Cash on delivery does not describe every way a customer pays

The comparison begins with a specific sequence of questions. Respondents said they had personally used a phone or computer to buy something online that was delivered during the previous 12 months. They then said they usually paid in cash when it arrived. Purchases arranged solely through a phone call were outside the online-shopping question.^[5]

“Usually” matters. The survey did not establish that these people always used cash. People who answered “both” to the usual-payment question formed a separate category and are not included here. That answer also does not establish an equal split between cash and online payments.

There is another important boundary before those questions. The original questionnaire used responses about an account, debit card or mobile-money service to decide who received them. Our group therefore comes from that screened population. We cannot use these results to describe people without accounts, or to estimate the share of all cash-on-delivery customers who use digital payments.

For the main calculation, we kept the usual-cash respondents who answered yes or no when asked whether they had made an in-store payment by phone or card in the previous 12 months. This creates a comparison between two answers from the same person, rather than combining unrelated national statistics.

The main results show the share reporting at least one in-store phone or card payment during the previous 12 months. They are weighted using the final survey weight supplied for each country.^{[1][2][3][4][7]}

The method section shows how unknown answers affect the estimate. Those missing-answer bounds are separate from sampling uncertainty.

The sample sizes in the first table count people answering the in-store question, not a country’s cash-on-delivery population. Someone who bought once and someone who bought repeatedly each provide one response. The survey weight determines their contribution to the weighted calculation; it does not turn their answers into a count of purchases.

A person can appear in both groups without any contradiction: usually paying cash for delivered online purchases and having paid by phone or card in a store. For a seller, the useful finding is the overlap itself. The survey did not ask that person to choose between two permanent identities, “cash customer” and “digital customer.”

These figures do not say how many online orders were paid in cash, how much money changed hands, or whether a particular buyer would switch payment methods. We also do not use them as a country league table. The estimates describe separate survey groups with different samples and fieldwork periods.

A survey respondent does not necessarily represent the same number of people as another respondent. The World Bank's final weights account for unequal selection probabilities and adjust the sample using population information. We used those supplied weights without trimming or pooling them across countries.^[6]

The unweighted calculation asks a simpler question: what fraction of the responding people in the released sample answered yes? Showing it alongside the weighted estimate makes the role of weighting visible.

Both percentage columns in the main results table use the same respondents and the same yes-or-no answers. Only the contribution of each respondent changes.

The Philippines illustrates why this check belongs beside the headline. Its weighted estimate is 12.5 percentage points above its unweighted estimate, using the unrounded calculations. The overlap exists under both calculations, but its estimated size is sensitive to how respondents are weighted.

We did not analyze which demographic characteristics explain that weighting difference, and it does not describe a change in behavior over time. When quoting the Philippines result, a seller or researcher should retain the weighted label and the accompanying sensitivity check, rather than treating 34.3% as an exact share of today's customers.

The in-store question covers any use during the previous 12 months. A follow-up asked those users how often they paid by phone or card in a typical month. This helps distinguish occasional use from a more frequent routine, within the smaller group that reported in-store use.^[5]

That last detail affects the reading of the first row. Indonesia's 50.1% in the lowest category should not be described as a group with a regular monthly digital-payment habit. The category is broad, and the typical-month question differs from the earlier question about any use over a year.

For these supported breakdowns, frequency-answer coverage was complete in Indonesia and Thailand and more than 99% by survey weight in Malaysia. Malaysia’s outward-rounded missing-answer bounds are 51–52% weekly, 30–32% monthly and 17–19% less than monthly. Each category has its own bound; their upper endpoints do not form a distribution. With complete answers, Indonesia’s and Thailand’s bounds coincide with their displayed estimates.

The Philippines remains in the main analysis. Only its frequency breakdown is withheld from comparison because that smaller subgroup failed our prespecified respondent-count and weight-only effective-size criteria. A blank frequency result means the evidence was too thin for that breakdown, not that nobody used those payment methods.

Begin with the information a payment choice actually supplies. It may tell the team how to collect payment for an order. It does not, on its own, explain the customer's reason, confidence, financial access or experience elsewhere.

For a creator launching physical merchandise or a business selling through social media, this distinction matters when writing order instructions. Explain which methods the business really accepts, when payment is due, and what happens at delivery. Avoid adding a story about the customer's skills or motives unless the customer has supplied it.

