A company’s true profitability can hide in the details. The real story often lies beneath the surface of traditional financial statements.

Profitability is a principal indicator of the health of a business, but relying solely on your P&L statement to tell your profitability story may not reveal the full picture of what’s affecting margins. Unit economics is a way of determining the revenues a business generates from a single customer, product, or location relative to the costs it incurs to acquire and retain that customer.

We’ve helped many of LLR’s portfolio companies unearth important insights into their profitability by applying unit economics. Here’s a look at why and how we break down revenue and cost by customer, product, and/or business model to better attribute margin detractors and enhancers, which is essential in understanding how to calculate unit economics.

Gross margins don’t always tell the full story.

For many companies, assessing overall gross margin – a key metric many used as a proxy for the profitability of the business – only reveals the tip of the iceberg. While it is a useful, consolidated figure, overall margin often doesn’t provide the granular insights necessary for strategic decision-making.

Consider a company whose overall margin is healthy. Applying unit economics through customer-level margin analysis reveals that a small subset of customers generates most of the revenue, another subset is driving a large portion of cost, and yet another has a negative margin.

This type of analysis allows for targeted, strategic action, such as identifying ways to reduce burdensome cost buckets, electing not to service a subset of unprofitable customers, or re-targeting growth strategies toward more profitable customer segments.

Customer-level profitability can help businesses boost revenues, improve renewal strategies, reduce costs, and more.

With a customer-level profitability analysis, businesses can:

  • Refine financial forecasting by correlating profitability with customer growth expectations.
  • Reduce costs by identifying manual or resource-intensive activities ripe for automation or self-service.
  • Improve resource allocation by identifying the customers (or segments) with greater margin contributions.
  • Improve renewal strategies by identifying upsell opportunities or embedding new SLAs into customer agreements.
  • Gain a better view into the ROI of technical support, customer success, and other functions in Cost of Goods Sold.
  • Help boost revenues by uncovering, and revising, agreements for customers whose pricing has never increased or who consistently benefit from legacy discounts.

3 first steps toward customer-level profitability tracking.

The challenge with unit profitability profitability can lie in bringing complex, high-volume datasets together. Here is where you can start laying the groundwork for better data hygiene and more sound profitability analysis:

1. Track direct and indirect COGS.

Where feasible, track the direct cost of goods sold (COGS) at the customer level. This can include tracking third-party software licenses, hardware costs, payment processing fees, and the costs of the hosting infrastructure or system capacity required to service a given customer.

Indirect COGS often includes functions like customer implementation, service and success, which can be measured by implementing time-tracking that monitors time spent supporting each customer. Since customer support costs can be difficult to attribute, begin by tracking support case volumes1 and consider implementing a method to quantify the complexity of support tickets. For example, if one is open for five minutes, but another is resolved after five days, how does that reflect a greater cost burden? This can eventually support allocation of support team costs at the customer level.

Commitment to data consistency should come from your C-suite and cascade down to the teams who will prioritize investment in proper data integrity.

2. Ensure data consistency.

If your reporting lacks a consistent identifier across datasets, it is challenging to attribute revenue and cost consistently by customer, product, or at another unit level across separate reports. Reinforcing data consistency in customer naming conventions – for example, with one unique customer, product name or ID that is replicated across all reporting – can facilitate much easier matching for a clear picture of by-unit revenue and cost allocation.

This commitment to data consistency2 should come from the top—your C-suite—and cascade down to the teams (often finance and operations leaders) who will prioritize investment in proper data integrity.

3. Determine an allocation methodology.

You’ve set the intention to conduct a customer-level margin and profitability analysis. Your data and reporting are clean and ready. Now, align on an allocation methodology that attributes revenue and cost across customers or products in a way that makes sense for your business and margin targets. For example, COGS for software services may include customer set-up, third-party data fees, and customer support services.

There is no “one size fits all” approach to revenue and cost allocation. Margin detractors come in all forms.

Determining these costs per customer could involve proxy calculations, third-party invoices, and tracking time against support tickets to build a bottom-up view of a customer’s overall cost and therefore “burden” on the business. This methodology may not always return a clearly attributable cost metric. In some cases, allocation will be based on pure customer usage, such as the number of SaaS licenses a customer has purchased, devices they are using, or other measures of their utilization of your platform.

During this exercise, you are likely to discover that there is no “one size fits all” approach to revenue and cost allocation and that margin detractors come in all forms. You may find that a given product is completely unprofitable within a customer segment, perhaps as a result of higher system usage, or that some customers are well below the annual revenue target. These findings inevitably inform actionable steps towards strategic improvement of margins and overall profitability. Below is an example of potential customer-level margin detractors.

examples of customer-level margin detractors when calculating unit economics

Transform unit-level insights into strategic decisions.

To glean insights and recommend actions from a customer-level analysis, tailor the approach to your business model and unique margin target(s). Capturing the nuances about your business, customers and products are essential to informing next steps.

The key to actioning these margin and profitability insights is to identify a core decision and review it from all possible angles.

Once a potential course of action is revealed, drill down into the details and implications. For example, you may find that 10% of your customers are underperforming across products in terms of profitability, and it may even make sense to stop servicing them. Ask questions like these to help determine the appropriate course of action:

  • What are the implications of stopping service for these customers on revenue and cost?
  • Will stopping service for these customers affect other customer relationships?
  • Even if we stop servicing these customers, are there some functions (e.g., customer service) that wouldn’t benefit because they are still needed to service the rest of the customer base?

The key to actioning these margin and profitability insights is to identify a core decision and review it from all possible angles and implications.

Giving visibility into customer profitability across teams can help democratize this information to help elevate your sales, implementation, and procurement teams’ decisions.

To further enable strategic decision-making, set up the reporting and analysis in a repeatable way. Given that margin targets, revenue and cost are ever-changing metrics, a model that can be refreshed often and easily to provide ongoing insights can be most helpful to ensuring accretive and timely decision-making.

It’s important for C-suite leaders to give visibility into customer profitability across teams. Democratizing this information can help sales teams understand the impact of how they price new deals, help implementation teams put more rigor around attending to customer requests, and help procurement teams to see the ROI of their vendor selection and negotiations. Visibility into findings across the business can inherently elevate the value of the insights and related actions.

Here’s the bottom line.

A company’s true profitability can hide in the details. The real story often lies beneath the surface of traditional financial statements, which means that without tracking unit economics, you could be leaving margin on the table. By delving into customer-level profitability, companies can unlock hidden revenue potential and make more informed strategic decisions to benefit the overall business.

  1. “Key Metrics for Measuring Customer Support,” HelpDesk, 2022, https://www.helpdesk.com/learn/customer-support-essentials/customer-support-metrics/.

  2. “Data Quality Assurance: The Key to Reliable and Trustworthy Data Engineering,” International Association of Business Analytics Certification, 2023, https://iabac.org/blog/data-quality-assurance-the-key-to-reliable-and-trustworthy-data-engineering