Customer Support Refund Approval Workload Statistics 2026

Refund work rarely ends when an agent clicks approve. A support team may verify the order, interpret policy, request evidence, secure a supervisor decision, update the customer, and answer another contact while the bank posts the credit. A denied or delayed request can then move into an escalation or card dispute.

The current public evidence does not provide one universal average handle time or approval rate for refund tickets. It does show the scale of return demand, the time customers may wait after approval, the cost of repeated contacts, and the growing chargeback load. These customer support refund approval workload statistics for 2026 keep those populations separate and identify where an internal estimate is still required.

Refund approval workload benchmarks at a glance

Sources: NRF and Happy Returns, Stripe, SQM Group, and Mastercard.

Return demand creates the potential refund queue

The National Retail Federation and Happy Returns project $849.9 billion in U.S. retail returns during 2025, equal to 15.8% of annual sales. They estimate that 19.3% of online sales will be returned. A return does not always produce a refund request or a support contact, but these figures describe the transaction pool from which approval work arises.

The research used two summer 2025 surveys. The consumer survey covered 2,006 people who had returned at least one online purchase in the prior 12 months. The merchant survey covered 358 ecommerce professionals at large U.S. merchants with more than $500 million in revenue. The findings therefore describe active returners and large merchants, not all consumers or small businesses.

Demand is also shaped by customer expectations. NRF reports that 76% of surveyed consumers were more likely to choose a return option with an instant refund or exchange. Meanwhile, 64% of surveyed merchants said updating their return process in the next six months was a priority. Faster customer promises can move work earlier in the journey because teams must make an approval decision before an item completes the full reverse-logistics process.

Support leaders should not convert retail return value into ticket volume. The operational denominator should be the number of refund requests received. Segment that volume by channel, reason, amount, product, policy outcome, and whether an item return is required.

Approval time and bank posting time are different clocks

Stripe's February 2026 business guidance says credit and debit card refunds typically appear in a customer's account within 5 to 14 business days, depending on the network and bank. Stripe also notes that some businesses wait until an item is received or reviewed before issuing the refund. That wait extends the total customer journey.

This published range is a payment-posting measure. It is not a benchmark for how long an agent or supervisor should take to approve a request. A support operation needs at least four timestamps:

1. Request received
2. Decision made
3. Refund submitted to the payment provider
4. Credit visible to the customer

Measure internal approval cycle time from the first timestamp to the second. Measure operational fulfillment from approval to submission. Treat the final interval as external posting time, but keep ownership of status communication. Otherwise, a five-day bank wait can look like a five-day support backlog, while an internal two-day approval delay can disappear inside one blended figure.

Report the median and the 90th percentile. A median can improve even while a smaller group of exception cases sits unresolved for weeks. Break out approved, denied, pending evidence, fraud review, and supervisor review because each status creates different work.

Repeat contacts can become a quarter of contact volume

SQM Group reports that repeat calls account for about 540,702 calls, or 26% of annual call volume, in the average contact center it benchmarks. Its model puts the annual cost of those calls at about $4.8 million. SQM also reports a 70% average first-call resolution rate.

These are general contact-center benchmarks, not refund-only observations. They show why a refund workload model that counts only initial requests will understate labor. A customer may contact support again because the approval is pending, the credit is not visible, the amount is wrong, or a denial was not explained.

Use a same-intent repeat-contact rate for refunds:

repeat-contact rate = refund cases with another customer contact inside the stated window / refund cases opened

Choose and publish the window, such as 7, 14, or 30 days. Link email, chat, phone, and messaging contacts to one case. A channel switch does not make the second attempt a new issue.

Refund status contacts should also be split by stage. A contact received before the business has made a decision signals an approval backlog. A contact received after submission may signal poor expectation setting or a bank-posting delay. The response and the staffing fix differ.

Escalations add review touches to each case

Refund approval rules often use thresholds for amount, customer history, return condition, fraud risk, or policy exceptions. Each threshold can create another handoff. The useful measure is not simply the share escalated. Teams also need to know how many people touched the case and whether the escalation changed the decision.

For every refund case, record:

• Number of agent, supervisor, payments, fraud, and finance touches
• Time waiting in each queue
• Reason for escalation
• Whether the higher tier approved, denied, or returned the case for missing information
• Number of customer updates sent while the decision was pending
• Total handling minutes and total elapsed time

The customer support escalation rate statistics review cites an older HDI technical-support benchmark in which 28% of incidents moved beyond the first level. That figure should not be imported as a refund target. Technical incidents and financial approvals have different policies, risks, and access controls. It does, however, illustrate why definitions must specify the starting tier and destination.

