Increase Contact Center Effectiveness with Big Data Analytics
Effectiveness of customer contact center agents is commonly based on metrics such as AHT(Average Handle Time), CSAT (Customer Satisfaction), CPC (Cost per Contact) etc. Established vendors in the contact center space have traditionally focused on these metrics from a long time. Several such vendors solve performance questions through sampling large and segregated data sets ignoring the big data approach, making a contact center more tactical to the company rather than strategic.
Contact centers collect huge volumes of structured and unstructured data through the course of their daily operations from sources like telephony equipment, CRM systems, call and screen recordings. Thus contact centers know a lot about the customer, information such as what product and when the customer bought it, how loyal the customer is to the company and if the customer has had any bad experiences previously with the company and of course they know where the customer lives from the demographic databases they own. Who is keeping these recordings, and what are they doing with the conversations, other than having a manager listen to them periodically to make sure the call center personnel are sticking to script? Big data is about being able to identify the conversations that include the customer using, say, the words "never again," or "no way" or any such key words. When we talk about unstructured data, those recordings fit the definition.
In the advanced world data consumption has gone up and a report from the UC San Diego released in 2008 said that an average American consumes 34 gigabytes of content in a single day. With abundant data available and consumed voraciously by the customer, when someone makes a decision to reach out to the contact center, the customer in most situations will have as much information as the contact center agent they reach pushing the contact center agents to be better informed than they already are with no room for responses as:
The customer already assumes the contact center agents to be the master of Big Data, which only leads to frustrated customers when agents fail to help them. The helplessness of the contact center agents stems from the fact that the customer intelligence data available to them is incomplete or not instantly accessible during a call. The agent might miss an up-sell or cross-sell opportunity or even lose a customer if the agents are provided single view of data about the customer.
It is time to focus on utilizing the big data we have and empower the contact center agents to enhance customer experiences. Once the agent receives the call, the rep should have a screen full of visualizations showing the customer's history and preferences, based on general activity on his account, what the system has been able to determine from previous calls and likes/dislikes about the company in the social media posted by the customer.
1) Data consumption by UC San Diego
2) Contact center metrics from Techtarget.com
3) A Blog on Holistic medicine for your call center
1) Saama SixthSense - Download a Point of View Presentation
2) Saama’s Data Scientists