Your SaaS Data Is a Product You Are Not Selling Yet

TL;DR

What: A vehicle activity score derived from GPS tracking data, sold to microfinance lenders as a risk signal. Why: Lenders who finance vehicles need to know if the borrower is actually using them. No usage means no income means no repayment. How: Score based on days active, distance driven, and drive time. Packaged as intelligence for a buyer I never originally targeted.

The Business I Built

I run a GPS tracking SaaS called Traxelio. The business model is straightforward. Sell GPS tracker hardware. Charge a monthly subscription for the tracking platform. Customers are fleet managers, car rental companies, and individual vehicle owners in Senegal and West Africa.

It works. Hardware margins are decent. Recurring revenue from subscriptions keeps things predictable. The whole product is built around one thing: knowing where a vehicle is and what it is doing.

For two years, that was the entire business. Sell the device, provide the platform, collect the subscription.

The Data I Was Sitting On

Every GPS tracker reports back multiple times per day. Location, speed, ignition status, distance traveled. Multiply that by hundreds of vehicles and months of history, and you get a dense dataset of vehicle activity.

I was using this data to show customers their fleet on a map. Trip history, live location, basic reports. Standard GPS tracking features.

But I was only thinking about the data from one angle: what does the vehicle owner want to see? I never asked a different question. Who else would pay for this data?

A Different Buyer With a Different Problem

Microfinance institutions and fintechs in West Africa have a specific product: vehicle financing. They lend money to buy taxis, delivery motorcycles, commercial trucks. The borrower repays from the income the vehicle generates.

Their biggest risk is not default in the traditional sense. It is the borrower stopping to use the vehicle. A taxi that sits idle for two weeks is not generating fares. A delivery bike parked in a compound is not earning. When the vehicle stops moving, the borrower's ability to repay collapses.

Lenders know this intuitively. But they have no way to measure it. They rely on field agents, phone calls, and guesswork. By the time they realize a vehicle is idle, the borrower is already three payments behind.

GPS activity data changes that equation entirely.

Building the Vehicle Activity Score

I needed to turn raw GPS data into something a lender can act on. Not a dashboard full of maps and trip logs. A single number that answers one question: is this vehicle being used?

The vehicle activity score runs daily. It looks at three metrics over a rolling window:

Days active (40 points): How many of the last N days did this vehicle move at all? This is the strongest signal. A vehicle that moved 6 out of 7 days is healthy. A vehicle that moved 1 out of 7 is a problem.

Distance driven (30 points): Total kilometers covered. A taxi doing 80km a day is working. A taxi doing 5km a day is barely leaving the neighborhood.

Drive time (30 points): Hours of actual driving. This catches vehicles that move short distances but spend real time on the road, like delivery bikes in dense urban traffic.

The three components add up to a score out of 100. The thresholds are simple:

• 70 and above: Healthy. Vehicle is active and generating income. No action needed.
• 30 to 69: Warning. Activity is declining. Lender should reach out to the borrower.
• Below 30: Critical risk. Vehicle is barely moving. This loan is in danger.

A lender does not need to understand GPS data. They need to see a number, a color, and a recommendation. Green means fine. Yellow means call the borrower. Red means act now.

From Score to Outbound

Once I had the score built, I needed to find the buyers. I mapped out the microfinance landscape in Senegal and the broader West African region. The result was a prospect list of 21 companies across four tiers.

Tier 1: Large microfinance institutions with existing vehicle loan portfolios. These are the ones already lending for vehicles and actively looking for risk tools.

Tier 2: Fintechs building digital lending products. They move fast and understand data-driven risk scoring.

Tier 3: Smaller microfinance institutions growing their vehicle portfolios. They feel the pain but may not have the budget yet.

Tier 4: Adjacent players. Leasing companies, fleet financing arms of banks. Longer sales cycle but higher contract value.

I wrote a 5-email outbound sequence targeting these institutions. The pitch is not "buy our GPS trackers." Lenders do not want hardware. The pitch is "we can tell you which of your financed vehicles stopped moving before the borrower misses a payment."

That is a fundamentally different value proposition. I am not selling a device. I am selling a risk signal.

The Insight Worth More Than the Feature

Here is what I keep coming back to. I did not build a new product. I did not write a new codebase. I did not hire a data science team. The data was already there. The infrastructure to collect it was already running. The only new thing was the score calculation and the realization that someone else would pay for it.

Most SaaS founders think about their data from the perspective of their current customer. That makes sense. You built the product for them. But your data often describes something bigger than what your customer cares about.

A GPS tracking customer wants to see where their vehicles are. A lender wants to know if a financed vehicle is generating income. Same data, completely different question, completely different willingness to pay.

Finding Your Hidden Buyer

If you run a SaaS that collects behavioral or activity data, ask yourself three questions:

1. Who else has a problem that my data describes? Not my current customer. Someone in a different industry with a different pain point.

2. Can I reduce my data to a simple signal they can act on? Not a dashboard. Not an API with raw data. A score, a flag, an alert. Something a non-technical buyer understands in seconds.

3. What is the cost of them not having this signal? If the answer is "they lose money" or "they take on invisible risk," you have a product.

For me, the answer was microfinance lenders. For your SaaS, it might be insurers, compliance teams, supply chain managers, or investors. The data you already collect could be the product someone else has been looking for.

You do not always need to build something new. Sometimes you just need to look at what you have and ask who else would pay for it.