I know this topic would look state to many who come to this post, especially those who have been already dealing with customer service for years and have put AI-based solutions in place. However, I can bet that even five years after its publication, this post will still be relevant, because even if organizations are fully aware of it and convinced of its value, operational deficiencies do not allow its proper implementation. That happens even in some of the most valued global companies.
Let me take a minute to emphasise the need to build trust, instantly, with a hassled customer - a point often given a priority lower than the technical aspects of grievance redressal (e.g. how big is is the knowledge-base of the chat-bot).
Customer support demands trust. Not only a bonding between the brand and its consumers, but trust of an intense level that the customer must quickly develop when he or she is in a critical mood. If the brand - represented by its physical office, website, app, phone or any other means of communication - instantly empathises with him/ her, is seen to be committed to remove the deficiency, and then acts professionally, the customer loses his/ her negativity and turns a loyal customer. On the other hand, if the brand cannot provide that trust, the customer becomes a purchaser of service who demands that the brand better listen to him/ her and redress their grievance. In today's world he/ she harms the brand not only by word-of-mouth criticism, but also gives vent to his ill-feelings on the social media. The loss is done, even if the brand later satisfies him/ her.
ChatGPT is commonly being used for these two tasks:
Using ChatGPT for quick and accurate responses to consumer questions
ChatGPT is a fantastic language model that can generate human-like responses, in fact better, due to quick access to a big database and no emotional baggage.
When organizations train the AI with their data and user cases, the responses can not only be precise but also human-like. The bot can always refer to a human if there is some gap in its understanding the queries or giving out answers/ solutions.
By leveraging ChatGPT especially for 'frequently asked questions', the customer support team can focus on more complex inquiries and provide personalized assistance.
Streamlining grievance redressal/ ticket resolution
AI is being used, though less frequently so far, also for resolution of grievances. Since grievances need to be handles with sensitivity, and might need technical skills on which training AI models is more difficult, companies are moving cautiously in this direction. However, seeing its potential (and also cost-cutting that it can lead to), it will also become commonplace.
Building of trust, which I discussed before, in ticket resolution is immensely important. When humans, supposedly trained in the task and with long experience, falter in this aspect, ChatGPT can become an asset or a disaster depending on a number of factors. I feel that the chances of loss of trust are higher, since the customer who approaches the customer support with a critical mindset is likely to get more upset that instead of a human who would empathise with his situation he has to deal with a machine.
Overall, I reckon that at the present state of AI tools, a proper mix of human and AI is the best approach. For FAQs, knowledge sharing, hand-holding, and such roles where the customer approaches with an open mind, ChatGPT can be used after proper training it on company-specific data. For handling grievances, it is better that a human takes over immediately after some preliminary data-gathering and queries.
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