The power of advanced analytics in optimizing payment performance

Several years ago, I was tasked with managing payment operations for a global platform selling fast-moving consumer goods. Every day, we handled hundreds of thousands in transactions. While we diligently tracked our conversion rates, our perspective on the broader payment performance was incomplete. We simply lacked the sophisticated tools needed for a comprehensive in-depth analysis.

This changed dramatically as I started learning about payment analytics. Our approach shifted from basic number crunching to uncovering patterns, anomalies, and assessing every facet of our payment process. Metrics such as payment failures, fraud decline rates, recovery rates, refunded payments across every country, business vertical, and sales channel, became our tools for success, helping us to focus on tailoring the right initiatives and ultimately leading to a 20% boost in our checkout conversion rate.

Navigating this complex ecosystem of payment data was enlightening. It made me truly appreciate the intricacies involved in successfully completing an online payment. From data encryption to bank authorization, these mechanisms, largely invisible to the customer, are a testament to the marvel of modern e-commerce. For us merchants, understanding these operations is not just illuminating, it's essential for improving profitability — and this is precisely where payment analytics becomes the key.

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Understanding payment analytics

So, what is payment analytics? Simply put, it's the practice of sifting through and examining the data from payment transactions. However, payment analytics goes beyond merely identifying and rectifying issues. It provides a detailed look into every step of the payment journey, unveiling not only weak spots that require resolution but also opportunities for savings and profit growth. 

Take an example of a business noticing a high rate of payment failures due to a specific payment method. By addressing this issue, they can potentially increase their sales, positively affecting their bottom line. Similarly, identifying a pattern in peak transaction times can help businesses optimize their operations and marketing efforts for those periods, driving higher engagement and conversions. The impact of these decisions coming together, both large and small, based on payment analytics, can have a substantial ripple effect on the company's profitability.

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What metrics can you track with payment analytics?

Within the scope of payment analytics, we rely on several key metrics that serve as indispensable guides. These metrics offer unique perspectives, enhancing our understanding of the payment process. It's important to note that these metrics do not exist in isolation; they're interconnected, with changes in one metric often influencing others. In essence, they collectively create a comprehensive overview of payment operations. The following are some of these critical metrics:

1. Payment authorization rate: This metric reflects the percentage of transactions that are successfully authorized. Rather than being a standalone statistic, it is a real-time tracking tool to ensure successful order completion. For a more comprehensive insight, merchants should monitor the authorization rate at both the transaction attempt level and the order level, revealing the correlation between payment attempts and orders. Analyzing the authorization rate through various dimensions provides a detailed perspective, which can help identify specific areas that need improvement.
2. Payment failures: Payment failures serve as indicators of the overall user experience. This metric shows the percentage of attempted transactions that fail for various reasons, like insufficient funds, expired cards, or technical issues. In this context, taking immediate and appropriate action is crucial. If a card lacks sufficient balance, the customer should be informed via an accurate error message, suggesting using another card. If a transaction is declined due to a 3DS requirement, it's worth enforcing all payments from the specific BIN to go through 3DS from the start. If the acquirer declined transactions by returning a "not allowed payment" message, merchants should seek further clarification. Solving unnecessary payment failures can thus help improve the payment authorization rate and overall customer payment experience.
3. Fraud decline rates: this metric helps businesses monitor and manage potentially fraudulent transactions. A high fraud decline rate might suggest the need for enhanced risk management strategies and preventive measures. Alongside this, merchants need to track false positives — legitimate transactions incorrectly declined due to suspected fraud. Defining what counts as a false positive for their business and closely monitoring this metric helps prevent revenue loss from valid transactions that are wrongly declined.
4. Refunded payments: These numbers give businesses insight into the number of payments refunded to customers. A high refund rate might indicate issues with a product or service quality. By identifying the reasons behind the refunds, businesses can take corrective measures to improve their product or service offerings, which in turn can boost customer satisfaction and retention. High refund rates might sometimes also include fraudulent behavior due to internal and external factors. 
5. 3DS share: This metric indicates the proportion of transactions using 3D Secure, an additional security layer for online credit and debit card transactions. If a large number of non-3DS transactions are noticed, businesses might consider promoting the use of 3D Secure among their customers to reduce fraud risk. However, it's crucial to also track the dropped rate due to 3DS flow. Balancing fraud risk and authorization rate is a delicate act, and these metrics provide key insights for optimizations.
6. Recovery rates: This shows the percentage of transactions that are successfully completed after initially failing. By analyzing the common reasons for initial failure and successful recovery methods, businesses can refine their payment systems to improve the overall payment success rate.
7. Chargeback rates: This key metric reflects the percentage of transactions that result in a chargeback, which occurs when a customer disputes a transaction, and the bank forces a refund. A high chargeback rate may suggest issues with product quality, customer service, or often fraudulent activity. This metric can be analyzed in conjunction with a payment method, issuer, and PSP to detect any correlations. For instance, if chargebacks are more frequent with a specific payment method, it may indicate that customers using this method are more likely to dispute transactions, which could necessitate further investigations or specific risk management strategies.

Each of the metrics can be analyzed further based on various dimensions, such as issuer, payment method, and payment service provider (PSP). This provides a more comprehensive view of the payment performance, unveiling intricate patterns and trends. It's possible that a specific PSP may result in higher transaction success, or a certain issuer could be linked to increased fraud decline rates. 

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Payrails approach to tailored payment metric analysis

We have crafted a straightforward, three-tiered approach — data integration, data harmonization, and data visualization. We know working with payment analytics is extremely challenging due to many different formats, structures and data transmission methods of different 3rd parties involved in the payment flow. Our method guarantees thorough data processing, a clear data comprehension, to ultimately empower our merchants to focus on using the data for making informed decisions and moving their business forward.

Here is how each pillar is adding value:

1. Data integration: Online transactions typically involve the use of numerous PSPs, each with its unique set of transaction data. Payrails simplifies this complexity by aggregating data from various sources such as Adyen, Stripe, and many others. This integration forms the foundation for all subsequent analyses.
2. Data unification: Managing multiple PSPs inevitably leads to diverse and sometimes conflicting data sets. The key is transforming and integrating these sets, resulting in a unified and coherent overview of all payment data. Once harmonized, this data paints a clearer picture, highlighting the strengths and areas requiring further attention.
3. Visualization: Payment data is visualized in an accessible manner, presenting metrics in clear, user-friendly formats. With the aid of dashboards, graphs, and charts, trends in payment performance become more evident. This approach not only highlights overarching patterns but also allows for a deeper exploration into the essential factors behind these trends.

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If you're looking to leverage a data-driven approach to maximize your revenue, drop us a message. Let’s explore how a comprehensive understanding of payment data with Payrails can unlock new opportunities for your business.