I’m testing whether transparent cost calculators help users make better car decisions
I’ve been thinking about a product question lately that seems simple on the surface, but gets complicated pretty quickly:
When users are making an expensive decision, do they want a quick answer — or a model they can actually inspect and adjust?
I started looking at this through car buying.
A lot of comparisons online focus on the easiest number to understand:
- purchase price
- fuel savings
- monthly payment
- “EVs are cheaper to run”
- “petrol cars are cheaper upfront”
But those usually aren’t the numbers that actually decide the outcome.
If someone is comparing an EV vs a petrol car, the real answer depends on a bigger set of variables:
- upfront price
- fuel or electricity costs
- insurance
- maintenance
- resale value
- where they live
- how much they drive
That got me interested in a broader product question:
Do users trust a calculator more when the assumptions are visible and editable, or do they actually prefer a simpler black-box answer?
To explore that, I built a small project around the idea:
https://www.carcostiq.com/
It’s currently focused on Australia, and the goal is to compare EV, petrol, and hybrid vehicles using a 5-year total cost of ownership view instead of a single headline number.
What I’m really testing isn’t just the math — it’s the presentation.
Right now I’m experimenting with a few things:
- showing assumptions openly instead of hiding them
- letting users adjust inputs like region, annual km, electricity price, fuel price, and charging mix
- treating the result less like “advice” and more like a transparent model users can reason with
My hypothesis is that transparency can increase trust, especially for decisions where people are naturally skeptical of oversimplified claims.
But I can also see the opposite case:
more transparency usually means more complexity, and more complexity can make people bounce before they get value.
So I’m trying to understand where that balance actually is.
If you’ve built calculators, estimators, or any kind of decision-support product, I’d love your take on two things:
- Do visible assumptions actually improve trust, or mostly add friction?
- How do you decide what to expose and what to simplify?
Still early, and I’m treating this as a learning exercise as much as a product experiment.
Would love any thoughts.
