What engineering challenges companies face in building credit-based pricing in-house?

Credit-based pricing is a monetization model where users purchase a set number of credits in advance. These credits act as a universal currency across your product. Instead of pricing each feature individually in tokens, API calls, compute time, or storage, you assign each action a credit cost. As the user interacts with the product, credits are deducted based on what they use.

For example:

• Running a basic contact enrichment might cost 2 credits.

• Performing AI-powered lead scoring could cost 10 credits.

• Sending an automated sequence might cost 5 credits per recipient.

This system allows companies to abstract the internal complexity of infrastructure costs while offering users a predictable, flexible way to consume the product.

It’s particularly useful when:

• Different actions have different backend costs.

• Some workflows are powered by expensive third-party APIs or AI models.

• You want a single pricing model across a diverse product surface.

In theory, credit-based pricing offers the best of both worlds: usage flexibility for customers and cost alignment for companies.

In practice, implementing credit-based pricing model is hard. Let’s take an example of a company that is successfully running credit-based pricing: Clay

Clay is a popular AI-powered lead enrichment and outreach automation tool. Users can purchase a monthly subscription that includes a fixed number of credits.

Every time a user performs an action like enriching a contact, running a scraping workflow, or generating a message using AI, credits are consumed. Example,

• Creating a table of suitable prospects costs 10 credits.

• Enriching a contact costs 1.5 credits per table row.

For implementing credit-based pricing, even before engineering teams writes a single line of code, you need to define a series of foundational frameworks that will shape the entire system.

Let’s break it down.

Define the pricing abstraction

How will the credit system behave at a product level?

• Will credits be tied to usage (per action), outcomes (per result), or time (per second)?

• Are credits fixed per feature, or dynamically priced based on load, latency, or vendor cost?

• Will different customer segments (freemium, pro, enterprise) have different credit mappings for the same actions?

Will credits be the only pricing abstraction?

• Are you bundling credits into subscription tiers?

• Do customers top up credits beyond their plan?

• Are you offering both usage-based and credit-based models simultaneously?

Build a feature-to-credit mapping system

This is where the pricing architecture begins. You need a source of truth that maps product features to credit cost:

This config must support:

• Versioning (you’ll tweak prices over time)

• Per-plan overrides

• Regional differences

• Custom rules for enterprise customers

Design the credit lifecycle

Credits aren’t just counters. You need a full credit accounting model:

This typically results in a ledger system which is ****a table that stores every credit debit, refill, refund, and expiry event with timestamps and metadata. You’ll want this ledger to be immutable, versioned, and eventually auditable.

Decide how to meter usage and trigger credit deductions

This is one of the most complex parts.

You must determine:

• What qualifies as a usage event?

• Where in the system is that usage recorded?

• When is the credit deduction triggered?

Show credit usage to customers

Once the core logic works, you need to build user-facing infrastructure:

• A credit balance component in the UI

• A usage breakdown per feature over time

• Tooltips or inline messages for: “This action will cost 3 credits”

• Real-time feedback on successful or failed actions (and what it cost)

Plan for pricing changes

Every decision above will need to evolve. Here’s what typically changes over time:

You’ll likely need an admin panel to manage pricing overrides, customer-specific credit rules, and to push new mappings without redeploying code for product and growth teams.

Finance, revenue, and support ops

Finally, credit-based pricing creates downstream complexity:

• Revenue recognition must track how credits are sold vs when they’re used

• Refunds must reconcile with ledgers and billing systems

• Support teams need tools to refund, explain deductions, and audit past activity

What does the system architecture look like?

A realistic architecture for credit-based pricing includes multiple moving parts:

Flow Example:

1. Your product service emits a feature_used event → “User 453 triggered AI Enrichment.”

2. The event is pushed to Kafka or Pub/Sub.

3. A Billing Processor listens to usage events, queries pricing rules, and deducts credits from the ledger.

4. The deduction is recorded as an entry: User 453 -6 credits for action_id=1234

5. A notification service sends real-time updates to the UI or audit system.

6. The credit API exposes balance, usage history, and limits.

Engineering headaches you must plan for

1. Concurrency + Deduplication What if a user triggers multiple parallel workflows? You’ll need:

   1. Idempotent operations

   2. Transaction-safe credit deduction

   3. Locking or optimistic concurrency

2. Partial Failures If Step 1 of a workflow succeeds (credits deducted) but Step 2 fails: do you refund credits? Do you retry? Can the refund be abused?

3. Custom Pricing Contracts Enterprise accounts often negotiate:

   1. Flat cost per 1,000 credits

   2. Different credit costs per region

   3. No expiry clauses

You now need dynamic, per-customer overrides layered on top of your default pricing.

The bugs you won’t see until it’s live

These show up in every credit-based billing system eventually:

• User reloads page → action runs twice → double deduction

• Credits deducted, but action fails 30 seconds later → support ticket

• “I bought 10,000 credits but only used 2,000—can I get a refund?”

• "My credits expired yesterday, but I just upgraded today—why can’t I use them?"

• Two teammates used up all credits → who gets blamed?