A Collections Chatbot Demo: Negotiating & Automating Debt Collections
Collecting debts or late payments is never a great customer experience. It is also an unpleasant and costly task for businesses to reach out to customers who or late or delinquent on payments so that they can avoid accumulating bad debts. Although it may seem counter-intuitive, collections is an ideal process for using a chatbot solution.
This is an outbound customer service activity that can be executed by a Collections bot or digital assistant, powered by AI. The bot can automate payment reminders and send late-payment warnings day or night, reaching out to customers on their schedule as often as needed. The bot can also negotiate different payment terms with customers in an empathetic and fruitful manner. If they need to escalate a collections issue the bot can hand over to a human agent for further action. The key characteristics that make a collections bot so valuable are that it can:
- Hold human-like conversations with customers
- Negotiate payment terms
- Schedule payment dates
- Process payments on the fly
- Seamlessly escalate to a human agent
- Work with an existing collections process
- Integrate with virtually any backend or live chat system
This video offers a high-level introduction to how a collections bot can automate and add value. This is followed by a demo of a collections bot in action, depicting three different scenarios:
In scenario #1, the collections bot starts the conversation by asking for the customer’s phone number. This allows the bot to identify the customer and through an integration with the backend, the bot can see the amount that the customer owes and that they do not have a payment plan. In this case, the bot requests the full payment and when the customer accepts the offer, immediately connects to the company’s payment system of record. Here the customer is prompted to enter in their payment details, or if preferred use Pay Pal or another form of payment. The bot sends a confirmation once the payment is processed.
In demo scenario #2, although it starts similarly with customer account validation, you’ll see the bot first empathizes with the customer who then rejects the request to pay the full amount due. At that point, the bot negotiates with the customer to collect an upfront payment of $20 and set up a future date confirmation for when the company can auto process the remaining balance due. Here you see the option to present a calendar with date selection, one of the many visual, interactive elements that can be added to enhance customer experience.
In scenario #3, where the customer has a large balance due, the bot expands its negotiation options after the customer refuses the bot’s first offer to pay a certain amount. Rules dictate that the bot can ask the customer how much they are willing to pay today, and if they offer an amount below the threshold required, the bot will then present a menu of varying options that may work better for the customer. If the customer does not feel comfortable with the options presented they can opt to speak to an agent. The bot then initiates a live chat session, opens a ticket in the customer’s ticketing system, and passes along the context of the conversation to the agent for resolution. We always suggest that our customers offer an option to escalate to an agent if the bot and customer are not able to come to an agreement. And lastly, we show an example of an interactive widget that can be easily added to the bot in an effort to collect a rating of the customer’s experience.