Payment data is one of the most useful byproducts of transactions and website traffic. As money flows into and out of any business, and visitors click around websites, thousands, if not millions, of data points are generated.
Buried in this mass of data are key insights that one can use to optimise their operations, improve their relationship with their customers, and grow one’s business.
But an effective approach to data requires you to understand which is important and how it can inform your decision-making.
This article presents the optimal metrics to monitor and outlines their effective utilisation for revenue optimisation, cart abandonment reduction, and enhanced conversions.
What is business payment data, and why is it important?
Whenever a customer makes a purchase, whether online or in-store, a wealth of data is generated. This raw business payment data can tell you what products were bought, the amount spent, the payment method used, as well as the time and location of the transaction.
It also provides the foundations for understanding the performance of your business at a granular level, granting insights into customer behaviour, sales, revenue over time, and notable trends that you can use to make impactful decisions both in the moment and to predict future trajectories for long term planning. But to make use of this data, you will need a powerful payment data analytics solution, which uses advanced software and techniques to transform the crude material into a usable product.
What types of payment data can businesses use?
There are several types of payment data that businesses should focus on when conducting payment analytics, including:
- Transaction data – the specific details of individual transactions, such as amount, location, method, time, and date
- Customer data – who made the purchase, their contact details, demographics, and purchase history
- Product data – the types and volumes of products or services sold, pricing, stock, and performance of specific products
- Payment processing data – the systems used to process transactions, fees incurred, settlement times, and authorisations and declines.
- Fraud data – data related to potentially fraudulent transactions, such as chargebacks, attempted payments with lost or stolen cards, and unauthorised payments
- Financial data – revenue, cash flow, overheads, and other costs that give you insight into the financial health of your business
How can businesses use data from payment analytics?
Knowing which types of payment data are useful to track is just the beginning. You also need to understand what these metrics can tell you about your business, and how you can use the data in your payments strategy to power effective decision-making.
Authorisation rates measure the percentage of attempted transactions that are successfully authorised and completed. If your authorisation rates are low, you’re losing revenue. They can also alert you to false declines (where legitimate payments are blocked as suspected fraud), a costly mistake for businesses that needs to be rectified as soon as possible. Using response codes, you can see why your unauthorised payments are being declined, and whether they’re soft declines, which you can reattempt; or hard declines, which you can’t. You can then determine suitable retry methods for different scenarios.
Fraud analytics looks for suspicious trends or anomalies in transaction data to identify potentially fraudulent activity. Fraud detection software employs machine learning to analyse massive amounts of data around the clock and in real-time, empowering you to effectively block or allow transactions using a risk-based system of rules. That means more legitimate transactions are authorised, helping to grow your business while preventing damaging illegitimate transactions.
It’s vital for merchants to keep on top of chargeback rates, the proportion of all payments that are disputed by customers. If you’re experiencing a high rate of chargebacks, you’re not only losing revenue but you could be flagged as risky by your card network and even placed on a program until you can bring your chargeback ratio back under a certain threshold.
Response codes are two to four digit sequences that tell you exactly why a transaction has been approved or declined, and understanding these reasons is essential to reacting effectively to any issue. For example, if you see that you’re experiencing a high number of declines due to a processing issue with the network, you can contact them promptly to get the problem resolved.
Your transaction data can be especially useful for understanding your customers’ preferred payment methods, helping you to create better payment experiences that result in increased loyalty and more successful transactions.
Your conversion rate tells you how many of your website visitors are actually completing purchases. While it can’t tell you exactly why, a poor conversion rate alerts you to the fact that there may be a weakness in your website design, marketing efforts, or customer journey that’s causing visitors to drop off without making a purchase.
Average transaction value
Average transaction value (ATV) is the average amount your customers are spending per purchase. A high ATV is healthy, indicating that your customers are buying high value, or a high volume of, products. A lower ATV indicates that you might need to rethink your pricing or product strategy to encourage your customers to make bigger, or more, purchases.
