So, I wanted to learn their wealth-building habits.
Here are 7 ways the Swiss approach money to become richer than you:
Switzerland has the world's largest percentage of millionaires.
AND they have 1 billionaire for every 80,000 people.
What's the Swiss secret – is it all about banking and neutrality?
To start answering this question, here's an interview with some locals:
Before we dive in, here's the low-down:
• 14.9% of Swiss adults are millionaires
• That's nearly double the rate of the US (8.8%)
• Yet Switzerland isn't even in the top 10 for average income
So how do they do it?
It's all about some key mindset shifts – here's a clue:
They Rent for Life (& They Love It)
Shocking fact: Only 41% of Swiss own their homes.
In the US? It's 65%.
Swiss millennials aren't obsessed with buying houses.
Why? They invest the difference in high-yield assets instead. Meanwhile...
They Treat Saving Like a Bill
Most people save what's left after spending. The Swiss? They spend what's left after saving.
They automate 20-30% of their income into savings BEFORE touching it.
It's not about willpower. It's about systems.
But saving alone won't make you rich:
Swiss People Invest in Themselves
The average Swiss spends 5-10% of their income on education and skills.
Every year. They're not chasing degrees. They're after specific, high-value skills.
"Find every major announcement, funding round, and product launch in [industry] from the last 90 days. For each one, show me: the date it happened, the companies involved, the dollar amounts if applicable, and most importantly - what trend or shift this signals. Then connect the dots: what pattern emerges when you look at all of these together? What's about to happen in this market that most people aren't seeing yet?"
Perplexity pulls real-time data with sources. ChatGPT hallucinates dates and makes up funding rounds.
I used this to spot the AI coding tools wave 4 months early. Built a product that hit $40k MRR because I saw it coming.
2. Competitive Teardown
Prompt:
"Deep dive on [company name]. I need: their actual revenue model (not what they say publicly, what they actually charge), their customer acquisition strategy (which channels they're investing in based on job postings and ads), their product roadmap clues (based on recent hires, patents, and beta features), their weaknesses (negative reviews, customer complaints, what people say on Reddit), and their next move (based on their hiring, funding, and market position). Give me sources for everything."
ChatGPT gives you generic competitive analysis. Perplexity finds the actual Reddit threads where users complain, the actual job postings that reveal strategy, the actual data.
I've used this to reverse-engineer 30+ competitors. Know their playbook before they execute it.
ChatGPT, Claude, and Gemini turn raw spreadsheets into actionable insights in seconds.
Here are 8 prompts that automated my entire analytics workflow ↓
1. Data Cleaning
Prompt:
"You are a ruthless data cleaner. I have this messy dataset [paste sample or describe/upload file]. Tasks:
1. Fix duplicates, missing values, inconsistent formatting (dates, currencies, text case). 2. Detect and flag outliers with reasoning. 3. Suggest new derived columns if useful (e.g., age from DOB, month/year splits). 4. Output: Cleaned version summary + Python/pandas code I can run myself + before/after comparison table."
2. Instant EDA Report
Prompt:
"Act as a senior data analyst. Analyze this dataset [upload/paste CSV snippet or full description]. Produce a full EDA report in markdown:
- Summary statistics
- Distribution plots descriptions (suggest viz types)
- Correlation heatmap insights
- Key trends/anomalies
- 3–5 business questions this data answers
- Keep it concise but actionable."