Payment Terms Optimization

Payment Terms Optimization

Overview

Payment terms define when a B2B customer must pay for goods delivered on credit: net-30 (due 30 days after invoice), net-60, net-90, or early-payment variants like "2/10 net-30" (2% discount if paid within 10 days). Offering flexible payment terms is a competitive advantage in B2B commerce — it reduces friction in the purchase decision — but introduces credit risk that must be carefully managed.

The right tools depend on your platform. Shopify Plus, BigCommerce B2B Edition, and several WooCommerce plugins provide native net-terms support. For smaller setups, a combination of your ecommerce platform and an invoicing tool (Invoiced, Stripe Invoicing) is the most practical approach.

When to Use This Skill

• When moving from prepay-only to net-terms for B2B customers to increase conversion
• When different customer segments need different terms (SMB net-30 vs. enterprise net-60)
• When you want to incentivize early payment with discounts to improve cash flow
• When setting up a new wholesale or distribution channel with trade accounts
• When credit losses are rising and you need better credit limit enforcement

Core Instructions

Step 1: Determine your platform and choose the right payment terms tool

Step 2: Configure payment terms per customer

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Shopify Plus (B2B native)

1. Go to Shopify Admin → Customers → Companies and create a company profile for each B2B account 2. Click a company and go to Payment methods — set their payment terms:

• Net 7, Net 15, Net 30, Net 60, Net 90
• or a custom number of days

3. Set a Credit limit on the company — orders that would exceed the limit are blocked or sent for approval 4. When a company buyer places an order, Shopify automatically creates an invoice with the correct due date and sends it to the buyer's email 5. The buyer can pay via a link in the invoice email; Shopify marks the order as paid automatically

Early payment discounts on Shopify Plus: Shopify B2B does not natively support "2/10 net-30" early payment discounts. Use Invoiced app for early payment discount terms — configure in Invoiced → Settings → Payment Terms → Early Payment Discount.

Shopify (Standard, via Invoiced app)

1. Install Invoiced from the Shopify App Store 2. Go to Invoiced → Settings → Payment Terms and create your term configurations: Net 30, Net 60, Net 90, 2/10 Net 30 3. In Invoiced → Customers, assign payment terms per customer 4. When a Shopify order is placed by a net-terms customer, Invoiced automatically generates an invoice with the correct due date 5. Configure dunning: go to Invoiced → Settings → Chasing and set up a reminder schedule (1 day before due, 1 day overdue, 7 days overdue, 14 days overdue)

WooCommerce

1. Install WooCommerce B2B plugin (by WooCommerce or a third-party B2B plugin) 2. Go to WooCommerce → B2B Settings → Payment Terms and configure terms per customer role or per customer 3. Install WooCommerce PDF Invoices & Packing Slips to automatically generate invoices with due dates 4. For early payment discounts, you can use a custom pricing rule (WooCommerce Dynamic Pricing plugin) that applies a percentage discount when a coupon code representing the early payment option is used

Credit limit enforcement in WooCommerce: 1. In the B2B plugin settings, set credit limits per customer or customer group 2. Configure the behavior when the limit is exceeded: block the order or notify an admin for approval 3. Credit is automatically released when an invoice is paid

BigCommerce B2B Edition

1. In B2B Edition → Company Management → Payment Methods, enable net-terms 2. In B2B Edition → Companies → [Company] → Credit, set:

• Credit limit
• Payment terms (Net 30, Net 60, etc.)
• Credit status (Approved, Pending, Suspended)

3. When a company buyer places an order, BigCommerce B2B Edition generates an invoice with the configured terms 4. The buyer can view and pay outstanding invoices from their account portal

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Custom / Headless

Use Stripe Invoicing for net-terms enforcement without building a credit system from scratch:

// Create a customer with payment terms in Stripe
const customer = await stripe.customers.create({
  email: customerEmail,
  name: companyName,
  metadata: { payment_terms: 'net_30', credit_limit: '50000' },
});

