Payment Method Data Isn't Just for Your Settlement Team — You're Missing Sales Opportunities

"Isn't the payment method just whatever the customer happens to pick?"

Yes. Whether a shopper taps a credit card, Naver Pay or bank transfer at checkout is the customer's call. It looks like there's no room for the brand to intervene.

But there's a trap in that question. Customers do "choose" their payment method, yet that choice is anything but random. Which customers use which payment methods is tightly linked to their purchase intent, order size and likelihood of buying again.

In other words, payment method data isn't just a "payment log" — it's a segment signal that tells you who your customer is.

Brands that actually break their data down by payment method tend to discover things like these:

• Bank transfer customers have an AOV (average order value) 2x that of card payers

• Easy-pay customers repurchase at a rate 10pp or more higher than regular card payers

• Virtual account payments are canceled at 4x the rate of card payments

• Once fees are factored in, the #1 channel by revenue is no longer #1 by margin

This article covers four patterns that show up again and again in payment method data, the actions you can take on each one right away, and how to check all of it in Laplace in under 5 minutes.

First, a quick self-check for your brand

If your answer to even one of the questions below is "I don't know," this article is for you.

1. Is the AOV of your bank transfer customers higher or lower than that of your card customers?

2. Who repurchases more often: customers who paid with Naver Pay or those who paid with a regular credit card?

3. How many orders were auto-canceled last month because the virtual account was never funded, and how much were they worth?

4. Have you ever ranked your channels by net margin on what you actually receive, after every channel and payment fee is deducted?

If you can't answer these four questions, it's usually not the brand's fault. It's how channel admin consoles are built.

In the Cafe24, SmartStore and Coupang Wing admin consoles, payment method data is buried in the settlement screens. Every channel classifies payment methods differently, so you have to log in to each admin separately, download spreadsheets and merge them by hand. Payment method data is the classic "I'd love to see it, but there's no easy way to" dataset.

Why payment method works as a segment signal

When customers pick a payment method, they subconsciously weigh the following factors.

As these factors overlap, the payment method becomes a proxy that tells you "what kind of order this is." That's why splitting AOV, repurchase rate and cancellation rate by payment method brings the outlines of your customer segments into view.

Dimensions you can analyze by payment method

Laplace unifies order data from every channel, so you can slice payment data by the following dimensions.

The key is that you can freely cross these dimensions with channel, product, period and customer metrics (Repurchase Rate, LTV). A channel admin only shows you "revenue by payment method on this channel," but unified data lets you see "the 90-day repurchase rate of easy-pay customers across all channels combined."

Pattern 1. Bank transfer = a bulk-order signal

Here is payment method data from a household goods brand.

Card:              AOV KRW 42,000  |  Avg. basket 2.1 items
Bank transfer:     AOV KRW 85,000  |  Avg. basket 5.8 items
Virtual account:   AOV KRW 72,000  |  Avg. basket 4.2 items

The AOV for bank transfers is 2x that of cards. The reason is simple: it's a way to pay a large amount without worrying about card limits or instant approval, so gift sets, office group orders and reseller-style bulk purchases all gravitate to bank transfer.

Why it matters

These customers are effectively closer to B2B buyers, yet most brands treat them exactly like regular B2C shoppers. In effect, they're texting bulk buyers a "10% off your first order" coupon.

Actions you can take right away

• Split out bank transfer + high-AOV customers as a separate segment. Instead of coupons, show them "dedicated bulk-order consultations," "tax invoice information" and "recurring order discounts."

• Reprioritize CS. A large share of bank transfer inquiries are "has my payment been confirmed?" questions. Simply adding an automatic payment-confirmation KakaoTalk notification cuts this CS volume significantly.

• Use it as evidence when deciding whether to open a B2B channel. Once bulk bank-transfer orders exceed a certain share of monthly revenue (e.g. 15%), it's time to consider a separate business-only store or wholesale channel. You can make that call based on data, not gut feeling.

Pattern 2. Easy-pay customers repurchase more

Regular card:   Repurchase rate 28%
Naver Pay:      Repurchase rate 38%
Kakao Pay:      Repurchase rate 35%

Easy-pay customers repurchasing at a rate 7–10pp higher than regular card payers is a pattern observed again and again, regardless of category.

Why it happens

Payment friction is low. There's no need to re-enter a card number; checkout is done in a few taps with a saved method. The moment where a customer "wanted to buy again but gave up because it was a hassle" simply disappears. The effect is especially strong in low-involvement, repeat-purchase categories (household goods, food, beauty consumables).

Actions you can take right away

• Move easy pay to the top of your own store's checkout. Especially on mobile. Something as small as the order of payment options affects repurchase conversion.

• Encourage easy-pay registration at the first purchase. A nudge like "earn points instantly when you pay with Naver Pay" isn't a first-purchase discount — it's an investment that lowers the hurdle for the second purchase.