Slow or unclear refund handling can shift work into chargebacks

Mastercard-sponsored 2026 research with Javelin surveyed 300 executives at large merchants and issuers. It found that consumers bypassed the merchant and went directly to the issuer in 75% of disputes. Among the cases that reached merchants, the merchant resolved 44% by answering the customer's question and 31% by issuing a refund or replacement.

Those observations do not prove that a slow refund caused every dispute. They do show an opportunity for support to resolve some problems before they enter the formal chargeback process. Clear transaction details, accessible contact options, visible status, and timely refund decisions can reduce avoidable confusion.

The same research reports that merchants handle an average of 5,950 customer inquiries per month. It also estimates average merchant cost per chargeback at $46 in third-party fees plus $82 in internal costs. The report says 35% of merchants found chargeback management challenging or severely challenging. These are survey results from large merchants and issuers, not universal unit costs.

Mastercard's 2025 chargeback outlook, based on Datos Insights research in the United States, United Kingdom, Brazil, and Australia, forecasts 324 million global chargebacks in 2028, a 24% increase from 2025. Merchants identified about 45% of their chargeback volume as fraudulent, though Mastercard says the share varies by country and industry. More disputes increase evidence collection, customer communication, financial review, and deadline tracking across support and back-office teams.

Build a refund workload forecast from measured inputs

There is no defensible public ratio that converts retail sales or return dollars into customer support staffing. A team can build an internal forecast with six measured inputs:

monthly workload hours = (new requests × minutes per first review + repeat contacts × minutes per contact + escalations × minutes per escalation + chargebacks × minutes per response + total after-contact minutes) / 60

Suppose a team receives 10,000 refund requests in a month. If its own sampled data shows 7 minutes for first review, 1,800 repeat contacts at 5 minutes each, 1,200 escalations at 9 additional minutes, and 300 chargeback responses at 25 minutes each, the estimated workload is 1,622 hours before meetings, training, breaks, and absence coverage. This is an illustrative calculation, not an industry benchmark.

The example also shows why approval volume alone is weak. First review contributes 1,167 hours, while repeat contacts, escalations, and chargebacks add another 455 hours. A policy or status update that prevents repeat work can free capacity even when incoming refund demand stays flat.

Track forecast error by week. Refund volume can change with promotions, holidays, product defects, delivery disruptions, or policy changes. The NiCE 2025 workforce survey of 400 contact-center leaders in North America and EMEA says multichannel work is creating scheduling and forecasting problems. It reports an average unmanaged attrition rate of 39% in 2024, compared with 49% in 2023. The statistic is not refund-specific, but it supports using actual availability rather than nominal headcount in capacity plans.

A practical 2026 refund workload scorecard

Publish the denominator and time window beside every rate. Compare like-for-like segments. A fraud-review queue should not be judged against instant approvals, and bank posting time should not be counted as agent processing time.

Teams that need more coverage for status updates, evidence collection, and policy-guided triage can review customer service support. A customer service virtual assistant can take structured follow-up work while supervisors retain approval authority and exception handling.

Sources

1. National Retail Federation and Happy Returns, Consumers Expected to Return Nearly $850 Billion in Merchandise in 2025, October 15, 2025. Includes results and methodology for 2,006 consumers and 358 ecommerce professionals at large U.S. merchants.
2. National Retail Federation, 2025 Retail Returns Landscape, 2025. Research overview covering return rates, consumer preferences, and fraud.
3. Stripe, Refunds for businesses: A guide to their meaning, timing, and financial impact, updated February 22, 2026. Payment-method timing and process guidance.
4. SQM Group, First Call Resolution Operating Strategies, accessed October 7, 2026. Benchmarks for first-call resolution, repeat calls, and modeled repeat-call cost.
5. Mastercard and Javelin Strategy & Research, Chargebacks: The case for coordination, 2026. Survey of 300 executives at large merchants and issuers.
6. Mastercard and Javelin Strategy & Research, Chargebacks: The Case for Coordination, 2026. Merchant inquiry, resolution, cost, and workload findings.
7. Mastercard and Datos Insights, 2025 Global Chargebacks Outlook, 2025. Global forecast and merchant chargeback findings based on research in four countries.
8. NiCE and Simpler Media Group, 2025 Workforce Management Trends for Contact Center Leadership, 2025. Survey of 400 contact-center leaders split evenly between North America and EMEA.