Tiny Data That Changed the Game

We didn’t call it “data-driven decision-making” back then. But in 1999, when I added just one new data point to my retail setup, everything changed.

When my wife and I opened our first clothing store in Kringlan Shopping Center, we made a small but bold investment: a simple camera-based people counter mounted above the entrance.

The counter was “dumb” by today’s standards. It didn’t know who people were, where they came from, or what they wanted.
It just counted how many people walked in and how many walked out.

That’s it.
No fancy dashboards. No real-time alerts. Just a rolling number on a screen.

But here’s the thing:
That one single dataset, the number of visitors per day, completely changed how we understood and ran the business.

We already had a sales system. We knew:

• Total revenue per day
  

• Items sold
  

• Average basket size
  

• Which products were moving
  

But without knowing how many people came in, we were working blind.

Once we had the visitor count, new KPIs emerged that hadn’t been visible before:

Conversion Rate

How many visitors actually bought something?
Suddenly we could separate “busy” days from “successful” ones.

Average Spend per Visitor

Not per customer, but per person who walked in.
This helped us understand how much value each footfall brought in, regardless of how     many items they purchased.

Bounce Rate (real-world edition)

How many people left without buying?
A real measure of opportunity lost.

Staffing Effectiveness

We began correlating visitor data with sales and staffing schedules:

Were we overstaffed during quiet hours?
Were we missing sales during peak walk-ins?
Was conversion rate consistent across weekdays?

Campaign Impact

We finally had a way to measure the true effectiveness of promotions:

Did the newspaper ad increase foot traffic or just boost basket size?  (Yes, we advertised in newspapers back in the day.)
Were our windows drawing people in, or just catching glances?

At the time, these weren’t standard KPIs, especially not for small businesses.
But by layering this tiny dataset on top of what we already had, we created a decision-making model that was years ahead of its time.

No clouds.
No AI.
No real-time dashboards.

Just a camera, a spreadsheet, and the willingness to ask better questions.

The bigger lesson

Today at Greind, I work with far more complex systems: Cloud data warehouses, real-time data ingestion, predictive models. But this simple story still shapes how I think about data.

You don’t always need more data. You need the right data. And most importantly, tiny data, when well-integrated, can have a massive impact. 

These days, businesses are surrounded by data: finance systems, CRMs, point-of-sale platforms, marketing dashboards. The information is there, but too often it lives in silos, disconnected and underused.

Back in 1999, that simple visitor counter in our NOA NOA store didn’t just add a new metric.
It changed how all the other data made sense.

It reminded me that sometimes, the right piece of data doesn’t speak the loudest.  It brings the whole picture into focus.