The same distinction can improve customer research. Instead of asking “Why don't you use digital payments?”, try “What made cash on delivery the right choice for this purchase?” The second question leaves room for a person who already pays digitally in another setting. Ask a separate question if you need to understand that other setting.

Possible explanations can become questions for a seller's own customers. They are not findings from this study. These survey fields do not identify trust in a particular store, a delivery concern, available funds or a reason for choosing cash. Reporting one of those explanations as the cause would add information the data do not contain.

The analysis also does not choose a checkout policy. Keeping, removing or changing a payment option involves the business's own costs, operations and customer evidence. Our result supports a better starting question, not a promise that a change will increase sales.

Imagine a creator selling printed notebooks who offers payment through a checkout or cash on delivery. In this fictional example, an order record shows that a customer selected cash.

The seller's first draft of a customer note says: “This buyer does not use online payments.” The order record does not support that statement. A more accurate note is: “Cash on delivery selected for this notebook order; reason not yet known.”

The seller then asks an optional question: “What made this payment option work best for this order?” In the fictional reply, the customer says that somebody else will receive the parcel and handle payment. The seller records that explanation as the customer's account of this purchase. It is not turned into a rule about other buyers.

A separate, optional conversation establishes that the same fictional customer pays by card in shops. That answer can sit beside the delivery choice. It does not cancel it, prove willingness to prepay for the next order, or establish which checkout explanation will persuade the customer.

The seller confirms the delivery arrangements and corrects the unsupported customer label.

Use these fields in an existing customer-research or order-review document. No sign-up is needed.

1. Purchase context: [product] · [sales channel] · [delivery arrangement]. Distinguish this order from a customer's usual behavior.

2. Payment observation: [method selected, or customer's description of their usual method] · [source of this information].

3. Business information: [methods genuinely offered] · [when payment is due] · [delivery instructions given to the buyer].

4. Customer explanation: [answer to an optional question about this purchase]. If there is no answer, write “reason not known.”

5. Other payment contexts: [relevant information the customer chooses to share]. Do not infer it from this order.

6. Next action: [specific clarification or operational follow-up] · [owner] · [review date]. Link the action to the information above.

Before using the notes to brief a campaign or change an order page, ask whether each sentence describes an observation, a customer explanation or an untested idea. If several customers raise the same issue, that is a lead to investigate with a defined sample. It does not turn these four national survey estimates into a forecast for your store.

We used the four versioned country releases of the World Bank's Global Findex 2025. Gallup conducted the surveys in 2024 among civilian, noninstitutionalized adults aged 15 and older. The country samples used face-to-face interviews, with the coverage qualifications described in the source methodology.^{[1][2][3][4][6]}

We fixed the questions, country set, calculations and support criteria before examining the joint outcomes. The primary calculation divides the total survey weight of in-store phone or card users by the weight of respondents giving a yes-or-no answer, within the usual-cash group. Each country has its own calculation.

Unknown answers are not recoded as “no.” We assess how much of the group answered the question and calculate bounds that assign every unknown answer first to “no” and then to “yes.” These bounds concern missing answers only; they are not confidence intervals. Small response groups and details that could reconstruct them are withheld from the public tables.

The sequence also explains why the figures use different groups:

1. Original responses about an account, debit card or mobile-money service determine which questions are asked.

2. A delivered online purchase in the prior 12 months and usual payment in cash define the group of interest. The separate “both” answer is excluded.

3. Known yes-or-no answers about in-store use form the main percentage's denominator.

4. Known frequency answers among in-store users form the smaller frequency denominator.

All four main country groups passed the predefined checks for sample support, response coverage and concentration of survey weights. The frequency breakdown passed for Indonesia, Malaysia and Thailand. Those checks are safeguards for presenting a descriptive result; they do not establish statistical precision.

The released files do not supply the full sampling-design information needed for our conditional estimates' design-based confidence intervals. We therefore do not attach significance tests or claim country rankings. The surveys also used different fieldwork windows and asked respondents to recall the preceding year.^[6]

A second calculation independently reproduced the fixed aggregate results. The downloadable method and code explain the definitions and calculations; individual survey records are not redistributed. These are historical survey findings, not a live measure of payment behavior in 2026.