Customer Support has a wild history rooted in the boom of innovation.
Customer service went from direct contact to a more distant relationship between the company and its customers, and this way of contact has lasted for a while.
With sporadic innovations in technology, the customer support services too have upgraded from 100% human involvement to semi-automated ones. Especially since the introduction of smartphones, because of 24/7 availability and fast reaction time, which follows the trends of customer behavior. Chatbots and AI powered omnichannel customer support systems are gaining ever increasing relevance. And it is not just certain features that makes this channel a customer and company favorite, but also the addition of pairing it with automated machine learning.
Applying artificial intelligence in a customer service channel allows support services to run smoothly. It does this by understanding the customer’s intent and registering their concern, and then giving back relevant information: whether it short text answers, trigger a background action like changing the subscription model or transferring the conversation to a Human Agent.
“At Simplify360, we believe the best customer experiences are created when Artificial Intelligence works with humans to solve customer problems” - Rohit Gupta, CEO, Simplify360.
Presently, there are a variety of emerging customer behavior trends emerging in the market. They include an increased demand for transparency, increased focus on customer satisfaction, a shift in omnipresent interactions, increased demand for anonymity, consumers looking for social experiences, increased focus on green products and lastly, more socially conscious shopping.
The Customer Support industry, to keep up with these emerging trends has formulated multiple counter technologies, to better serve the customers. Few of the latest successful such innovations are:
1) Customer Service Analytics: Customer service analytics can help companies uncover a diverse range of insights that can be used to improve operational and individual agent performance. Along with the help of Data Scientists, this approach can be used to maximize the precise understanding of customer's needs. Citibank is a great example using big data and customer analytics for customer retention and acquisition. One of the ways they do it is by processing and analyzing customer data combined with machine learning algorithms to pitch promotional spending
2) Chatbots: Chatbots rely heavily on artificial intelligence, particularly natural language understanding and machine learning. They are able to automate upto 60% of customer interactions, resulting in quicker and efficient resolutions For examples: Tata Play Whatsapp Bot, Swiggy, Spotify, etc.
3) Voice of the Customer (VoC) Solutions: Voice-of-the-customer solutions combine multiple, traditionally siloed technologies to capture, store, and analyze direct and indirect customer feedback. By integrating data from multiple VoC sources, companies can uncover subtler insights, drive accuracy, and ultimately instill more confidence in the actions taken at both the individual customer (such as an outbound call) and overarching strategic (such as a process change) levels. For example: Apple, Amazon, Microsoft, etc
4) Virtual Customer Assistants: Virtual customer assistants allow organizations to scale the number of engagements they can handle, especially in the contact center. A voice-enabled VCA in a kiosk or automated teller machine can remove the need for typed interventions and create more interesting interactions for nontraditional audiences. Examples: Ajilon, Belay, etc. These mentioned companies along with a list of other companies use virtual customer assistants as they are a cost and time efficient way to get tasks or projects done.
5) Customer Engagement Hubs (CEH): Customer engagement hubs are architectural frameworks that tie multiple systems together to engage customers optimally. They enable both proactive and reactive communication, as well as personalized, contextual customer engagement—using humans & artificial agents —across all interaction channels. They can also reach and connect all departments to enable synchronization of marketing, sales, and customer service processes All of this is done to personalize the customer experience while also making it more efficient. In a way, we’ve harkened back to the departmental store experience with shop help. The customer wants something that feels like they’re in-person and one-to-one, having a conversation with someone that’s a real expert in the information they’re seeking. They want someone that knows the products so well, they can anticipate an issue – they want someone that can be proactive instead of reactive. With all the scale and technology the world has offered up in the last hundred years, it really all comes down to the human touch.