When you are cancelling an appointment to meet a friend for a drink do you phone them, or do you message them? My bet is that you message them. They message you back, you apologise and then you go back and forth, and eventually agree on a new time and place. In companies, we do this all the time, except we use an application to help us agree the time and place. Google Calendar can help find a time that is available between two people, and Calendar.ly is a popular application in this space.
Some of the first tasks we are handing over to intelligent assistants, or chatbots, are simple actions such as booking a time, agreeing a call back time, or giving us a suitable quick reply “Great, see you then” in our Gmail. You are probably using these functionalities every day and not really thinking that much about the fact that they are artificial intelligence driven. But a key point is that we didn’t call our friend, did we? No. We messaged them.
Now looking at the whole area of credit and collections, when dealing with personally embarrassing or frustrating situations the ability to interact via messaging with some automation that incorporates self-service deescalates the situation. A gentle reminder is sometimes all that is required in early collections and with a simple SMS debt collection automated chatbot, (or any messaging channel). For later stage debt, two-way blended SMS messaging conversations with an agent and a chatbot has proven to be incredibly powerful. Simple two-way automated SMS conversations can be made to feel very natural and have replaced the traditional outbound blasts asking customers to 'Call' or 'PAY'.
The conversations are mostly programmatic and structured with responses to payment issues being similar across industries. Payments and collections have their own nuances in terms of the technologies and software’s that they need to integrate with, but the conversational design challenges one industry faces are very like those in other industries. In short, there are economies of scale.
Normally when we get an email reminder, we either ignore it or we go to a website. We then check our balance, go to the payment history, and admit to ourselves that we do indeed owe it. A quick web chat right ‘there and then’ might be enough for us to clarify the minimum payment requirement would be that would not harm our credit score, and maybe we make the payment. If we could pay that agreed amount right there in the message with a single click, then all the better. Other times we have to walk away and think about which bill we should pay first. If we’re behind on one bill, chances we are behind on others too. We also now have multiple other conversations to manage. Which ones did I call? What did I promise each one? What did I say last?
This is where persistence in messaging is like an instant memory. We only have to scroll back on our messaging history to see what was said, to remember what was agreed, and by when. We might even have the agents name in the messenger. Driving these emails, chats, messenger and even voice interactions, are chatbots. Today these are likely to be different systems and you are probably having to do a lot of data-joining in the background to get the kind of business intelligence you need for a scale operation. That’s where Conversational Middleware and Conversational payments helps you prepare for scale.
Automate conversations where you can and augment the agents where possible. Chatbots are a great way to do this. Just like Google Quick Reply or Booking a meeting time on Google Calendar. It’s easier than you think. Why not message us to find out more?