Governments have a challenge understanding and using the huge amount of data they are bombarded with daily to make better decisions and better serve their citizens.
Now, I want to look at how one major Canadian city is actioning intelligence from this data to drive significant efficiencies.
One area that government and public sector organizations continue to have trouble with is understanding exactly why their customers are contacting them. While customer service employees can and should correctly categorize each contact, they usually don’t, which leaves customer service directors with only a partial view.
This major Canadian city answers approximately 1.5 million calls every year, 70 percent of which are general inquiries and 65 percent of which fit into more than one category. Not even the best agents correctly categorize every call, which means this city didn’t know what all of their calls were about, making it hard for them to plan effectively.
However, the city knew that it could gain a complete picture of what customers were calling about if it could somehow extract the valuable information held in its call recordings. I refer to this valuable information as “dark data,” because it is not easy to get at.
This is where speech analytics comes in. It “shines a light on the dark data,” helping to enable organizations to understand what is really happening in their customer service centers.
Verint’s speech analytics solution not only identifies transactional categories, such as the number of complaint calls, but also identifies behavioural categories, such as the number of “emotional” calls, the number of call transfers and the number of callers put on hold.
The analysis of transactional and behavioural activity derived from unstructured data has enabled this city to take action in a variety of ways. First, it is identifying opportunities to improve customer satisfaction by giving agents the information they need to help lower levels of complaint and frustration. Next, it can more accurately categorize call volumes for internal billing. And, finally, it can help identify spikes in calls about specific topics and either assign them to the most appropriate agent or redirect them to the Web— something that can help reduce call demand significantly.
Taken together, this type of analytics enables this city to drive efficiencies on an ongoing basis—and to help manage demand through optimal staffing of resources and use of the Web.
By using speech analytics, this Canadian city is not only becoming smarter but also empowering its agents to be more efficient and provide the exceptional service its citizens demand.