Call Centre Analytics: Uses in Four Areas

Interacting with a customer care helpline or a call centre is usually a nightmarish experience for most of us.  People would often prefer to live with the problem rather than try to elicit support from some customer helplines, and are therefore held in contempt by many. Recent advances in data collection, data analysis, and artificial intelligence (AI) are being exploited by companies to improve the call center experience for customers as also provide valuable insights to companies. Let’s delve into four key areas where AI is used to transform call centres.

1. Supervisor alerts

Reports from different teams and agents are often received  and reviewed by the contact centre supervisors a bit too late to satisfy an upset customer or deliver the necessary training to an under-performing agent. Using AI, supervisors can quickly view trends and issues with the aid of real-time alerts  thus making faster decisions about when to intervene and help agents or customers. Now, how does this work? Alerts for keywords and phrases, such as ‘very unhappy’ or ‘cancelling my subscription’ can be set by the supervisors.  As and when a customer speaks these words and phrases the supervisors will receive a notification on their desktops. The system pulls up other relevant phrases that were spoken to indicate the reason for unhappy customers using real-time speech analytics. Supervisors can then decide the decision of whether  to step into a call to assist an agent or follow it up with additional agent training after the supervisor takes the call.  Further, on the occurrence, trending topics can be pushed to higher echelons of management  to enable them to forward data about issues to relevant teams and prevent escalation. For example, a sudden upward trend of the phrase “service  interruption” may lead them to discover a technical problem that impacts the entire organization. The above illustration depicts a  telephone customer wishing to cancel his phone service. Since the speech analytics tool picks up the phrases ‘cancel my service’ and ‘bill is too high’, indicating an aggrieved customer. That the customer is of high value, can also be seen by the supervisor and she can interject and forward a new plan option to the agent which is conveyed to the customer. Meanwhile, the customer doesn’t have to be put on hold as the agent receives the plan details almost instantaneously and finds a solution that ensures the customer is satisfied.

1. Context creation

It is important for any company to be aware of customer challenges and adapt accordingly. Therefore access to feedback in the form of latest data from the contact centres is required . Customers do provide a good indicator of satisfaction and underlying enterprise issues during their live conversations with agents. However, contact centres are usually located far away and cut off from the rest of the company , despite their agents speaking to customers on issues related to billing, sales or product knowledge. With first-hand knowledge of customers, their opinions and common queries, the company employees can act faster to benefit the business. Context can be used to, plan product changes, develop training programmes and discuss ideas in a collaborative environment by employees from various departments of the organisation. Simultaneously, agents can gain live updates on customer needs to enable them to respond better when new callers ask similar queries. In the illustration shown below, a customer calling about a potential weather issue triggers to help different teams put in place set processes for agents to carry out in the event of requests for  flight changes or cancellations. 2. Context Creation It is important for any company to be aware of customer challenges and adapt accordingly. Therefore access to feedback in the form of latest data from the contact centres is required . Customers do provide a good indicator of satisfaction and underlying enterprise issues during their live conversations with agents. However, contact centres are usually located far away and cut off from the rest of the company , despite their agents speaking to customers on issues related to billing, sales or product knowledge. With first-hand knowledge of customers, their opinions and common queries, the company employees can act faster to benefit the business. Context can be used to, plan product changes, develop training programmes and discuss ideas in a collaborative environment by employees from various departments of the organisation. Simultaneously, agents can gain live updates on customer needs to enable them to respond better when new callers ask similar queries. In the illustration shown below, a customer calling about a potential weather issue triggers to help different teams put in place set processes for agents to carry out in the event of requests for  flight changes or cancellations. Now, how does this work? Real-time tagging of audio content picks up particular key words and phrases and  ensures that trends are highlighted. Supervisors monitor these trend feeds and send relevant information to the knowledge team who update their documentation and share it with all departments. The context around customer queries is forwarded to agents and also used to create training or updates in real-time. Further, agents are also made aware of customer issues as and when they arise.      3. Process Improvements A critical aspect of customer service is a selection of suitable agents to the customer depending upon the nature of the query and after that providing the selected agents with the right information thereby reducing transfers and hold times. Voice triggers are used to find the right agent or set a process in motion, and customers will receive a more tailored experience, and agents will be able to assist them more effectively. By the use of speech tags and classifying customer information, companies can automatically match the most suitable and best agent to the call. Processes like pushing specific knowledge articles to an agent during a call are also started with the detection of keywords and phrases. Tagging data can also be used by managers to monitor individual tasks and how long it takes for agents to handle a particular query. This assists the managers to find roadblocks and make improvements.    4. Connecting customer journeys Integration of real-time analytics across social media, communities, chat, and within mobile or web self-service in addition to voice conversations should be in place. So that when customers switch channels, agents can view the most useful information  to them. For example, personalized updates can be pushed  to customers mobile devices based on their actions or a link can be sent to a phone when their issue requires a discussion with an agent. Agents should be able to  see the historical context about customer behavior on the web, alongside purchase history from the customer’s Customer Relationship Management record when they begin a chat or call with a customer . This empowers the agent   to provide personalized guidance and answer queries rapidly. If speech and text analytics are used together, Customers themselves can be sent articles or recommendations to their mobile device, based on the live agent discussion, if speech and text analytics are used together   Share this on


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