SaaS Metering Infrastructure Build vs Buy: Is it your financial system of record?

Foundational Understanding: What is Metering Infrastructure?

For many SaaS startups, implementing usage-based pricing is a logical step to align revenue with customer value. The core technical task, how to track usage for SaaS pricing, can seem straightforward at first. You count events, store them, and generate a bill. However, this apparent simplicity masks a complex reality that consumes engineering resources, creates customer friction, and complicates financial reporting.

The critical question quickly evolves from a technical exercise to a strategic one. Is building and maintaining your own metering infrastructure the right use of your company’s limited time and capital, or is it a costly distraction from your core mission? For early-stage companies in the UK and USA, where runway is everything, making the right choice on the build vs buy decision from the start can significantly impact growth and operational efficiency.

One of the first misconceptions to address is that metering is just about counting things. While counting is a component, a true metering infrastructure is a complete data pipeline engineered for accuracy, auditability, and integration. It’s the difference between a simple counter and a financial system of record for your revenue. A robust pipeline involves several distinct stages, each with its own set of challenges.

• Ingestion: This first stage focuses on reliably collecting raw usage events from your applications without data loss. It requires a resilient system capable of handling spikes in traffic, network interruptions, and ensuring every event is captured accurately.
• Aggregation and Transformation: Raw events are rarely billable on their own. This stage processes them into meaningful metrics that align with your pricing model, such as aggregating API calls into a monthly total or transforming data logs into gigabytes processed.
• Enrichment: Here, crucial business context is added to the aggregated data. This involves linking usage to the correct customer account, subscription plan, and contract terms, which is essential for accurate billing.
• Access and Integration: Finally, the clean, enriched data must be accessible to other business systems. This is the most critical stage for operations, enabling automated Stripe billing, simplifying reporting in accounting tools like QuickBooks or Xero, and feeding data into analytics platforms.

Without every stage working correctly, you are not just counting events. You are creating future problems for your engineering, finance, and customer success teams.

The "Build" Path: The Hidden Iceberg of In-House Metering

The appeal of creating custom metering solutions is understandable. It promises full control over your data and avoids another subscription fee. However, the initial build is merely the tip of a very large and expensive iceberg. The real cost of building metering is not in the first version but in the relentless, long-term maintenance, where opportunity costs truly accumulate.

The True Cost of Building Metering: Beyond the Initial Code

The reality for most startups is that engineering resources are finite and best spent on the core product that customers pay for. When your engineers are debugging a metering discrepancy, they are not building your next competitive feature. Ongoing maintenance includes handling schema migrations as your product evolves, performing complex backfills when pricing plans change, investigating billing disputes, and scaling the entire infrastructure as your customer base and usage volume grow.

A scenario we repeatedly see is a Series A company that built an in-house meter. When a bug was discovered that had been miscalculating usage for six months, the engineering team spent three weeks pausing all feature work to investigate logs, write custom backfill scripts, and manually correct hundreds of invoices. Research from OpenView confirms the scale of this commitment, noting that “Engineering costs for in-house metering systems can reach $500k-$1M over 2-3 years.” This long tail of hidden work becomes a significant and unpredictable drain on resources.

The Endless Cycle of Maintenance and Backfills

A homegrown metering system is never truly "done." As your business evolves, so must your meter. Each new pricing plan, feature, or discount introduces complexity that your system must handle flawlessly. If you decide to change a metric from being billed at the end of the month to being billed in real-time, it often requires a substantial re-architecture. When errors inevitably occur, the process of correcting historical data, known as backfilling, can be a major engineering project that halts product momentum and frustrates your team.

The Perils of "Good Enough" Data

Many in-house systems start as “good enough” solutions. They seem to work, and the occasional error is handled manually. But the risk here isn't a single catastrophic failure; it's the slow erosion of trust and operational efficiency. When a customer in the US or UK questions their bill, your ability to provide a clear, auditable log of their usage is paramount. If you cannot, you lose credibility.

Direct Revenue Leakage and Customer Churn

This friction inevitably leads to concessions, discounts, and churn. The financial impact is significant. A 2022 survey by Wakefield Research for Stripe found that “78% of SaaS businesses are forced to make concessions on billing disputes due to unreliable data.” This is direct revenue leakage caused by an internal system’s inability to produce trustworthy data. Every time your team issues a credit because they cannot prove usage, you are paying the price for an inadequate system.

Operational Drag and Impaired Decision-Making

For a founder without a dedicated finance team, this pain extends deep into operations. The inability to get clean data makes financial planning impossible. You cannot produce accurate forecasts or reliable investor metrics if the underlying usage data is constantly being questioned or manually adjusted in a spreadsheet before being entered into QuickBooks or Xero. In the UK, HMRC requires VAT records to be kept for six years, a requirement that becomes stressful with unreliable data. For US companies, this introduces major complications for revenue recognition under US GAAP. It creates a bottleneck that hampers strategic decisions and introduces friction during due diligence.

