Whether a merchant decides to establish a brand-new e-commerce operation or seeks to improve the performance of an ongoing operation, it is crucial to monitor aspects of payment performance. Data-driven decision-making helps manage and leverage the digital insights needed to make more informed decisions. Payment metrics and key performance indicators (KPIs) may be tracked manually within Excel or, even better, via a business intelligence (BI) dashboard. BI dashboards use tools like Tableau, Microsoft Power BI, QlikView, and more to analyze data through info management and data visualization.
To create a useful monitoring routine, you’ll want to decide which KPIs should be measured to properly reflect the efficacy of your business. When talking about payments performance, the following metrics are found useful by many merchants:
Conversion Funnels and Drop Off Rates
Approval and Decline Data
Chargebacks, Refunds, and Fraud Data
Let’s dive a little deeper into what exactly merchants should be looking at when measuring the success of a business. We’ll look at three specific areas: conversion funnels, processing metrics, fraud risk, and post-processing handling metrics. In addition, we’ll explore some sub-categories of those in order to provide a full overview of what payments processing truly entails.
First up, let’s explore a common visual guide that helps businesses monitor customer interactions: the conversion funnel.
1. Conversion Funnel and Drop Off Rates
A Conversion funnel (frequently known as a sales funnel) tracks the journey of a user and helps businesses to visualize the flow of customer interaction. It begins with the acquisition source, through the site pages and product interactions to ultimately reach the payment page. The conversion funnel flow helps visually confirm certain metrics such as:
· How many users reach the payment stage
· How much time it takes them to complete the purchase
· How much time they are spending in cart before payment
· How many of them initiate the payment process by pressing the ‘BUY’ button
Note that when using a hosted payment page, you may not be able to apply your own tracking tools since the page is handled by your payment processor. If so, you should discuss this with your processor as they may have built-in tracking and should be able to share this information with you. The tracking of user behavior on the payment page is useful to see which element on the page may confuse or pose challenges to the user, thus slowing down the payment process.
On the payment page it’s smart to monitor the following:
● Various payment methods chosen by a user
● When or if a user switches between payment methods
● Specific fields within the payment page
● Redirect payment methods or 3D Secure flow
● Analyze traffic by device, operating system, and browser
● How many attempts a user makes to deposit
Diving deeper, ask yourself the following: do many users pause on things like the CVV field or the Wallet ID field? If so, an informative icon might be needed to refresh their memory. Perhaps users consistently start a flow but how many actually complete it? If this is the case, run a life test to see if the redirect works properly. When it comes to users making deposits, you can create alerts for users that get “stuck” on a payment page attempting to deposit repeatedly. This could be a good indication that there is a technical issue on the merchant side. Alternatively, it could be a possible fraud alert. Either way, tracking the number of attempts made by a user will help rectify the issue.
You can use the above information for further improvements in processes. Tracking data points like these will make it significantly easier to find any bugs that need fixing.
Response Time and Uptime
Additional metrics worth monitoring include the response time of the website, specifically the payment page, as well as the uptime of the processor.
Monitoring these will help identify any issues related to payments processing that might prevent users from paying. With such information, you´ll be able to decide how to handle payments processing issues. For example, you could close one of the processors and route deposits to a different processor in the interim while you find a fix for your primary processor.
2. Processing Metrics
Once a user has pressed the ‘BUY’ button, the payment process begins. You can track the following KPIs for a good picture of payment processing metrics: approval ratio and decline codes.
Approval (Authorization) Ratio refers to the number of successful payments out of total attempts made. This metric impacts revenue directly and is crucial to online businesses. The ratio can be measured in the following ways:
● Transaction level
● User level
Transaction level refers to the total successful transactions in relation to the total attempts made. User levels refers to the total successful transactions per total attempts made by a particular user in a session.
For example, in the table above we can see that the overall approval ratio sits at 54%. This number is relatively low. However, when looking at the customer level of 83%, this number sits more within the normal range. By looking at these percentages, we should ask ourselves: why do our customers have to retry several times before they succeed? Is there anything we can do to improve this situation and bump those percentages up? A variety of reasons exist as to why a payment processor might decline a transaction. Some of which include expired cards, mismatched IP and billing addresses, invalid cards, and more.
To better understand the problem users might be facing, we will investigate the web analytics metrics (see above) to track any issues on the payment page that might be causing problematic input prior to the deposit.
Another way to understand the issues at hand is to check error code or decline code metrics.
Decline Code Metrics are used to track error codes statistics by showing the split of unsuccessful transactions by error group. If you see any changes in your regular consistency, you’ll need to contact your payment provider for further investigation.
