Thursday, June 20, 2024

Chaser launches AI-powered recommended invoice chasing times to help SMEs reach customers when they’re most likely to pay

SMEs can now eliminate the guesswork when it comes to getting invoices paid on time. Using artificial intelligence, this new feature lets businesses reach their customers via email or text message precisely when they are most likely to make a payment.

Chaser, the global accounts receivables platform and credit control service provider, launched recommended chasing times. Recommended chasing times show in the Chaser software when businesses set up workflows and schedules to chase customer invoice payments via email and text messages. Recommended chasing times present users with the optimal time and day to chase customers, which is calculated and predicted using artificial intelligence (AI).

By leveraging AI and machine learning, Chaser analyzes a wealth of data, including customer payment patterns and historical behaviors, to generate tailored recommendations on the best times to chase customer payments. This strategic approach ensures that payment reminders are delivered when customers are most likely to engage with them, increasing the chances of prompt payment and reducing delays.

Key features of recommended chasing times: 

  • Payment reminder emails and SMS messages are sent at the best times and days to ensure they have the maximum chance of getting noticed.
  • Businesses can reach customers precisely when they are most likely to pay their invoice, based on their previous payment behavior.
  • Ongoing analysis of customer behavior means recommended chasing times are continually updated based on new data and insights.
  • If calculations predict that a business would see improved results by sending out multiple sets of payment reminders per week, the recommended chasing times feature will suggest multiple times and days to chase customers.

"Recommended chasing times empower businesses to reclaim valuable time spent on manual follow-ups and to optimize their collections efforts," said Sonia Dorais, CEO of Chaser. "By automating the timing of payment reminders, SMEs can effectively reach customers when they are most likely to make payment, reducing the number of follow-ups needed, and increasing the likelihood that payment will be received on time."

Key benefits of recommended chasing times:

  • Faster payments: Users can reach customers precisely when they're most likely to pay, reducing late payments and improving cash flow.
  • Eliminate guesswork: The AI-powered system considers various factors, including customer payment patterns and historical behaviors, providing users with customized recommendations on the optimal days and times to send payment reminders.
  • Continuous refinement: Chaser's system continuously adapts and learns from customer data, ensuring that the recommended chasing times stay accurate and effective as customer payment patterns evolve.

Find out more about recommended chasing times from Chaser.


[email protected]


Chaser helps businesses get paid sooner with its all-in-one accounts receivables automation platform, debt collections, and accounts receivables services. Users can credit check, monitor debtors, chase late invoices via SMS and email, collect payments, recover debt and reconcile accounts, all in the same platform. By sending automatic and deeply personalised payment reminders, the software and service provider effectively gets invoices paid on time without losing the human touch. To date, Chaser has helped users chase over USD 30 billion in overdue invoices. Chaser was named B2B Supplier of the Year at the CICM British Credit Awards (2022), won Best Use of Technology at the Credit Awards (2022), was Xero's 'App Partner of the Month' (August 2021), and the Accounting Excellence 'Cloud App of the Year' three years in a row (2017, 2018, and 2019).

Contact Information:
Amaya Woods
Senior Marketing Manager
[email protected]
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Original Source: Chaser launches AI-powered recommended invoice chasing times to help SMEs reach customers when they're most likely to pay
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