// Create an invoice with net-30 terms
const invoice = await stripe.invoices.create({
  customer: customer.id,
  collection_method: 'send_invoice',
  days_until_due: 30,            // Net-30
  auto_advance: true,            // Automatically finalize and send
  description: `Invoice for Order ${orderNumber}`,
  metadata: { order_id: orderId, po_number: poNumber },
});

// Add line items, then finalize and send
await stripe.invoiceItems.create({ customer: customer.id, invoice: invoice.id, amount: orderTotal, currency: 'usd', description: orderDescription });
await stripe.invoices.finalizeInvoice(invoice.id);
// Stripe auto-sends the invoice and handles dunning reminders via Billing settings

Configure dunning in Stripe Billing settings: Go to Stripe Dashboard → Billing → Settings → Invoice reminders and configure automatic reminders: 3 days before due, on due date, 3 days after, 7 days after, 14 days after.

Credit limit enforcement (custom):

async function checkCreditAvailability(customerId, orderAmount) {
  const customer = await db.customers.findUnique({ where: { id: customerId } });
  const openInvoicesTotal = await db.invoices.aggregate({
    where: { customerId, status: { in: ['sent', 'overdue', 'partially_paid'] } },
    _sum: { amountDue: true },
  });

  const currentBalance = openInvoicesTotal._sum.amountDue ?? 0;
  const availableCredit = customer.creditLimit - currentBalance;

  if (orderAmount > availableCredit) {
    return { approved: false, availableCredit, shortfall: orderAmount - availableCredit };
  }
  return { approved: true, availableCredit: availableCredit - orderAmount };
}

Step 3: Optimize terms for cash flow and credit risk

The right terms for each customer tier:

Early payment discount economics: "2/10 net-30" means the customer gets a 2% discount if they pay within 10 days instead of 30. For the customer, this is equivalent to borrowing at ~36.7% APR — most customers with any cost of capital should take the discount. For you, paying 2% to receive payment 20 days earlier is typically better than your borrowing cost.

Annual credit review: Review every credit account annually — set a calendar reminder. A customer who qualified for $50,000 credit 2 years ago may look very different today. Reduce limits for customers who have developed slow-pay patterns.

Best Practices

• Start new B2B customers on stricter terms — onboard new accounts at net-30 or net-15 and upgrade after 6 months of on-time payment; never start with net-60 or net-90 without a credit check
• Never ship to accounts on credit hold — enforce credit holds at the order level, not just the invoicing level; once goods leave the warehouse you have lost leverage
• Price early payment discounts correctly — "2/10 net-30" implies an annualized cost of ~36.7% to the customer; communicate this value clearly
• Segment collections intensity by risk tier — high-risk customers need follow-up on day 3 overdue; long-term accounts with a perfect history deserve more grace
• Document every credit decision — store the reason for every credit limit change; you will need this if you ever need to defend a write-off to auditors

Common Pitfalls

Related Skills

• @accounts-receivable-automation
• @invoice-generation-automation
• @payment-reconciliation-automation
• @stripe-integration

B2B Order Credit Gate

Problem/Feature Description

TradeCo Supplies is a wholesale distributor that has just moved from prepay-only to offering net payment terms for its B2B customers. Before this change, every order required upfront payment, so there was no credit risk. Now, approved customers can place orders and pay later — but the engineering team needs to make sure the business doesn't overextend credit.

The head of finance has flagged three recurring problems from the pilot rollout: orders are occasionally being accepted for customers whose accounts have been put on hold due to disputes; some customers with "pending" applications are placing orders before their credit has been approved; and a handful of large orders have been processed that push customers well past their authorized credit ceiling. The root cause is that the current checkout service only checks credit after invoicing, not at order placement — meaning the warehouse ships the goods before the system catches the problem.

Your task is to implement a checkCreditAvailability function and a releaseReservedCredit function for the order service. The functions should handle all the edge cases the finance team identified, and when credit is approved, the system must update the customer's credit state immediately at order creation time (not after invoicing) so that a second simultaneous order cannot exceed the same limit. Also implement a releaseReservedCredit function for when orders are cancelled before confirmation.

