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How to use payment data to grow your business

                             Data will talk to you if you are willing to listen
                                                                                  Jim Bergeson

Today, businesses mostly dwell on a data-driven or data-informed approach to changes. It means they don't make important decisions out of the blue, and instead of poking around hoping for success, they rely on the actual data and build their growth strategies taking it into account. 

However, data itself is neither a life ring nor a magic wand. Its actual value unveils as we collect and analyse it, turn it into information, and then — into actionable insights.

During my work, I observed how clever businesses use their own operational data analysis to grow. And yet, for most, payment data stays out of scope, and so are the optimisation opportunities hidden in it.

This article will help you start using payment data for growth.

Step 1: Get the tool

If the company accepts online payments, it has a lot of data that can be analysed. But first, the manager needs to find a way of handling the aggregation and normalisation of all that data. The larger business becomes, the more sources of data are available, and it gets increasingly harder to get it all together. 

That's where dedicated data services platforms come in handy, allowing to collect, monitor, analyse, and reconcile payments.

Alternatively, data collection and analytics tools are something the company can ask its payment provider about. Not every payment gateway or processor offers it, but some do.

If the business works with multiple payment providers, the owner should consider a payment orchestration platform like Corefy. Besides making daily payment handling more efficient, it will also gather all the data under one roof and make it much easier to process it. With such a solution, all the performance metrics are spread before the eyes in real-time mode. Moreover, it's possible, quickly generate accurate and thorough reports and access intelligence on the go.

Step 2: Collect a payment data

Once the tool is available, it's time to collect data. It happens automatically as customers pay the company or vice versa, depending on the business model.

The more data is aggregated, the more a manager can get out of it. If the transaction flow is moderate, it's better to wait until a critical mass of data will be collected. But if the business is large and processes dozens of transactions every minute, the entrepreneur can experience the power of real-time monitoring. Live data empowers him with constant updates on his customers' behaviour and habits. 

As Douglas Fisher and Nancy Frey wrote, "Data that sit unused are no different from data that were never collected in the first place." Let's learn to use payment data!

Step 3: Analyse the payment data and take actions

Now let’s turn vague numbers into tangible and actionable information. Here are payment-related metrics I suggest looking for and brief explanations on how to interpret them.

Conversion rates

Conversion rate is the percentage of users who complete the desired action, most commonly — a purchase.

Conversion rate may be calculated through many perspectives. For example, our clients can monitor their conversion rate:

  • By the project, for comparative analysis and to know which one performs best. 

  • By the customer, to detect if there are users who incessantly enter a payment page and don't pay. We also provide the conversion rate breakdown by payment methods a customer used. Our clients could display best-performing ones at the top of the checkout page for each returning customer individually. 

  • By the provider, to analyse which transactions (depending on the currency, time, payment method, card brand, etc.) each one processes better and use this information for payment routing. 

  • With enabled and disabled CVV/3DS authorisation, evaluate the necessity of the friction caused and find the balance between security and conversion. 

  • In real-time, to monitor performance.

  • Over a selected period, to analyse past performance, etc. 

Decline reasons

By collecting and analysing transaction statuses, statistics and error codes, the company can unveil issues preventing payments from successful completion. Moreover, the owner can easily separate the decline reasons that require actions on the user's side (lack of funds, expired payment card, incorrect payment details, etc.) from those the owner (like bad UI/UX) or its payment provider (such as downtimes, transactions stuck in pending) can fix. Having the statistics on decline reasons, the business can improve success rates and avoid abandoned shopping carts by working with customers or payment providers. 

Authorisation rates

Considering authorisation rates, it is possible to learn which bank or payment provider handles particular transactions better and further route these transactions to them. It is handy for international businesses, as sometimes the payment setup they have in place may not be optimised for particular markets. Additionally, a low authorisation rate for an issuing bank may indicate that the company or its acquirer don’t send sufficient information or have a bad risk profile with this bank.

Payment methods usage statistics

By analysing conversion rates and usage statistics per every payment method which is connected, the owner can make sure the selection of provided options is optimal and sufficient for the particular market. It also allows saving costs by eliminating the need to support methods which customers don't use.  

Average transaction value and frequency

Understanding an average spending and transaction frequency per customer allows businesses to create more efficient and highly personalised targeted marketing campaigns. For instance, if a previously active buyer hasn't shopped on the current website for a while, the manager can offer a special discount or bonus to win their attention back. This way, the company has higher chances of retaining customers and building a loyal audience of returning buyers. Moreover, such information helps in operational and strategic planning. 

Users' behaviour on the payment page

Access to the statistical information about what users do at the payment page, how long it takes them, where they click, etc., provides the owner with underrated but precious insights. It allows revealing UX issues that lower the conversion or even prevent customers from checking out. Once, a quick look at user behaviour data helped us determine that one of our new clients suffers ~20% conversion simply because the payment page closes if a user misclicks the payment pop-up. Immediately after fixing this issue, our client reached over 80% conversion. Don't neglect user behaviour tracking!

Transaction fees

By knowing how much each transaction costs, the manager  can set up payment routing in a way that will help notably save on fees. For instance, a bank that issued a card is more likely to process a transaction using this card faster and cheaper than a different one. If terminals at various banks are used, intelligent routing will help to benefit from this fact. The owner can also integrate appropriate alternative payment methods if the owner transaction costs end up being too high. It is often an issue for cross-border card transactions. 

Balances

By keeping an eye on the balances at payment providers the company works with, the manager can use this information for payment routing to avoid undesirable zero or too high balances and diversify cash flows. 

To summarise. Taking payment data into account may be very lucrative if the company owner knows how to flash out this data. Hopefully, this post will draw attention to all these opportunities. 

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Denys Kyrychenko

Denys Kyrychenko

CEO & Co-founder

Corefy

Member since

19 May

Location

London

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This post is from a series of posts in the group:

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Fintech discussions and conversations around the development of fintech.


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