We discuss metrics for different business models, the challenges merchants face in tracking and interpreting payment data, and the opportunities for leveraging AI in payments.
Anta provides actionable insights on optimizing authorization rates, reducing costs, and minimizing involuntary churn. He also explores the future of payment technologies and the importance of viewing payments as a revenue driver rather than just a cost center.
Interview callouts
Understanding Payment Metrics
Anta highlights the complexity involved in tracking payments metrics – it's not just about a couple of numbers, but a comprehensive view that varies based on industry type, transaction volume, and geographical presence.
Key metrics include authorization rates, decline reasons, and cost of accepting payments. Particularly for e-commerce businesses, customer drop-offs and decline codes are critical metrics, while subscription companies focus on churn rates and retry strategies.
Challenges in Payment Tracking
One significant challenge mentioned is the lack of standardization in payment reporting across different service providers. This inconsistency requires merchants to build substantial internal data and developer teams to clean, standardize, and derive actionable insights from the data.
Anta emphasizes the necessity for merchants to take proactive measures, exploring options with current payment service providers to leverage all available information and improve payment performance.
Optimizing Through Payment Experiments
A/B testing in payments is a common recommendation, albeit a challenging one due to the operational and integration requirements involved. However, by identifying areas of underperformance with current providers, merchants can strategically choose new providers or improve existing processes.
Successful experiments have led to improvements in retry strategies, fraud reduction, and cost optimization by addressing decline reasons with more targeted responses.
The Promise of Gen AI and Future Innovations
The advent of Gen AI presents exciting opportunities for payments analysis, although Anta suggests that the industry is about 70-80% there. Prediction and solution models for fine-tuning payment strategies are still evolving. However, ongoing advancements in AI are expected to facilitate more proactive and precise interventions, significantly enhancing payment reliability and efficiency.
The Role of Merchant Mentality and Regulation
A key insight is the mindset shift required for merchants to view payments as a revenue driver rather than just a cost center. This perspective opens up opportunities to optimize transactions, improve metrics, and ultimately increase revenue. Furthermore, regulation and global expansion bring additional layers of complexity and opportunity, requiring merchants to stay informed and compliant while capitalizing on emerging payment strategies.
Final Thoughts
Anta concludes by encouraging merchants to engage with their payment data actively – extracting value from existing integrations and enhancing them where necessary—to improve performance and profitability. As the payments landscape continues to evolve with technology and regulation, staying informed and adaptable remains crucial.
For a deeper dive into these insights, the full conversation with Anta, full of practical examples and advice, is accessible through his LinkedIn or via direct contact.
Interview Timestamps
00:00 Introduction to Payment Success Rates
00:20 Actionable Insights from Payment Data
00:52 Guest Introduction: CEO of InEye
01:56 Key Payment Metrics for Merchants
04:32 Metrics for Different Business Models
08:55 Challenges in Payment Performance Tracking
11:20 The Role of Data in Payment Optimization
18:32 A/B Testing and Orchestration in Payments
25:15 Future of Payments: AI and Account-to-Account
33:19 Common Advice for Merchants
37:31 Conclusion and Contact Information
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