The "Buy" Path: A Strategic Trade-Off for Speed and Focus

Opting for third-party metering software is not an admission of technical inability; it is a strategic trade-off that prioritizes speed, focus, and reliability. By buying a dedicated solution, you are trading a direct and predictable subscription cost for the unpredictable and often far larger indirect costs of an in-house build. This is a classic business decision about core competency.

Accelerate Your Pricing Model Implementation

The primary advantage is speed. Implementing a usage-based pricing model can be accomplished in weeks, not the months or quarters required for a custom build. This allows you to iterate on your pricing model implementation faster to find what works best for your market. While a competitor is debugging their custom data pipeline, you can be testing new pricing tiers and gathering market feedback.

Sharpen Your Team’s Focus on Core Value

The second major gain is focus. Your engineering team is freed to concentrate entirely on your core product, which is the engine of your company’s growth. Instead of becoming experts in data plumbing, they can build features that differentiate you from the competition. This allows you to allocate your most valuable resource, engineering time, to activities that directly increase the value of your product for customers.

Achieve Finance-Grade Data from Day One

Finally, these commercial usage tracking tools are built specifically to produce auditable, finance-grade data out of the box. They are designed to integrate cleanly with billing platforms and other systems, solving the data trust problem from day one. This provides your finance team with reliable numbers for reporting and forecasting and removes the operational drag on your entire organization.

A Simple Decision Framework for Your Stage

Deciding between building custom metering solutions and buying third-party software depends heavily on your startup’s current stage and complexity. The right answer changes as you grow.

• Pre-Seed / Early MVP Stage: Your primary goal is validating a core idea. If your pricing is extremely simple, like a single per-seat metric, a basic internal counter in your main database might suffice. The risk is low, but you should view it as a temporary solution that will need to be replaced. Building something complex now is a premature optimization.
• Seed / Product-Market Fit Stage: At this point, you are scaling your customer base and need flexibility to experiment with more sophisticated pricing. If you plan to bill on multiple usage vectors, the complexity of building in-house rises dramatically. This is the natural inflection point where the "buy" decision often provides a clear ROI by enabling faster pricing iteration and freeing up engineering resources for product development.
• Series A/B Stage: You have significant revenue, a growing team, and investors who require reliable metrics like net revenue retention and consumption forecasts. Auditable data is no longer optional. Building a robust metering system now would be a major undertaking, diverting a senior engineering team from the core roadmap for an extended period. The strategic priority is growth and expansion, making a reliable, off-the-shelf solution the pragmatic choice.

Practical Takeaways

The decision to build or buy metering infrastructure is more about strategy than technology. It hinges on how you value your team's time and where you choose to focus your resources. To make the right choice, consider the following steps.

1. Reframe the question. It is not “Can our engineers build this?” but rather “Should they?” The distinction is critical. Your team is talented enough to build many things, but their time is best spent on the product that delivers unique value to your customers.
2. Audit your current system honestly. If you have a homegrown solution, audit it honestly. How long does it take to resolve a customer billing query? Can you provide an auditable usage log on demand? If the answer involves hours of engineering time or manually combing through logs, your “good enough” system is already costing you.
3. Calculate the Total Cost of Ownership (TCO). Factor in not just the initial build, but the ongoing salary cost for maintenance, the opportunity cost of delayed features, and the revenue lost to billing concessions. Compare this figure to the transparent subscription cost of a dedicated tool. For guidance on COGS calculation and authoritative guidance on revenue recognition for usage-based models, consult with your finance advisors.
4. Recognize metering as a business enabler. Finally, recognise that a robust metering system is an enabler for the entire business. It provides product teams with real-time usage analytics, gives finance the data for accurate forecasting, and gives leadership the confidence to make strategic decisions. It is not just a technical component; it is foundational infrastructure for growth.

Frequently Asked Questions

Q: Can't we just use our data warehouse, like Snowflake or BigQuery, for metering?

A: While data warehouses are excellent for analytics, they are not designed for billing. They typically lack the real-time processing, idempotency controls, and auditability required for a financial system of record. Using a data warehouse for billing often leads to a separate, complex ETL pipeline that re-creates the same challenges as a fully custom solution.

Q: What are the first signs that our homegrown metering system is failing?

A: The early warning signs include an increase in support tickets related to billing questions, your finance team spending days manually reconciling invoices, and engineers being pulled away from product work to investigate usage discrepancies. Another key sign is a reluctance from your sales team to sell complex usage-based deals because they don't trust the system.

Q: We are a small startup; aren't third-party usage tracking tools too expensive?

A: When evaluating cost, it is crucial to compare the subscription fee of a tool against the total cost of building and maintaining a system in-house. This includes the fully-loaded salary of the engineers involved, the opportunity cost of features not built, and the revenue lost from billing errors. Often, a third-party solution is significantly more cost-effective.