As Mobile Devices and Software Upgrades Make Their Launch, AI and Predictive Analytics Provide A Helping Hand
The recent mobile device launch of the Galaxy Note 8 and Apple’s software update of the iOS 11 for iPhones and iPads have mobile users excited to see what features will benefit them in their tech-savvy lifestyles. As these new tech devices and features roll in, so does the frustration of troubleshooting and other concerns.
When Apple released the new iOS 11 software update, there were already millions of downloads by users within minutes of the drop. Aside from the iPhones small feature upgrades, there where no major changes to device but the iPad revealed noteworthy upgrades to features such as digital scanning, the Apple Pencil, and the ability to multitask in between apps.
As these features presented themselves, so did the need for customers to understand how to use them, leading to common questions such as:
“Do I need to upgrade my device to get the new iOS?”
“Why can’t I update to the new iOS?”
“I updated to the new iOS and don’t like it, how do I go back to my old iOS?”
Call centers have already began preparing for a heavier amount of customer service requests just as these upgrades were being downloaded onto customers’ devices. With help from Artificial Intelligence (AI) and Predictive Analytics, call centers are able to access these technologies from prior device launches and software upgrades to prepare themselves, as well as retailers and carriers for the upcoming inquiries.
Widely known for their overheating issue that made mobile news on the Note 7, Samsung took the advantage of utilizing AI during the Note 7 launch to collect incoming questions and concerns regarding the overheating of the device.
Solutions for the problem began formulating by customer support in preparation of the incoming calls on the issue.
This assistance in predicting the subject matters surrounding new devices and software updates is a game changer for a lot of brands. AI technologies are also being used by agents in call centers as a “co-pilot” when resolving customer problems. At times, agents are unable to answer customers questions fast enough and have to either put a customer on hold, a trigger to customer frustration, to find an answer or transfer the customer to someone else, even more frustrating.
With an intelligent digital assistant, call center agents are able to retrieve the correct solutions, guiding customers through their support journey effectively, resulting in satisfying customer service. As more service methods follow this path, the amount of happy customers rises and so does their loyalty to a brand.
As AI reigns success for agents, it also is available for customers to utilize in their self-support journeys. Self-support materials such as product guides, tutorials, spec sheets, FAQs, and videos are all accessible for customers to self-troubleshoot at their convenience. There is also the availability of chatbots, machine learning bots who can direct customers and provide them with the solutions they need, without needing to make a phone call.
The effect of these available online support materials have created a new standard of what customer support should provide. In a recent industry survey, 66% of brand marketers said a small amount of customers, even close to none, made any attempt for a follow-up purchase because of the lack of online interaction methods in the customer support system.
The movement of AI and Predictive Analytics in the customer support industry gives opportunity for agents to successfully assist customers with questions with their newest mobile device or system upgrades or inquiries about the device or upgrade before action is sought to obtain it.
As the customer to agent interaction becomes more personalized, so does the relationship between a customer and a brand. These relationships provide greater results for manufacturers, carriers, and retailers in the industry of mobile technologies.