I recently spoke at the AI Summit, Singapore, at their Start-up Showcase. The talk was focused on the impact that artificial intelligence (AI) and natural language processing (NLP) technology can have, specifically in the customer experience vertical.
But, before I get into it, it’s important to ask “Why is good customer service critical to any business?” Because it’s typically any customer’s first touch-point with a brand. So, it better be good!
As we move away from screens, to chat and voice-based interfaces, a high shift is happening 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 more so when this experience has to be provided at all times during a user’s product journey.
It’s 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.
Let’s dig a little deeper into what I just mentioned above:
We start by understanding, what exactly is customer service? 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 the customers and the businesses. But how often does that happen? Almost never. So, for now, it’s a pretty utopic vision.
When customers call customer service folks, their experience is most likely to be fragmented and frustrating when they are transferred from one department to another or is just made to wait for a long time till someone who can actually help comes along. We’ve all been there and we’ve all hated it, haven’t we?
On the customer’s side, the experience with customer service is most likely to be fragmented and frustrating when they are transferred from one department to another or is just made to wait for a long time till 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 & 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 bad reputation(since human tendency is to criticize than appreciate): Resulting in loss of customers to competition
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 the 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 & 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 below:
AI Summit Singapore Presentation