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The Latest Mobile Device Launches & Software Upgrades Aided by AI & Predictive Analytics


October 2, 2017 ( Newswire) New mobile devices and features are hitting the market, but with these technologies come the stampede of questions and concerns from customers. Often, the problems customers might have with their latest device or software are all too familiar to customer service agents and it is up to them to keep up with customer inquiries.

A great representation of the amount of mobile users begins with the recent launch of Apple's iOS 11 software update. Within just a few hours of the update becoming available to Apple customers, there were millions of downloads of the iOS 11 by users. As the iPhone did not undergo any critical changes, iPad users did notice new impressive upgrades to its features like digital scanning, multitasking in between apps, and the Apple Pencil. Because of the new features and upgrades on the iPad and iPhone, customer service agents can anticipate what kinds of questions customers will likely have.

"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?"

Questions like these, are already being anticipated by call centers, before mobile updates even hit devices. Call centers have began their collaborations with Artificial Intelligence (AI) and Predictive Analytics. Gathering data from previous device launches and software upgrades support the preparation of call centers, carriers, and retailers for the parade of questions to come in the future.

In the release of the Samsung Galaxy Note 7, customer support can be one step ahead in the overheating issue with the help of AI. As AI gathers the anticipated questions surrounding overheating of the device, call centers can prepare themselves with solutions to those future questions, without having to wait until the issue becomes widespread almost customers and the story hits newsstands.

Call centers are also benefiting from AI because of the Predictive Analytics that runs it. It is the use of data, aiding in the process of machine learning when computers and databases study previous customer inquiries, in the case of mobile technologies, the questions that come up concerning new product launches or software upgrades

Because call centers want to assist customers as quickly and efficiently as possible, they turn to AI to be there "co-pilot". These digital assistants can guide agents to specific answers to customer questions instead of putting them on hold to look for an answer and unfortunately, at times come back with a weak solution or no solution at all.

AI support systems also comes to the benefit of many consumers. For the select amount of mobile users, they are used to navigating through their devices on a daily basis, thus, they prefer to contact customer service via their device for quick service. However, the majority actually prefer to not speak to anyone at all, rather, they prefer something more a convenient support and avoid the calling process.

This preference is widely known as the self-support route. AI has made self-support an entity customers are used to interacting with. From machine-learning chatbots, to accessible online self-support materials such as FAQs, product guides, spec sheets, videos and tutorials, customers can put less of a weight on call centers.

According to a recent industry survey, 66% of brand marketers say that fewer to no customers, made follow-up purchases because of the lack of online interactions within the customer support session. This goes to show how much of an impact technology has today.

As customers have adjusted to using technology for support and call centers using the same technologies to better assist customers, AI and Predictive Analytics have led to efficiency in support and creates positive experiences for customers, and having them return for more products. This evolved support system benefits the business of manufacturers, carriers, and retailers.

Editor's Note: James Ramey is CEO of DeviceBits, a software company that services clients through a predictive and personalized understanding of interactive tutorials, adaptive FAQs, Interactive Guides, and Videos designed to for self-serving consumers. For more info visit - investing ideas in tech stocks- mobile payments, social media, AI and Robotics, Drone Stocks, GPS and more

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