Conversational AI For Customer Engagement

The Case:

Customer Engagement is the emotional connection between a customer and a brand. Highly engaged customers buy more, promote more, and demonstrate more loyalty. This makes customer engagement a crucial part of every company’s marketing strategy.

The Challenge:

As important as customer engagement is it’s very difficult to keep up with every customer and to constantly follow up with them. For a company with a few hundred loyal customers this can be managed by hiring more staff to handle all of the customer requests. However for companies that get thousands of customer inquiries per day this approach is not scalable.

Some companies use automated solutions which reply by returning a series of predefined responses. The problem with these solutions is that they look and feel very robotic and often times don’t take into account what the client has actually said.

This can turn off clients who are used to having a conversation with human operators not machines.

The Solution:

To solve this problem we used advanced NLP and NLU algorithms to build a conversational AI that tries to make sense of what the user is saying.

Our algorithm can detect sentiment, qualify prospects, verify information such as emails, phone numbers and addresses all while sounding natural taking into account what the client has said.

The system maintains context over several exchanges and can adapt to changes in the client’s responses. This makes the system more flexible and makes the conversation sound more natural.