To ensure it built a solution that truly served a purpose and solved the needs of its customers, the financial services company leveraged its most valuable assets: its employees. As the closest touchpoint to customers, employees had a deep understanding of customers’ questions and needs. The firm used that knowledge to inform the chatbot.
Meeting the expectations of a new kind of customer
Insight helped the financial services organization launch a multichannel conversational agent, or chatbot, with rich capabilities for buying or selling stocks, locating nearby branches, getting quotes and more. Users can ask questions around financial topics, and the chatbot is able to provide educational resources in the forms of articles and short videos.
By providing seamless access to easily digestible information, the financial services organization has experienced a 72% increase in new accounts among millennials — and more savvy customer conversations.
“That’s the beauty of mobile applications and conversational agents: They digitally transform your customers’ experience,” says Matt Jackson, vice president and national general manager of Digital Innovation at Insight. “This real-time experience connects your audience with your organization in a more meaningful and personalized way.”
With the chatbot, customers gain the convenience of anytime, anywhere access and quick answers to questions. On average, it takes a human customer service representative 15 to 20 minutes to answer an inquiry. The chatbot can do it in seconds.
“Our investments in technology are paying off. Whether it’s something short-term or something bigger and all-encompassing, like competing on the client experience, everything we do ultimately ladders back up to that one thing: transformation,” says the financial firm’s chief executive officer.
Continuous improvements
The nature of AI means it’s always learning, so the financial services bot is continuously getting better at serving customer queries.
Every time the bot responds, “I’m sorry, I don’t know what you’re saying,” it gets logged in a database. Then, a human reviews the exchange and tells the bot what it should have said. The bot remembers that and variations of it so the next time somebody asks the same or a similar question, the bot provides a better answer.