UJET Reveals Top Mobile, Cloud and Web Customer Service Predictions for 2019

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UJET’s Founder and CEO Anand Janefalkar has revealed his top customer service predictions for 2019.  Exceptional customer support will mean fast access to personalized, efficient, omnichannel service by phone, live chat and mobile app. Empowering more efficient interactions by enabling end users to verify their identity and share photos, screenshots and texts with support agents using a smartphone and providing contact center managers the visibility and flexibility to optimize operations in real time are an imperative.

Janefalkar has outlined the following eight major trends he sees in mobile, cloud and web customer service that guide his predictions:

  1. Companies will begin to treat customer support and communication as an integral part of the product and brand. Companies are beginning to take notice that you can create a cult-like following if you take care of your customers and don’t treat customer support as a checkbox or a cost center. It’s long overdue that companies view customer support as an integral part of the product and brand.

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  1. Blending of different technologies in cloud computing space is going to continue and accelerate. In the computing cloud space, we’re seeing a trend of companies integrating their technology with devices like Alexa and Google Home that consumers speak into. We see brands, solutions providers and devices coming together and this will evolve faster and faster. Unless communications solutions providers fully leverage new capabilities and services, they’re not going to be in the forefront very long.
  1. Organizations will continue to move to cloud-based customer support solutions. Cloud-based solutions expedite digital technology progress at an exponential pace. Which companies are consumers going to recommend to their friends, family and co-workers? It will be the companies that have the best customer onboarding, support and transparency. We believe that the recipe is for non-analog, true digital, cloud-based, multi-channel, auto-scaling support communication platforms. We expect Web Real-time Communications (WebRTC) to continue to make inroads here.
  1. Companies will realize the need to up their game in how they provide support in their mobile apps. Quality of service needs to become a priority. It’s a dated concept to present a default phone dialer that pushes the customer outside of your mobile app. Support solutions need to leverage available customer data to streamline information exchange and resolve disappointing experiences where customers feel their time and effort are wasted providing answers to a company that should already have access to their information.
  1. Context-aware solutions maximize what we know about a user. The recipe for achieving delightful end user support experiences is to minimize average support session durations and maximize agent effectiveness. In-depth awareness of end user context is becoming an increasingly important ingredient to leverage in support. We see this evolving relatively quickly into a standard end user expectation over the next few years.

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  1. Customer service will become progressively more user profile and data-driven. By drawing insights from basic profile metrics like lifetime customer value (LCV), evaluating core customer historical data, channel and more advanced preferences like voice and personality of the support entity, it’s possible to elevate support experiences, strengthen brand appreciation, increase LCV, and help drive positive organic social media reach and impact.
  1. Companies will continue to move to a single support center solution. Operating a contact center by combining multiple technologies, e.g., especially different communication channels and services will come with increasing opportunity costs. The longer a contact center relies on different core technology solutions, the greater the gap to competitors with modern single contact center platforms.
  1. Automation of processes will have more impact than AI. Artificial Intelligence (AI) and machine learning (ML) are somewhat overhyped for the contact center industry. For example, instead of trying to identify specific patterns in images or data, it will be more useful to increase the volume of satisfying self-service support sessions through intelligently applied automation to resolve common questions and provide guided user flows through defined business processes. By leveraging AI and ML to intelligently automate support processes, human intelligence can be focused primarily on those support scenarios that can’t be effectively automated, and call center operations will be further optimized.

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