Payments Data: Power up your business using payments insights

How payments data can help you grow your business using real-time research, performance optimization analysis and more.

Using data to create a business strategy is nothing new, but it’s often hard to break down the amount of information that’s available and useful to your business, like understanding your customers better.

Why payments data?

Picture this modern purchase journey:

A customer enters your store, restaurant or hotel. They’ve bought via your website and in other locations before. Today, they’ve paid with a credit card, gave an email address to receive their e-receipt and scanned their loyalty card. It’s simple, yet this short process shows five pieces of payments data a modern payment provider can see about the customer:

  • They’ve used your e-commerce platform in the past
  • How frequently they shop at this particular location
  • If they have credentials on file you can add to
  • Their email address
  • The country of their card issuer

This may not be new to you, however, what happens when a customer forgets to bring their loyalty card and you can’t recognize them at the checkout? By linking earlier transactions made online or in store, we’re able to help you recognise your customers.

Now let’s look at how to learn more about customer behaviour using payments data.

1. Addressing customer needs with real-time research

It’s hard to know what your customers truly want. Field research and focus groups can help you understand customer segments and how best to position your business or its products, but the problem with these approaches is that they only show a snapshot in time. They’re also costly, take a lot of resources, and the information quickly becomes out of date.

Payments data provides a picture of customers and their purchases in real-time, so you can investigate your customer segments, their behaviour and test what works best for them.

A great way to put this real-time data to work is by using the recency, frequency, monetary value (RFM) methodology as a framework. With this, it’s possible to split the customer base to find a frequent visitor segment. Within this segment, you may then start to analyze the average transaction amount online or on-site, or start to catalogue what behaviours lead to loyalty. Because you’ve now identified your valuable customers you can start to tailor your strategy.

Here’s a list of data points you might like to explore:

(Data point – Description)

Frequency – Number of visits to one or more of your physical, web or app stores

ATV – Average transaction value based on date, location or customer segment

Recency – Last visit by date or time

Sales channel – Transactions by physical, web or app stores

Customer lifetime value – Continuous tracking of transactions across a customer group to understand their monetary value, behaviours and churn rate

2. Optimizing store performance

There are many ways to measure store performance. Most often it’s based on store size or sales data. With payments data, you can be honest about performance by using richer data.

For example, if you were to analyze a single store’s performance, you could see how many new or returning customers it’s attracting and what level of returns or refunds to expect.

You can also match stores based on a range of performance drivers. Stores with similar performance profiles can be used to A/B test interior layouts, offers, or in-store innovations like self-service kiosks. Stores with different profiles can share learnings such as how to increase spend in fewer visits or differentiate experiences for high traffic sites.

Finding the perfect distance between stores and where to expand your presence is also easy when you use payments data. Delivery addresses from your e-commerce site can help to show where your customer base is. Once you know where you should (and shouldn’t) be opening stores or distribution centres, you can test with pop-ups to make sure you have the right inventory and payment method mix.

Then, when it comes to opening day have confidence that the right price point, payment methods and channels are offered.

People shopping with a credit card

3. Use data to keep customers coming back for more

Any marketer will tell you that retaining customers is about surfacing relevant messages in the right place at the right time. This is where unified payments data becomes useful. You can find customers that haven’t shopped with you for a while and apply the right loyalty bonuses, personalised offers, or even survey them. By understanding you’re returning customers’ sales channel preference, average transaction value and frequency, you know when, what channel and what price point to use so they’re back shopping with you.

Unified payments data also helps to simplify cross-channel customer experiences by storing information in one place. Take the following example:

  1. A returning customer makes an online purchase, a pair of jeans, but they’re not quite right. They want to exchange them quickly, as it’s for a party and they want to look their best.
  2. They go to their nearest store but to their horror, realize they’ve forgotten the receipt.
  3. The sales assistant has good news. They can find the order history through their credit card or via their transaction history on their Merchant App.
  4. The customer picks up an alternative and a partial refund is actioned. Based on the full order history a real-time discount is applied. Everyone is happy.
  5. Across these different categories, each stage (purchase, exchange, loyalty) is connected to that customer.

That’s the insights enabled future experience consumers and merchants want.

Get in contact with our experts here at Youtap to learn about how we can work together to unlock your insights enabled customer experience.