By Joseph Carboni
What is ROI (Really)?
“Return on Investment” (ROI) is traditionally defined as net profit divided by cost, which is used to measure how well a financial investment pays off. However, in a service or software context, this definition doesn’t hold.
Consultants often use “ROI” interchangeably with Customer Profitability Analysis (CPA)—measuring how much a specific customer relationship brings in versus what it costs to support. Think of it less as pure profit margin, and more as a cost-to-serve ratio. High ROI (or high customer profitability) signals that a relationship is worth maintaining or expanding. Low ROI can identify unprofitable clients or processes in need of improvement.
How to Execute Customer Profitability Analysis
To measure ROI per customer relationship, you need a few key data points:
- Revenue, per client
- Time spent to serve, broken down by employee and client
- Cost of that time, including:
- Wages, taxes, benefits
- Overhead (e.g. office rent, utilities)
The Hard Part: Measuring Time
Time is the trickiest input. Rough estimations are fast but unreliable, while meticulous tracking introduces the Observer Effect, where efforts to measure something too exactly changes the result.
Keep it lightweight. A basic time grid—clients on one axis, time blocks on another—can capture useful patterns without becoming a burden. Don’t overengineer it.
With this in place, you can calculate ROI like this:
ROI = Revenue / (Time Spent * Cost Per Hour)This lets you compare customer relationships on a level playing field.
Measuring Impact
Once you have a baseline ROI, you can track change, which is especially important when introducing new workflows or automations.
When internal tools reduce time spent on low-value tasks, the ROI should increase even if total spend remains unchanged. You’ll see the impact in how time shifts across client relationships: more time going to high-value work, less time sunk on repetitive service.
Unlike traditional financials, this kind of operational ROI lets you observe the real-world effect of process changes, which is especially helpful when evaluating software investments.
My Workflow
Start small, keep it repeatable.
I recommend setting up a Python Jupyter Notebook to process and visualize data. Use libraries like Seaborn to create clear, consistent visuals. Run it monthly or quarterly to see trends over time.
Once the pipeline is built, tracking ROI becomes simple, fast, and actionable.