• Branch your repurchase campaigns by payment method. Send product-focused messages to customers with a registered easy-pay method and convenience messages like "check out in 1 minute" to those without one, and the same campaign will draw a different response rate.

A word of caution

A higher easy-pay repurchase rate doesn't prove that "easy pay creates repurchases." It could be that customers who are already inclined to repurchase are the ones who register easy pay in the first place (reverse causality). Either way, the fact remains that easy-pay registration is a strong signal for predicting repurchase likelihood, and actions that lower the payment hurdle carry no downside under either interpretation.

Pattern 3. Revenue rank and margin rank are different — PG fees

Own store card payment:     PG fee rate 2.5%
Easy pay (Naver Pay):       PG fee rate 3.85%
Marketplace (Coupang):      Marketplace fee rate 10.8%

On the same KRW 100,000 sale, what you actually receive comes to KRW 97,500 / KRW 96,150 / KRW 89,200 depending on the payment path. Add marketplace ad spend and fulfillment costs, and the gap widens further.

Why it matters

Most brands judge performance by channel "revenue." But when you re-rank by net margin after fees, it's actually common for the #1 channel by revenue to drop to 2nd or 3rd by margin. Without knowing this, you keep making the same decision to pour more ad spend into thin-margin channels.

Actions you can take right away

• Review a net margin table by channel × payment method once a month. Re-rank channels by revenue − PG fees − marketplace fees. In Laplace, adding the pg_fee dimension does this calculation automatically.

• Design a program that steers payments to your own store. Grow the share of low-fee paths with reward points, interest-free installments and bundles available only in your own store. If the fee gap versus marketplaces is 7–8pp, spending 3–4% to steer customers to your own store still leaves you ahead.

• Decide on expanding easy pay together with Pattern 2. Easy pay costs more in fees but drives higher repurchase rates. You need to compare "an extra 1.35pp in fees vs. a 10pp rise in repurchase rate" from an LTV perspective to make the right call. And that comparison requires repurchase data by payment method.

Pattern 4. Cancellation rate by payment method — a quiet operational leak

Card:              Cancellation rate 4.2%
Bank transfer:     Cancellation rate 12.8%
Virtual account:   Cancellation rate 18.5%

Bank transfers and virtual accounts are payment structures with a state of "order placed, but not yet paid." The share of orders auto-canceled for non-payment before the deadline is overwhelmingly higher than for cards.

Why it matters

Non-payment cancellations are lost revenue and, at the same time, an operating cost. Orders that will never be paid tie up inventory; for items close to selling out, they create the opportunity cost of real buyers being unable to purchase; and they even trigger CS tickets asking "I paid, so why was my order canceled?"

Actions you can take right away

• Automate payment reminder notifications. Simply sending KakaoTalk notifications on D-1 and the morning of the payment deadline meaningfully lowers the non-payment cancellation rate. Even bringing an 18% cancellation rate down to 12% recovers several million won in revenue per month for brands with a large share of virtual account orders.

• Retarget customers whose orders were canceled for non-payment. These customers "got right up to the point of purchase." A message within 24 hours of cancellation, such as "Would you like us to add the items you ordered back to your cart before they sell out?", converts better than a standard cart reminder.

• Separate inventory statuses. Manage orders awaiting payment in a different status from confirmed orders, so that provisionally reserved stock doesn't distort the inventory actually available for sale.

Summary: Pattern → Data → Action

Check it in Laplace in under 5 minutes

To run this analysis in channel admin consoles, you'd have to download spreadsheets per channel, manually align payment method classifications and join them with customer data. In Laplace, data from every channel is already unified and standardized, so all it takes is adding a dimension.

Step 1. Payment statistics screen → Add dimension → select pay_method or pay_service

Step 2. Compare revenue, AOV, number of purchasing users and repurchase rate by payment method side by side — first check for any metric that differs by 2x or more from card payments

Step 3. Add the pg_fee dimension → identify payment paths with a high revenue share and a high fee rate

Step 4. Compare cancellation rates for bank transfer and virtual account against cards → if the gap is large, start by automating payment reminders

Step 5. Cross-check easy-pay share × repurchase rate → decide whether to expand easy pay or change its placement order

Not sure where to start? We recommend that brands under heavy margin pressure begin with Step 3 (fees), and brands with a heavy CS/operations burden begin with Step 4 (cancellation rate). Both are areas that yield actions you can execute within the first week.

Customers choose their payment method. But that choice carries signals about who they are, how much they'll spend and whether they'll come back. Whether you leave those signals in your settlement team's spreadsheets or use them as raw material for segment strategy and margin management is up to your brand.

Check your brand's payment method patterns in Laplace payment statistics now. It takes just 5 minutes to answer the four self-check questions above.