Adobe reported $20 billion in buy now pay later online spending during the 2025 U.S. holiday season. Against its $257.8 billion overall online-spending total for the same period, that is approximately 7.8%. The share is a TrueMargin calculation from Adobe's published totals, not a global BNPL market-share estimate.[1]
BNPL statistics become confusing when holiday spending is compared with a provider's annual payment volume or company revenue. All can be useful numbers. They measure different parts of the business, and combining them without checking geography, period and product scope can produce a meaningless market-share calculation.
The key BNPL figures have different units and reporting periods
This comparison keeps observed results separate from forecasts and provider operating metrics. The goal is a useful reference table, not a single headline total made by adding unrelated figures.
| Measure | Reported figure | Scope | How to use it |
|---|---|---|---|
| Adobe BNPL online spending | $20 billion | U.S., November-December 2025 | Completed-season payment-method spending |
| Adobe BNPL online spending forecast | $21.3 billion | U.S., November-December 2026 | Planning estimate, not final sales |
| Klarna GMV | $127.9 billion | Provider global full year 2025 | Company-reported merchandise volume |
| Klarna revenue | $3.5 billion | Company full year 2025 | Company revenue, not merchant sales |
Sources: Adobe 2025 season recap, Adobe 2026 forecast and Klarna full-year results. Klarna's overall GMV should not be relabeled as the size of the U.S. holiday BNPL market.
The company figures are context, not a numerator for the Adobe dataset. A worldwide year contains a different geography, more months and potentially a different mix of payment products. Provider revenue is another step removed: it describes what the provider recognizes as revenue, rather than the entire value of merchandise consumers bought.
Same-scope totals produce a useful holiday spending share
The 2025 calculation is $20 billion divided by $257.8 billion, or approximately 7.76%. Rounded to one decimal place, BNPL represented approximately 7.8% of the online spending in Adobe's holiday analysis. The numerator and denominator refer to the same publisher, geography and seasonal window.
Adobe's 2026 forecast gives $21.3 billion in BNPL spending and $275.1 billion in total online spending for the holiday season.[2] Dividing those displayed forecast values produces approximately 7.74%, also 7.7% to one decimal place. Both the input values and the derived share remain forward-looking.
The nearly similar ratios illustrate why dollar growth does not automatically mean a large increase in payment-method share. The method's dollar volume and the surrounding ecommerce market can grow at roughly similar rates. A rising spending headline should not be paraphrased as equally strong share growth.
Do not overinterpret tiny differences between ratios calculated from rounded published totals. The arithmetic can be exact for the numbers displayed while the underlying quantities are more precise. A reasonable citation uses approximate language and keeps the calculation visible.
Spending share is different from order share and adoption
Spending share is the fraction of purchase value using BNPL. Order share is the fraction of orders using it. Shopper adoption is the fraction of people who use it within a defined population and period. A provider's active-customer count is yet another metric.
These distinctions affect practical conclusions. A payment method can account for a modest number of orders but a larger share of spending if its average order value is higher. The reverse can also happen. Without order counts, a spending ratio cannot reveal the fraction of shoppers who chose the method.
A single shopper can place more than one order and use multiple payment methods. Adding provider customer counts can therefore double-count people. Similarly, a survey asking whether someone has ever used BNPL will not answer how often they used it during the most recent holiday season.
For a merchant dashboard, choose the unit before building the chart. Use the order ID for a payment-method order count, the appropriate sales amount for spending share, and a clearly defined customer identifier for shopper adoption. Show unknown or unclassified payment records rather than silently treating them as another method.
Higher order value alone does not establish incremental profit
A merchant considering BNPL needs to distinguish the value of orders using the method from the additional contribution caused by making the method available. These are different questions. Customers choosing the method may already have intended to purchase, and their products or basket sizes may differ from other customers'.
