technologies applied to huge datasets of phone calls in near real time.

Conversation Analytics provide deep insights into the operational side of the sales organization, the environment where the crucial part of the customer path to purchase takes place. Once the caller leaves the marketing realm, companies can have a blind spot as to what happens next. In a world, where customer acquisition can cost 5x or more than customer retention, maximizing each opportunity through the entire sales process makes good business sense.

What can Conversation Analytics tell you?

Conversation Analytics are metrics derived from AI algorithms that analyze vast datasets of customer communications – typically phone calls – either in real time (no call recording required) or via analysis of converted speech-to-text scripts.

Analytics can provide insights into why a customer called: Was it was in response to a marketing promotion, for instance? They also measure caller sentiment: Did the caller have a certain attitude about a concern? Often, Conversation Analytics are used to optimize agent performance by automating mystery shopping programs that only score a sample set of calls. In fact, Conversation Analytics can measure every call. For example, it can highlight agent adherence to scripts and provide the opportunity to optimize those same scripts for high-intent callers. These analytics also provide a high degree of clarity into call outcomes. Did the caller abandon the call? If so, why, and what can we do to retarget them? And, if not, was a sales or appointment discussed?

With the advent of artificial intelligence and natural language processing, Conversation Analytics gives you the ability to answer these types of questions. Thus, Conversation Analytics should be a key component of any call-based business’s operations. It will help understand its audience better, provide an excellent customer experience when prospects connect and optimize marketing-driven leads for better business results.

To learn more, visit the Marchex Call Analytics 201 page.