Predictive Analytics and the Samsung Galaxy S8 Product Launch

When it comes to smartphones, the competition has gotten fierce. Sure, the focus remains squarely on how pretty the device is, as well as its new bells and whistles. And for this reason, the Samsung Galaxy S8 has started off on the right foot, other than a few launch hiccups.

For the most part, it’s been a success for Samsung. However, there may be another reason why this device will experience success and put pressure on its competitors: The customer service experience might finally be headed in the right direction.

Customer Service Strategy Now A Priority
Customer service is often looked at as a supporting cast for a smartphone. Traditionally, the role of customer support has been relegated as a priority, but only when something has gone wrong with the product.

Times may be changing, though, and we should stop to look at the customer support strategy that has been implemented for the Samsung Galaxy S8.

Many organizations, especially for mobile and technology, are now viewing tech support in a more proactive manner rather than a reactive component when things go wrong. Predictive analytics, self-support online digital materials, and machine learning are increasingly being utilized for customer service inquiries.

Using Predictive Analytics and Machine Learning
For the Samsung Galaxy S8, carriers and manufacturers utilized predictive analytics and focused on customer service launch insights from previous smartphones to better understand patterns that would help steer where certain customer demographics would most look for help materials on the latest smartphone – the Galaxy S8.

For example, younger age groups have traditionally been likely to download online support materials that are for technical areas of the phone, like customizing the smartphone, configuration, and accessing/programming of the SIM card. Older age groups have been more likely to have support needs in areas of device operation, such as making a call, setting up voicemail, and setting ringtones.

What We Can Take Away From the Latest Device Launch
Many of these areas were expected to be a large part of customer support requests for the S8 launch, but the device also offered a bevy of new features that required a more predictive analytics approach to customer support trends.

New features like Bixby, the intelligent assistant; and a new iris scanner were expected to require a lot of support because of the hype surrounding these features.

However, it turns out that Bixby wasn’t available as a “ready feature” during the launch, and the majority of carrier agents were instead focused on security-related matters as a larger need for tech support. At the time it was difficult to argue this approach given the sensitivities around device security. What’s more, carrier agents also planned on the more traditional device support areas more focused on operations.

However, data from customer support downloads pointed to a different trend. While Bixby wasn’t immediately made available as a live feature, it was the largest customer support material downloaded. More than 40% of the device’s support downloads were for Bixby.

In fact, security, which agents had planned as the top customer support need expected, was actually third behind Bixby and general phone set-up and troubleshooting concerns.

Machine Learning For Future Launches
Machine learning, predictive analytics, and the ability to track customer support material downloads will play an increasing role in the overall customer support strategy, leading to a better customer experience for brands. The ability to engage with these resources means brands can do a better job planning launches more effectively, and evolving their omni-channel strategies beyond just sales to also include customer support.

This type of approach is key because the right customer support experience can help brands expand revenue opportunities in front of existing customers, and help with retention strategies down the road when future devices are launched by competing brands.

About the Author: 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 www.devicebits.com.