My talk at the AI Summit, Singapore.
In 2017, I spoke at the AI Summit, Singapore. My talk was focused on the impact that artificial intelligence (AI) and natural language processing (NLP) technology can have, specifically in the customer experience vertical. And, yes, that is me up ob the stage.
But, before I get into it, it’s important to ask “Why is good customer service critical to any business?”. The answer — because it’s typically any customer’s first touch-point with a brand. So, it had better be good!
As we move away from screens, towards chat and voice-based interfaces, a major shift is taking place in the technology that’s enabling customer experience. Given that customers are more likely to use your product through voice-enabled interfaces like Google Voice and Amazon Alexa, or even mixed reality environments, there is a deep layer of complexity to delivering great customer experience. That’s all the more so when this experience has to be provided at all times during a user’s product journey.
It is no longer possible to bank on existing methods of providing help and support, where content is on webpages and searchable through simple indexing. If your product user is in an audio-only or experiential environment, then the experience on a webpage-based system can end up being sub-par, and can result in high product drop off.
Conversational UI for a restaurant POS.
Let’s dig a little deeper:
Let’s begin by understanding what exactly customer service is. Let’s not look at it from the point-of-view of a business or a customer, but as an onlooker:
Great customer service should translate to love and loyalty — between customers and businesses. But how often does that happen? Almost never. So, for now, it’s a pretty utopian vision.
When customers call customer service, their experience is most likely to be fragmented and frustrating when they are transferred from one department to another or just made to wait for ages until someone who can actually help comes along. We’ve all been there and we’ve all hated it, haven’t we?
Let’s look at the current problem scenarios mapped to their gaps —
Customers post their queries across channels: Information is fragmented and scattered, so businesses are unable to understand who their customers really are.
Peak time is ‘always on’ when it comes to customer service: Customer service reps are bound to make errors while trying to get the entire picture.
The 4 big messaging platforms together have over 3 billion monthly active users: Consumers are already gaining exposure to chatbots on smartphones and other devices
Inability to solve issues can quickly lead to a bad reputation(since the human tendency is to criticize rather than appreciate): This results in loss of customers to competition.
Comparing the perception of good vs bad customer service
But how will these issues get solved?
For customers — when they have to visit just one point for prompt response on any query or issue.
For customer service reps — when they can cut down the noise and focus on the right things.
This is where AI, powered with content and conversations, comes in to bridge the gap:
As an AI application, an NLP-based chat or voice bot can:
Understand customer correspondence
Extract key and relevant info
Share it with the right people
Record the data and answers to enquiries on its own after learning from conversations
Wherever the bot gets stuck, a human should intervene. This lets the bot:
Hand over requests to the customer service rep and learn from the way its human counterpart handles it.
Free up the rep to build customer relationships and convert more brand advocates.
You can go through my presentation in detail here.