Artificial intelligence (AI) is defined as being “the ability of a machine to perform at the level of a human expert”. We have recently seen an example of this come to the fore when Google-owned DeepMind’s program AlphaGo beat the reigning world Go champion, Lee Sodol, 4-1 in what many consider to be the most difficult game in the world.
Traditional business use of the telephone as a major business tool involves two parties. A debt collection agent tries his or her best to “encourage” a client to pay their account. A sales rep attempts to entice a lead to purchase their product. A customer services rep works with an existing customer to solve a specific problem that they have. Most, if not all, contact between the two parties is restricted to the telephone, without any visible body language, which makes it more challenging to understand — and at times it can seem like each party has conflicting objectives.
Overcoming Phone Agent Challenges with Technology
While technology has long been part of this process, it has predominantly been used for data collection and storage. This has changed recently, however. Firstly there is considerably more relevant data available now. While much of this would have been stored in the past, it was often not particularly accessible. An agent or rep calling a client would have a subset of the information available, but that is all. If the client gave conflicting information in the call, no one may have ever picked it up. Also, there was a reliance on agents, reps and clerical staff typing information into systems. Any other data simply remained unrecorded. In recent
Also, there was a reliance on agents, reps and clerical staff typing information into systems. Any other data simply remained unrecorded.
A Smarter Way to Close Customers
In recent years there have been lots of solutions developed around buying lists, qualifying prospects, using social media but little around capturing the engagement of the customer with the phone agent. Voice analytics is being used to identify which customers are open to buying, transacting or paying off debt, but where the agent is not sufficiently skilled to move that customer to closure.
The clever part comes with the combined use of predictive analysis – a form of artificial intelligence. The software makes use of all available data, combining it with predictive models built around human emotions and behaviors. Predictive modeling utilizes past historical data and automatically builds strategies to predict future customer tendencies and expectations.
This software also utilizes any other analytics that a company may have – self-learning algorithms for instance – to constantly improve its own performance. In many cases, you can simply rely on the software with little need to use a dedicated analyst.
Of course, a specialist analyst may come up with the same conclusions, given enough time. By then, of course, the lead may have chosen to go with a competitor, the upset customer may have become an ex-customer, and the poverty-pleading new Mercedes-owning creditor may be happily paying off the $10 a week debt repayment that they negotiated with your naive agent.
Advantages of Artificial Intelligence in the Call Center
The key advantage of predictive analytics artificial intelligence software is that it can identify patterns in hours rather than the weeks or months that more traditional methods can take to come up with a conclusion (not necessarily the correct one).
This technology does, of course, collect data from both sides of telephone calls. Just as it can predict the likelihood that a creditor will pay their account or the probability that a lead can be converted into a paying customer, it can also analyze the agent or rep performances. For instance, are they engaging positively, with enthusiasm and confidence? Or are they robotic, monotonous and dismissive. This AI can become an integral part of agent quality performance.
With an artificial intelligence-enhanced predictive voice analytics in operation, you are not operating in the dark. Your call center can truly see, and understand, the behavior of all parties in your phone conversations. You can look past what people are saying and instead understand what they are feeling.