Net 30 vs Net 60 vs Net 90: How to Choose Payment Terms in 2026
Net 30, Net 60, and Net 90 are payment terms: the number of days a customer has to pay after you invoice them. Shorter terms protect your cash flow, longer terms help you win and keep larger customers but tie up working capital. The right choice depends on how the customer pays, their credit risk, your own cash needs, and what is normal in your industry. Set terms from the account's behavior rather than from what the sales team wants, and revisit them as the risk profile changes.
What do Net 30, Net 60, and Net 90 mean?
Each term is a deadline. Net 30 means payment is due 30 days after the invoice date, Net 60 means 60 days, and Net 90 means 90 days. The higher the number, the longer you are effectively lending the customer the value of the invoice. That is the core trade-off: longer terms are a selling point for the customer and a working-capital cost for you, because the cash sits in receivables instead of your bank account.
Net 30 vs Net 60 vs Net 90 at a glance
Use this to match terms to the account in front of you.
| Terms | Best for | The trade-off |
|---|---|---|
| Net 30 | Default terms, newer or higher-risk accounts, smaller invoices | Protects cash, but larger buyers may push back |
| Net 60 | Established mid-market accounts, common B2B norm | Widely accepted, ties up about two months of cash |
| Net 90 | Large or strategic buyers with negotiating leverage | Wins and keeps big accounts, heaviest working-capital cost |
| 2/10 Net 30 | Accounts you want to pay early | A 2% discount for payment within 10 days, at a real cost to margin |
How do you choose the right terms for a customer?
Start with three inputs: how the customer pays, how risky they are, and how much cash you can afford to have outstanding. A customer with a clean payment history and a strong credit profile can carry longer terms safely. A newer account, or one showing late payments and disputes, should start on shorter terms and earn longer ones. The mistake is setting terms by the size of the deal alone, because a large customer on Net 90 who pays 20 days late is financing their business with your cash.
What does each extra day of terms cost you?
Every day of terms is a day your cash is unavailable. Terms feed directly into DSO, the average number of days it takes to get paid, and DSO is working capital you cannot spend. On $100M in revenue, shaving DSO frees millions that used to sit in unpaid invoices. That is why terms are a finance decision and not only a sales one. For the levers that bring the number down, see how to reduce DSO.
Should you offer early-payment discounts?
Sometimes. A discount like 2/10 Net 30 gives the customer 2% off for paying within 10 days, which can pull cash forward on accounts where speed matters more than margin. The math has to work: a 2% discount to get paid 20 days sooner is expensive if you did not need the cash that fast. Offer it deliberately, on the accounts where early cash is worth the margin, rather than as a blanket policy.
How do you set terms by risk instead of by what sales wants?
By putting the payment behavior and the credit risk in front of the decision. When you can see how a customer pays you and how the bureaus rate them, terms stop being a negotiation and become a number you can defend. That means shorter terms for shaky accounts, longer terms for reliable ones, and a documented reason either way. Setting a limit alongside the terms keeps total exposure in check, which is covered in how to set customer credit limits.
How does Monk help set data-backed terms?
Monk combines the first-party payment behavior it sees from collections with third-party bureau signals into a single credit score, then suggests terms with the evidence behind them. Because the score updates continuously, an account that starts slipping triggers a review before the next renewal rather than after a write-off. Teams on Monk reduce DSO by 40% or more, and more than $2B in receivables runs on Monk today, including for Profound and ElevenLabs. See how the score is built in credit intelligence.
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