Smarter digital support for bill inquiries through AI chatbots and enhanced digital channels

We’ve all found ourselves trapped in IVR hell occasionally – when the options don’t correspond to our needs. More recently, many of us have gone through the frustration of trying different phrase combinations to get an answer out of a rules-based chatbot. But Generative AI is set to revolutionize these pain points to help deliver a far more sophisticated, personalized level of customer support along with faster resolution of inquiries and complaints.

The limited responses and rules-based approach of many chatbots often cause more frustration than assistance. This is all about to change as service providers begin to give smarter, AI-driven chatbots access to more data sets – enabling them to provide more personalized and wide-ranging support.

Data-driven, predictive chatbots deployed in self-service portals and apps will not only respond to customer needs but be able to anticipate customer them, personalize their responses, remember key dates (such as birthdays, contract renewal dates etc) and make smarter recommendations.

“Hey! What’s this charge on my bill?” 

This becomes an inquiry that’s easy to handle by smart chatbots without the need for any human intervention. The chatbot can interrogate billing data to find the anomalous charge. This charge might have been incurred for exceeding the included data allowance, for example. At the time, the telecoms operator might have flagged up the cost to the customer, but that was weeks ago and the customer has subsequently forgotten. Simply reminding them of what the charge was for and the circumstances around it might be enough to answer their question. 

“Would you like to avoid that charge in future?”

But what if the customer wants to avoid such charges in the future? Here a further interaction with the smart chatbot can be triggered either by the customer asking for more help, or the chatbot operating in a proactive or preventative mode. 

• In responsive mode – the customer might ask the chatbot an open-ended question in their app to avoid future overage charges. “Can I add more data to my package?” The chatbot immediately provides options to the customer, such as adding a data bolt-on, upgrading the package from next month, or adding alerts when data usage reaches certain levels. It can also look up the customer’s usage from previous bills and suggest how much data the customer is likely to need. Once the customer has chosen the best option(s) for them, AI will prompt the workflows to process the request.
• In proactive mode – the AI might ask whether the customer would like to take advantage of a new package that includes a bigger data allowance. In this case it would have assessed the likely amount of data the customer requires in order to suggest the best package or bolt-on. This results in new recurring revenue for the service provider, while avoiding the negative consequences of billshock.
• In preventative mode – the AI might incorporate a new set of rules – effectively learning from the interaction. When a customer is in danger of exceeding their data allowance, it might decide that they should automatically have the best options offered to them to prevent a large overage charge and the resulting fall out. When the bill is due, the AI might also remember to send a reminder of what choices were made to avoid the frustration of an unknown or forgotten charge. This can also be proactive: “Remember you subscribed to a new data bolt-on? This was added to your bill, but if you’d like to subscribe to this each month I can give you an additional 10% off the cost.” 

Incorporating generative AI, such as ChatGPT, means chatbots can understand a far wider range of customer queries and respond with even greater accuracy and personalization. These smarter bots can take the burden of service agents and provide support 24x7, 365 days a year across all channels of interaction.