Insights and Inspiration



Your Customer Conversations are Assets So You Need to Use Them

Mark Oppermann

In my last post, I spoke about how AI is modernising the credit and collections industry and how personalisation has been taken to another level. Today, I will look at data and managing the nuances of customer conversations and in particular conversational data.

Being able to understand the nature of the debt and the probability of being able to collect on it, is a key competency of most collections' organisations. The ability to work with data is key to these calculations, yet we often do not fully utilise the conversational information itself, and we do not use this conversational data to affect real-time outcomes. Being able to get access to all your conversational data, and how it is being acted upon, is an emerging concern for most financial-service companies.

Being able to get access to all your conversational data and then bringing those into reports, dashboards, and workflows is key to getting value from your conversational assets. And this concept was the driving force for us, as a business, in developing Propensity Studio.

AI that really works for credit and collections

Well not just for credit and collections, for any industry. Propensity Studio is designed to optimise customer engagement using AI and automation to better manage all customer conversations. By predicting business outcomes across all digital collection’s conversations, the conversations can now be better managed and guided through a range of best next steps dynamically selected in real-time as the conversations flows.

The business outcomes could be any outcome that is specific to how your business operates, such propensity-to-pay, or not to pay, or else propensity to be vulnerable. Engaging with customers and managing the nuances of each individual customer’s personal circumstances especially for digital

Imagine having the power to predict the financial and personal well-being of every customer at each stage of their conversation and design personalised journeys for each customer type, delivering the right message and level of agent resource at the right time. Well, this is possible, it is a reality.  

Using customer conversation data is the foundation for making all the good stuff work.  It serves to augment the speed at which conversations take place, how they are managed, the type of interaction that will take place between an agent and the customer. By turning conversational analysis into unique insights can only serve to improve conversation efficiency, conversation outcome, and of course conversation experience. Don't let one of your biggest assets go to waste.  


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