By Tracy Oppenheimer/Helpshift
Fintechs, by nature, have a more comprehensive understanding of today’s consumers than brands spanning other industries, as they exist largely to create better relationships between banks and their customers — thus catering to customer values such as convenience and efficiency.
Incorporating these values into the user journey matters at every touchpoint, with customer support being no exception. Customer support can be a true differentiator, especially for fintechs that view support as a channel that promotes an ongoing conversation as opposed to one-off interactions.
Utilizing “conversational customer service” lends itself to those better customer relationships that fintechs strive for by thoughtfully leveraging innovative tech to power highly personalized conversations at scale. Here are three best practices for fintechs looking to augment their support operations to achieve a fully conversational experience.
- Support Mobile Users with Mobile-First Communication: Messaging
Fintechs know that their customer base largely lives on mobile phones. They understand the benefits of a native mobile experience and often have mobile apps to support this. Customer service should therefore be native mobile as well (not just mobile responsive).
That means having a mobile-first communication channel, like messaging, and in-app self-service. In-channel messaging, similar to an iMessage or Whatsapp interface, is the preferred channel for personal conversations — so why not use this for conversing with customers?
It’s important to note that this is different from a web-based live chat that would take users out of the app and require them to wait around for a customer service agent to respond. Messaging isasynchronous
, meaning customers can send a message and continue on with their day, and receive a notification when there is a response waiting for them.- Use AI and Chatbots to Improve UX, not Just to Reduce Costs
These tech tools need to be used, first and foremost, with the user experience in mind. Forcing users to navigate clunky IVR-esque menus or to interact with AI-powered chatbots that have less-than-optimal levels of accuracy only increases frustration and is bad for business.
Appropriate applications of these technologies includes collecting user information and leading customers down specific workflows through decision tree-based chatbots, reserving chatbots infused with natural language processing (NLP) for suggesting knowledge articles and improving self-service (as opposed to using them to converse with the customer directly). NLP can also be used to categorize issues and route them to the agent best equipped to handle them.
Those three AI and bot applications allow customers to receive the quickest response and get their issues resolved as efficiently as possible — vastly improving UX in the process.
- Prioritize Phone Communication as an Outbound Escalation Channel
Certain issues and customers demand a more urgent channel of communication. By using asynchronous messaging as a primary channel, there will not be a live queue of customers waiting on hold in a browser to speak with an agent. This gives support teams bandwidth to take a more strategic approach to issue prioritization.
For high-priority issues that need to be escalated, agents can be directed to these messages first and call the user when it’s necessary to have a verbal conversation. These channels of asynchronous messaging and outbound calling can work in harmony so that agents can focus on high-touch issues and customers don’t have to listen to any “hold music.”