A transparent first step is a payment-method contribution view. Start with the same sales boundary for each group, then include product cost, applicable payment charges, refunds and any other costs allocated under the store's accounting method. Document which costs are included and avoid deducting a charge twice.
Consider an illustrative set of 100 orders using a payment option. Assume average net sales of $120 per order, product costs of $48 per order and a hypothetical payment charge of $6 per order. Before other costs, contribution is $66 per order: $120 minus $48 minus $6. Across the set, that is $6,600.
Those values are hypothetical and are not a statement of any provider's pricing. They describe the contribution on the observed order set under the example assumptions. They do not establish that all 100 orders were caused by offering that payment option.
To estimate incremental value, the merchant needs a credible counterfactual: what would the same business have generated without the option? A suitable test design should address changes in traffic, promotions, products and customer mix. A simple before-and-after revenue chart can be informative but does not automatically isolate the payment method's effect.
A payment-method comparison starts with compatible records
Export orders for a fixed period and identify the method recorded at checkout. Use consistent treatment of canceled orders, refunds, taxes, shipping and discounts. A dashboard based on checkout events may not match a finance export based on settled or retained sales, even when both systems are operating correctly.
Separate gross activity from net outcomes. If an order is later refunded, the purchasing event still occurred, but the merchant's retained sales changed. An external industry spending statistic may use a different boundary, so keep its context alongside the internal comparison instead of forcing a numerical match.
For operations, add the timing dimension. The customer payment schedule and the merchant settlement schedule are not interchangeable. Compare actual settlement records under the agreement rather than assuming that consumer installments map directly to the merchant's cash receipts.
TrueMargin recommends keeping a short metric dictionary beside the report. Define order count, net sales, payment cost and contribution in language the merchant can audit. The best comparison is one that can be reproduced from a clear set of records and assumptions.
A payment dashboard needs a visible time boundary
Keep purchase date and settlement date in separate fields. An order created near the end of a reporting period can settle later, so matching an order-based spending chart to a cash-based statement requires an explicit reconciliation. A difference between those totals is not automatically missing revenue.
When comparing providers, use the actual contract and settlement records for the store. Record adjustments and refunds against their associated orders where possible. This gives the merchant a reproducible bridge between the checkout event, retained sales and cash received, while preserving the reason each report contains a different total.
Methodology and limitations
This article reconciles primary Adobe and Klarna publications. The reported dollar values belong to those sources. The holiday spending shares are TrueMargin calculations using the displayed same-period totals. The merchant contribution example is illustrative and uses no private customer information.
We do not have the underlying transaction files, a complete product-level reconciliation of provider GMV, or a dataset that supports estimating provider share within Adobe's holiday sample. No such market-share claim is made. Company figures are included to explain measurement boundaries, not to compare the size of unlike markets.
The cited current-season figures are forecasts. They should be replaced or clearly paired with completed-season results when available. This article does not evaluate a consumer's borrowing decision or recommend a particular provider; its purpose is accurate merchant and publisher measurement.
Frequently asked questions
What share of holiday spending used BNPL?
Using the two displayed 2025 Adobe totals, the derived share is approximately 7.8% for its U.S. holiday analysis. That is spending share, not the share of all shoppers or orders.
Can provider GMV be divided by Adobe's holiday total?
Not to calculate a meaningful market share when geography, period and product scope differ. Use a numerator and denominator that describe the same market.
Is provider revenue the value of purchases financed?
No. Company revenue and merchandise volume are separate reported metrics. Preserve their original labels when citing financial results.
Does BNPL sales growth prove extra merchant profit?
No. Extra profit depends on incremental retained sales, product margins, payment costs and other relevant expenses. A sales headline alone cannot establish that result.
Related research: see how refunds affect advertising revenue reports for a worked application of these measurement distinctions.
Sources
- Adobe: 2025 holiday season recap, January 2026.
- Adobe: 2026 holiday forecast, September 2026.
- Klarna: full-year 2025 results, February 2026.