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Companies that want to be successful in the consumer IoT market need to redefine the customer service models and processes to provide an enhanced experience that customers demand.
Fremont, CA: The use of internet-connected devices offers improved efficiency and convenience to consumers. But the value for businesses is in the data that IoT devices and sensors generate.
For a data-driven IoT environment, organizations will be pushed to redefine the current policies and processes for data management, information security, service delivery, and support operations. Here are three tips on how contact centers can provide value in an IoT environment:
Human, Proactive, and Personalized Customer Support
IoT brands that offer a one-contract support experience will be a major distinguisher in retaining consumers in a competitive market. This will require contact centers to improve the frontline customer service agent’s position to a more consultative role that demands more critical thinking and problem-solving skills to address and solve issues throughout the IoT product landscape.
The contact center can help create customer loyalty and retention while decreasing repetitive calls by including customer education as part of the support interaction. As the interaction becomes more complex, agent performance metrics need to be reviewed to provide support, such as focusing more on outcome metrics like customer satisfaction and Net Promoter Scores.
Data Security Protocols and Customer Trust
Cybercriminals widely target ioT devices because they are easy to hack into. The more devices they have connected, the higher the risk is as it offers an entry point for hackers.IoT contact centers need to actively inform customers about privacy and data security protocols during the onboarding process and during customer support interactions to build consumer trust. Additionally, frontline agents need to follow customer authentication protocols and educate customers on keeping their devices secure.
Investment in People and AI
To obtain value from the significant amount of real-time data that IoT sensors and devices generate, investing in artificial intelligence (AI) and machine learning technology is important to monitor, sort, and group the data. Another critical factor is to find and retain the analytical talent needed to obtain actionable insights from the data, becoming an AI deployment pain point for many companies.
Organizations need to close the skill gap by training employees with a background in statistics and data management or creating a job-sharing arrangement with business partners or other companies in the product ecosystem.