Using Machine Learning To Elevate The Samsung S8 Customer Experience

The following is an exclusive guest contributed post from James Ramey, CEO of DeviceBits.

The Samsung Galaxy S8 launched to its expected fanfare, and so far many of the reviews have been mostly positive about the device. It is sure to be a smartphone that pleases its usual raving fans, and perhaps gives the device maker a chance to win over a few new ones.

While the device itself and its features – both upgraded features and new ones – are going to be a major reason why people love the device, there is another component that will likely play a key role in the customer satisfaction and experience:

The ability to properly offer customer and tech support on the new device.

Customer Service Strategy Equally Important As Sales

Tech support is often viewed as a supporting role in a mobile device’s life. Historically, both consumers and manufacturers/carriers view tech and customer support only as something needed when something goes wrong.

But the approach manufacturers and carriers take with customer and tech support has been changing over the last few years, and we began to see the results of this shift with the launch of the Samsung Galaxy S8.

Many brands, particularly in the mobile space, have started to look at tech and customer support as more of a proactive strategy rather than a reactive part of the overall customer experience. Machine learning, predictive analytics, online digital materials available in a self-service environment, and even chatbots are increasingly being used to help satisfy customer inquiries.

Machine Learning & Predictive Analytics

For the Samsung Galaxy S8, manufacturers and carriers leveraged machine learning and studied customer support launch trends from previous devices to better understand certain patterns that would help guide where certain customers and demographics would most seek support for the latest device – the S8.

As an example, younger demographics have been most likely to seek online support materials for help in more technical aspects of the device, such as customizing the device, configuration issues, and accessing/programming of the SIM card. Older generations 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’ve Learned From Samsung S8 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, because Bixby wasn’t going to be ready as a live feature at the time of launch, many carrier support agents were instead planning on areas such as device security to be a larger need of customer support – an area that has traditionally tracked high on customer support in the past. Agents were also planning on other traditional areas of customer support, such as phone set-up and operational troubleshooting.

In the first several days after the S8 was launched and made available to the masses, data from customer support materials downloaded suggest a different trend. Even though the Bixby intelligent assistant wasn’t immediately available as an operational feature, it represented the largest customer support request downloaded – more than 40% of downloads during the first weekend, according to number of downloads of the device’s digital support materials.

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.

Predictive Analytics 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.

The post Using Machine Learning To Elevate The Samsung S8 Customer Experience appeared first on Mobile Marketing Watch.

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