As technology advances, we all have that utopian dream of having all our problems answered at a click of a button. No matter the difficulty. No matter the medium...instant solutions and quality experiences. Many believe that for customer service, Artificial Intelligence, or AI, is the future of customer service and maybe the disruption of the entire call center industry.
But, what is call center AI? Do you have to look forward to a robot selling you a timeshare? Do I have to start liking being stuck in an endless IVR; routing me to automated responses that don’t end up resolving my issue? Do we have to get used to washy, robotic, and thoughtless chat-bot responses? Many people have an augmented view of what exactly AI is, and more importantly whether or not artificial intelligence will have negative impacts on the future of contact center operations.
While many argue the introduction of AI in the contact center industry believe it will completely replace the role of live agents. In reality, the technology that AI brings call center agents only makes them more effective & efficient. Here’s a list of 5 reasons why call center AI is there to enhance, not replace agents. (P.S. you won’t be speaking to a robotic customer service agent anytime soon)
So, What is Artificial Intelligence when it comes to contact centers?
AI was coined in 1955 when scientists lobbied the Rockefeller Foundation to fund the Dartmoth Workshop. The Dartmoth Workshop was a two month long project with the purpose of, “finding how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves."
Over 60 years have passed since that defining moment, and with that time AI has been integrated into all of ours lives to make our day to day activities more streamlined and efficient. However, hollywood would make us believe we have not truly reached the concept of Artificial Intelligence filled with machines smarter and more emotionally intelligent than humans.
People and companies alike believe that AI is a saving grace– a system that replaces the human element, but keeps the human touch. Yet the real AI is somewhere in the middle. The middle ground of AI for many companies has been a smooth way to leverage a better customer experience.
In terms of AI in the Contact Center industry this enhanced customer experience has come in the form of programmed automation. Whether that be a live chat, programmed email triggers, or an IVR system. However, increasingly customers are left in the dust with the frustration that AI brings.
Many chat response systems do not have the machine learning capabilities to debut solutions to complex problems. Leaving customers stuck in a vicious cycle where they are fighting IVR systems & live chat systems just to finally get to a human responder.
Many see AI as the saving grace for contact centers. The data proves that AI is extremely helpful, but AI being the savior, this is simply not the case. For call centers, AI should be viewed as an enhancer, not an alternative solution:
1) AI is extremely expensive to fully implement
Many SMBs are worried about how the plan to upscale their customer service expenditures to interact with the evolving AI mediums. Customers exceedingly want faster solutions and for many SMBs with contact centers they rely on quality customer experiences to raise CSAT scores, create promoters, and lower churn. However, is the rising expectations of customers worth shelling out thousand, if not hundreds of thousands, to implement an AI system?
Data is very important here. Knowing who your customer base is and why they contact you is extremely important. For SMBs with an older base–odds are keeping your contact center is going to be extremely important. According to SoftwareAdvice, 63% of people over the age of 35 prefer human interaction in the form of a phone call compared to an automated live chat. (Survey)
David Brown, a customer experience expert, attended the 2016 TaskUs’ CxSummit. At the event one of the main topics was AI and the impact that machine learning has on the customer experience (specifically contact center related). “AI was a huge focus of CxSummit. However, one thing was very clear regarding AI and contact centers. Unless you have an insane volume of orders...we are talking tens of thousands of tickets or orders per month, then AI simply is not worth the money and manpower to implement at this time.” Brown said.
2) Contact Center AI technology is not there yet.
Going back to the definition of AI a key phrase is missing from the equation: “improve themselves.” In today’s tech, this is known as machine learning. As stated in #1, properly setting up the systems that require AI and the automation that encompasses it takes a vast amount of resources. These resources are not limited to what’s in your pockets.
Currently, the aspect of machine learning & real AI is only as good as the implementer. Meaning all the systems in place for AI in call centers are all set up by managers and subsiding departments. This gives customers an experience only as good as what is in front of them. Thus, leaving the door open for many customers to simply not have a real solution to their problems. Let's say your system utilizes keyword detection– a customer might be typing “set-up phone” and be linked to a result that did not really answer what the customer wanted. The user would then have to go into the system and manually trigger a different result based on new keywords. Whereas the ideals behind AI and machine should really have a self taught system smart enough to correct itself.
Bobby Hakimi, SVP of Research & Development at Convoso, studies the industry everyday and realizes the ups and downs of AI. “AI as a term kind of just gets thrown around a bit too much. When really the current state of AI is just a system that pulls from a database. However, building that database takes immense time and valuable resources.”
3) Streamline your lower level inquiries
When it comes to sales and customer support, there is no doubt that people still prefer human beings over automation. However, this does not mean that AI should not be used to make the lives of agents much easier. Currently, there are many contact center solutions that you can use today that will help streamline your operations. Whether it is as simple as setting up an online FAQ form to getting a system with IVR capabilities. Make those easy answers easily accessible to your customers. More importantly, make the process of customers calling into your operation one that is necessary & relevant.
4) Sophisticated technology requires sophisticated answers
Odds are when you were contacting support on your flip phone last decade–your problems were much less complex than the issues your technology gives you today. This is simply due to the fact that the advancements of technology are growing exponentially. This expansion in technology has set a precedent for contact centers: sophisticated technology requires sophisticated answers. The types of answers that are only capable by real live human agents.
As much as owners would like all their issues resolved by an FAQ page– odds are there is no way to answer the vast complexity that your customers truly need. For your call center, this means developing a system that can streamline lower level inquiries but can handle higher level concerns.
Online retail customer support is a good testimonial for technologies limitations. Average hold time (Queue Time), a major contact center KPI, is at 1 minute and 51 seconds when on the phone with an automated system. However, customers calling into live agents only experience a hold time of 51 seconds. (Source: Time) Proving that sometimes a customer's fight through automation can easily be tackled by a human-being.
5) AI is a complement to your contact center operations. Not an alternative.
Currently, Contact center solutions offer many of the automation features that SMBs are striving to achieve when looking for AI. Whether that be IVRs to advanced scripting capabilities.
AI can also be used to enhance every customer experience. As many voice recognition softwares now can read vocal queues and record customer experiences– thus offering actual data to customer reactions & frustrations they call in for. This kind of speech analysis tries to go beyond what customers say to understand how they say it. This type of technology can help automate your system as you build up your database to realize what kind of communication certain age groups like/dislike.