Clearing and settlement
The clearing and settlement of funds involve numerous entities and processes. Whether your business relies on fast settlement or deferred settlement, you should monitor when funds arrive in your accounts following transactions to check that they’re arriving on their expected schedule. If not, it could mean there’s an issue that’s preventing one or more institutions in the chain from meeting their obligations on time. You can then take action to address the issue before it impacts your liquidity.
If you are a subscription-based business, it’s important to keep track of your churn rate – the percentage of your customers that end their subscription in any given year. You’ll always have some churn, but if you notice that your churn rate is unusually high, you can take steps to improve customer retention and then use payment analysis to measure the results.
How can payment data improve business growth?
Having observed the empowering nature of payment data, organisations can leverage it to consistently enhance their payments strategy and proactively address any potential issues that may adversely affect their business. Here are practical examples of how this can be achieved:
- Revenue optimisation and pricing strategies – from understanding why payments are being declined to working out which products are popular; payment data should be at the cornerstone of your revenue optimisation and pricing strategies. For example, you can spot where you might be unnecessarily losing revenue and take action to recover it, refocus your marketing strategy around high-performing products (or promote underperformers), or redesign your customer journey to boost conversions and, therefore, revenue.
- Expansion into new markets – breaking down payment data by location can show you regional differences in all sorts of areas. You might discover that certain products are much more popular in one market than they are in another, or that customers in a particular country prefer a specific payment method. Armed with this data, you can optimise your strategies for more effective expansion into new markets.
- Reduced cart abandonment – according to the Baymard Institute, the average rate of cart abandonment is about 70%, with surprise extra costs, mandatory account creation, and slow delivery times cited as the most common reasons for giving up on a purchase. If you notice an unusually high cart abandonment rate, you should investigate and address any contributing factors to bring it back down and boost sales.
- Understanding customer behaviour – payment data is great for measuring your key performance indicators, but it’s also great for bringing a statistical aspect to customer behaviour. And by turning behaviour into data, you can track, understand, and influence it. For example, you can segment your customers into useful categories, allowing you to target them with demographically appropriate marketing materials, discover when and how they like to shop and find out if there are any consistent behavioural trends on the checkout page that could reveal why customers are abandoning purchases.
How to start accessing insights from payment data
Having highlighted the significance of payment data for organizations, let us now delve into effective strategies to maximise its potential:
1. Gain control of your payment data
Your business will produce an unwieldy amount of raw data, so you need to be proactive about keeping it organised and in a usable format. Firstly, using a self-service portal for your data tracking and reporting, rather than outsourcing to an external provider, will allow you to gain full control over your data and to use it how and when you wish. It also allows everyone on your team to quickly gain access to real-time, actionable data insights, meaning they can be responsive and decisive when necessary without having to waste time jumping through hoops. Secondly, you should attempt to aggregate data from multiple sources into a single view. This will make it easy to compare and draw meaningful insights from the mass of data produced.
2. Utilise data reporting tools
Data reporting tools make it easier to stay on top of, and reconcile, all your payment data. For example, you can set up webhooks to give you real-time notifications when key events occur. That way, you can get on with running your business, safe in the knowledge that you’ll be alerted to act when it matters. And with an API, it’s even easier to manage your data by automating reporting and reconciliation of key payment data.
3. Analyse the right payment data points
Put simply, the more data you must work with, the better placed you are to strategise, optimise, and take action. But it’s important to hone your approach to payment data by ensuring your tracking and analysis is effective and efficient. Focus on the metrics that really matter to your business, and that help you towards achieving your business goals. This may change over time. For example, sometimes you might need to work on reducing cart abandonment, and so have a laser focus on all data related to abandoned purchases. At other times, you might want to assess how a price change has affected sales.
4. Collect monthly reports
Collecting payment data reports every month is a good frequency. It’s regular enough to spot meaningful trends or changes, and not so often that it distracts you from other aspects of running your business. As stated above, as long as you have a focused and strategic approach to data, it can be your best friend for optimising your operations, boosting customer loyalty, and growing your business.
Checkout.com recognises the significance of merchants analysing their payment data efficiently with a platform that provides a seamless experience to visualise key payment data points and KPIs, empowering informed decision-making.
This article/report was first published by Checkout.com and has been republished on our website with permission.
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