Note that each processing bank will likely use different decline messages and error codes. Some processors will create error groups for you, others will simply pass on the message received from the issuer.
To that end, it is highly recommended to analyze the decline code and map out the declines into the following error groups:
Card Details Incorrect
If you see this error a lot, check if in field validation works properly on the payment page.
If this error occurs for cards on file, or for subscription payment, it is most likely that the cards are expired. You may talk to your service provider to discuss possible handling procedures.
This is usually one of the most common errors. If you see this error occur in some markets more than in others it may indicate that there are some limitations on cards.
Talk to your service provider and review your pricing for this market.
Another common error. You may retry again if you have a card on file. Best to try in 12-24 hours.
Note that the generic error “do not honor” often serves banks when they are unable/unwilling to give more detail on the decline reason. So, in fact, it is a compilation of any number of actual declines.
If you encounter this error more than no funds talk to your service provider to complete an in-depth analysis.
Should not happen. If this error occurs let your tech team know immediately.
Most common reason for this error: something changed in the API structure.
The share of this error group should be very low. If you have many cases of this error, you may be under a fraudster attack. Talk to your service provider.
Errors related to customers that failed to complete SCA authentication. Note that the failure may take place during different stages of the process.
3. Fraud Risk & Post-Processing Handling Metrics
Every merchant is required to track metrics related to regulated compliance programs. It is also advisable to track metrics that are not always required by the compliance programs. Tracking these metrics will help you better predict potential risk factors.
The following is a list of risk dashboards and related information you can refer to. These are all items that will provide clarity on progress, as well as support for informed decision-making.
● Data from fraud tools
○ Overall Risk Declines with drill down by flags were triggered
○ False positives- how many cases flagged were whitelisted after manual review
○ False Negatives - Fraud tools detection and manual review Vs confirmed fraud chargebacks and fraud files
● Chargeback History
Monitor chargebacks count and rate (%) as per card scheme thresholds
● Fraud to Sale History
Monitor fraud file amount and rate (%) as per card scheme thresholds
● Retrieval Request and/ or Chargeback Alerts Handling
Tracking alert handling status such as, new, refunded, and turned to chargeback will help you get the most benefits form these pre-chargeback alerts.
● Chargeback, dispute, or recall handling funnel
Terminology will depend on the payment method, but essentially it is a user initiated reversal of sale. Each payment method has its own time frames and rules for disputes. It is helpful to measure the presentment stats in order to understand why disputes arise and whether there are actions that can be done on the merchant's side to prevent those. Additionally, looking at the results (reversals) of the presentment it will be easier to identify where our effort is the most valuable.
For example a funnel may look like that handling funnel (new>disputed (yes/no, why not)>reversed (won chargebacks> >arbitration)
● Chargeback after Refund ratio
How many refunded transactions were also received as a chargeback? This may indicate one of two things. Either it takes you too long to refund clients, or that in certain markets, refunds are less effective because banks don’t always confirm whether a refund was provided.
● Chargeback age
The time difference between the transaction and the chargeback. If the difference is small, it indicates that users are filing chargebacks quickly. This may further indicate fraud issues or a particular major flow in the product or service.
● Refund Reason
Define refund reasons relevant for your operation, for example: fraud prevention, client request, technical issue.
It is advisable to measure refund handling time frames, if t takes too long to issue refunds, they might me less effective as a chargeback prevention tool.
4. Processing Cost Metrics
Each of the following processing cost metrics help evaluate performance for future optimization:
● Processing cost per payment method
● Cost of refunds
● Cost of chargebacks and chargeback handling
This may help define when it is worth representing the chargebacks and vice-versa
● Processing cost per user including all user attempts
A benchmark is a point of reference from which measurements can be made with aggregated data. It measures data points and allows you to compare specific results against competitors or peers. To normalize the benchmark, ask for data based on your Merchant Category Code (MCC) or vertical. The MCC is a four-digit number used by credit card companies to classify a business by the types of goods or services it provides.
In order to track anomalies, you need to know what your typical statistics are. This can be tricky if you are establishing a new operation or adding a new product. This issue may be resolved by contacting your payment provider and asking for some benchmark data.
When you know what a standard performance looks like within your vertical, you will be able to build a dashboard that shows your performance against merchants similar to you. It is advisable to request benchmark data every three to six months. This allows you to properly track changes within the industry.
Analysis of Information
Aggregating data and improving upon it is crucial in gaining consumer trust and loyalty. To do this, merchants must ensure processes and procedures work seamlessly. Understanding payments and the processes needed to complete them successfully is a big part of this. A payments expert will understand that tracking and measuring the above KPIs will help with mitigating the loss of online sales. Ensure optimal functioning of your payment systems by utilizing proper payment metrics.