Contact centres, like most contemporary companies, have to deal with ever increasing quantities of data, with the number call recordings, analytics and other metrics being added daily.
Most companies battle to work through the data they accumulate each day, let alone make sense of it or use it to improve customer service or agent productivity. With speech analytics for contact centres this needn't be the case.
Inaccurately assessed data
Quality management in contact centres is usually done by examining a handful of sample calls from each agent. This approach means potentially problematic calls or agent habits might not be picked up, and that analysis and assessment of service quality, potential up-selling opportunities or other call-specific factors can only be assessed retrospectively.
Speech analytics solutions make it possible to analyse customer behaviour and agent responses in realtime. This means its possible to flag, for example, a disgruntled caller during the call and notify a team leader or prompt the agent to offer various potential ways of resolving the caller's complaint.
It also means quality management can be extended to every single call rather than simply a small selection of them. This allows for more agent-specific training and also enables a contact centre manager to measure the effectiveness of training after the fact.
Speech analytics is not a one-size-fits-all solution and has to be customised to each contact centre's needs. However, once properly customised and implemented, a speech analytics solutions should be able to recognise what the correct answer is to a customer's question and whether or not the agent offered it.
Where analytics are concerned on-premise solutions tend to be best because of the processing power required. Solutions like those from Genesys and Verint integrate seamlessly with existing switches or recording solutions a contact centre might have.
The power of analysis doesn't stop at voice. The very same applications used for speech analytics can be used to analyse text using the same rules and phrases. This move to "interaction analytics" makes it possible to monitor social platforms like Facebook and Twitter, and application programming interfaces (APIs) mean most solutions can be adapted to additional channels as desired.
It's something of a business maxim that it's easier and cheaper to retain an existing client than to try and win over a new one, which is just one of the reasons analytics systems are becoming so popular. Improved responsiveness, customer service and complaint resolution is one of the easiest and most consistent ways to maintain customer loyalty, ensuring repeat business and maintaining a company's reputation.
Moreover, consumers have become far more demanding of good service than they used to be. Some argue that by the time a customer calls you an opportunity has already been lost. If, for example, someone wants to buy something they tend to research it online, then try to find it for online purchase or in a physical retailer. Many consumers will only pick up the phone as a last resort, which makes it imperative that by the time they do call the person on the other end of the line is able to help them.
As speech and text analysis improves the range of information that can be processed and the range of feedback that can be provided subsequently will increase dramatically, but it's already clear that analytics is offering contact centres another tool to improve efficiency, bolster customer service, reduce caller frustration while increasing retention, and service callers more effectively by providing pertinent information and responding to their moods, needs and annoyances.
Posted on 24 Jul 2014 14:00