E-commerce giants such as Amazon and Shopify use data to create highly personalized customer experiences. Yet, bill payment remains largely untouched by this transformation, leading to friction, higher costs, and customer frustration. Despite the wealth of payments data available, many organizations fail to leverage it to enhance customer interactions and reduce costs.

This gap presents a major opportunity: by applying data-driven insights, businesses can not only improve the payment experience but also drive efficiency, reduce costs, and boost customer satisfaction.

In a recent PaymentsJournal podcast, PayNearMe’s John Minor, Head of Product and Gustavo Jordao, Product Manager, joined Don Apgar, Director of Merchant Payments at Javelin Strategy & Research, to discuss how payments data can help organizations deliver better payment experiences.

Payments data provides organizations with deeper insights into consumer behavior, extending beyond transaction details. It captures factors such as time of day, device used, and payment method, offering an in-depth understanding of consumer interactions.     

These data points can be synthesized to create a comprehensive view of the customer’s mindset and context during payment, enabling billers to turn transactions into personalized interactions that improve the overall customer experience. 

Beyond improving customer experiences, payments data plays a key role in operational efficiency, helping businesses reduce operational costs. Businesses that embrace automation and data-driven decision-making can streamline processes and lower their total cost of acceptance.

“One of our clients in the lending space was able to save $44,000 a month just by leveraging automation,” added Jordao. “By triggering specific rules based on transaction data, they streamlined payments and significantly cut costs.”

Any discussion of data inevitably leads to artificial intelligence (AI). However, success with AI or machine learning depends on clean, structured data.     

“There’s so much buzz about AI, but we put in our 2025 forecast that it’s going to be the second adopters of AI that will really reap the benefits, as opposed to the first movers and early adopters,” Apgar said. “So many companies are rushing to find so many applications for AI that I think it’s too easy to stub your toe, especially in a customer-facing or risk-facing application.”

AI depends on high-quality data. Poor data can lead to unreliable insights. To ensure accuracy, organizations must prioritize data cleanliness, implement strong monitoring systems, and maintain transparency in AI decision-making.

“It’s about understanding the interactions and making sure you’re instrumenting the transactions you rely on to create good datasets,” Jordao said. “That’s one of the key things about AI—making sure that you have a way to trace and audit how it’s being used, because it’s a very complex tool. You should be able to control its application and drive it toward      performance and a better experience for consumers.”

Fraud detection is an area where AI excels, analyzing vast amounts of data to identify anomalies and automate responses—a costly and time-consuming task. Fraudsters are becoming more sophisticated, making it more difficult to flag fraudulent transactions based on isolated data points. 

“Risk is a highly complex interaction—there’s no single red flag for fraud. That’s where machine learning takes the spotlight as a tool to be used,” said Jordao. “One of our gaming clients reduced fraud by 60% just by leveraging AI to analyze transactions in real-time—something that would be impossible to do manually.”

ML models excel at recognizing patterns and triggering automated actions. Unfortunately, few organizations have fully leveraged the power of AI and machine learning to enhance the bill pay experience.

“As it relates to bill payment, generative AI could be used to replace or automate several aspects,” Minor said. “Automated bots could handle outbound and inbound calling, messaging, and communication using generative natural language processing. That could help lower the costs required to collect the payment.”

E-commerce has set the standard for data-driven personalization and the bill pay industry must follow-suit. “In e-commerce, data is being used to personalize what you see, how you can pay, and what items belong together, which varies by consumer,” Minor said.

“Those insights are gained by leveraging clean data like past purchases, browser history, and location. Bill pay is no different. Consumers need access to different content and options beyond just completed transactions. They want to complete what they’re there to do at a given point in time.”

For example, a customer logging into their bill pay account may not intend to make a payment immediately. If their bill isn’t due yet, they may be looking for information such as their payoff date or account details. A personalized experience can anticipate this and present relevant options.

Additionally, payment experiences should adapt based on the access point. If a customer pays through a mobile device, the system could suggest payment methods optimized for mobile transactions.

Despite these possibilities, many organizations have not prioritized personalization in bill pay.

“What you see sometimes in bill pay is that organizations haven’t given the process the same amount of focus as they have on the product they’re selling to the consumer,” Minor said. “Unfortunately, they are often using fragmented platforms that aren’t able to ensure the consumer is able to complete the thing that they’re there to do at a given period of time.”

Data offers significant advantages; it is not just an asset—it’s the foundation of growth and innovation. However, the true power lies in how organizations interpret and apply their data. 

Leveraging data gives businesses the ability to better understand customer behaviors, preferences, pain points, and purchase drivers. To maximize value, businesses should seek partners who provide actionable insights that drive measurable results. Clean, structured data not only improves efficiency, but also serves as a springboard for delivering exceptional payment experiences.   

“We’ve heard a lot in the news about payments orchestration,” Apgar said. “That’s been the buzzword in the payments business for the last couple of years. That is also data-driven, but I think the way that we’re talking about using data in this context takes the payment experience to the next level of payment orchestration, not only from the data that is being captured, but the way it’s being applied.”

As AI continues to shape the future of payments, organizations must carefully evaluate potential partners, ensuring AI is used responsibly and critical data remains protected. “With great data comes great responsibility,” Minor said.

The future of payments isn’t just about adding new technology—it’s about creating an experience that is seamless, secure and deeply personalized. True, sustainable innovation requires more than just ‘bolting on’ the latest shiny object; it demands a strategic approach that drives real value.

“Data is behind everything we do. If you’re not thinking about data, you’re already behind. Our job is to democratize it, make it actionable, and help our clients lower their total cost of acceptance,” said Minor.