Write the implementation as a JavaScript module (credit-check.js) along with a test file (credit-check.test.js) that demonstrates each decision path using in-memory mock data. The test file should print results to stdout so the outcomes are visible.

Output Specification

• credit-check.js — The credit check module with checkCreditAvailability and releaseReservedCredit functions
• credit-check.test.js — A runnable test/demo script (no test framework required, plain Node.js) that exercises all decision paths and prints the results
• results.txt — Run node credit-check.test.js > results.txt 2>&1 and save the output

The test script must be runnable with node credit-check.test.js without any npm install (use no external dependencies).

Early Payment Discount Engine

Problem/Feature Description

FinFlow Wholesale offers several payment terms with early payment discount (EPD) options — for example, a customer on "2/10 net-30" terms can deduct 2% from their invoice if they pay within 10 days, otherwise the full amount is due in 30 days. The CFO wants two things from the engineering team.

First, the accounts receivable team is processing payments manually and keeps accepting discounts from customers who pay after the discount window has closed. The team needs a function that, given an invoice and a proposed payment date, calculates whether a discount applies and what the customer actually owes — so the AR clerk can stop making judgment calls.

Second, the CFO has been trying to convince the sales team that offering 2/10 net-30 is actually very expensive financing for customers who don't take the discount. She wants a utility function that, for any discount-bearing payment terms code, computes the annualized cost of the credit so she can use it in conversations with customers and in the company's pricing model. She suspects that most customers with a reasonable cost of capital should be taking the discount — they're essentially borrowing at an extremely high implied rate if they don't.

Implement both utilities as a single JavaScript module (early-payment.js). Also write a demo script (demo.js) that shows the discount calculation for a few sample invoices and prints the annualized cost for all discount-bearing terms in the system. Run the demo and save the output.

Output Specification

• early-payment.js — Module with calculateEarlyPaymentDiscount(invoice, paymentDate) and computeImpliedCostOfCredit(termsCode) functions, plus the PAYMENT_TERMS configuration object
• demo.js — Runnable Node.js script (no external dependencies) that exercises both functions and prints results to stdout
• results.txt — Output of running node demo.js, saved to file

The PAYMENT_TERMS configuration should cover at minimum the standard discount-bearing terms. The demo should include at least one case where the discount applies, one where it does not (payment too late), and compute the implied cost for at least two different discount terms.

Automated Credit Scoring and Collections Escalation

Problem/Feature Description

Meridian Distribution has been extending net payment terms to B2B customers for two years. The credit manager currently reviews all accounts manually — a process that doesn't scale as the customer base has grown to several hundred accounts. Two problems have emerged: the team treats every overdue account the same way regardless of the customer's track record (sending aggressive collection emails to 20-year accounts that are 4 days late), and new accounts are being given overly generous terms because the sales reps are making judgment calls without a consistent methodology.

The engineering team has been asked to build two things: (1) an automated credit scoring function that analyzes a customer's 12-month payment history and outputs a risk score, risk tier, and recommended payment terms and credit limit multiplier, and (2) a collections escalation engine that, given a customer's risk tier and the number of days an invoice is overdue, determines what action should be taken next.

Implement these as a JavaScript module (credit-risk.js). The module should export a scoreCustomerCredit(customerId, paymentHistoryRecords) function that takes in payment history data directly (no database calls — accept the records as a parameter) and returns the scoring result. Also export a getNextCollectionsAction(riskTier, daysOverdue, actionsTaken) function that returns the next action to take given the overdue days and what has already been done, or null if no further action is warranted yet.

Write a demo/test script (demo.js) that runs several representative scenarios through both functions and prints the outcomes. Save the output to results.txt.

Output Specification

• credit-risk.js — Module exporting scoreCustomerCredit and getNextCollectionsAction
• demo.js — Runnable Node.js script (no external dependencies) covering multiple customer risk profiles and overdue scenarios
• results.txt — Output of node demo.js, saved to file

The demo should cover: a new customer with no history, a customer with excellent payment history, a customer with poor history, and collections escalation examples for all three risk tiers at various days-overdue values.