After 5 months of running an AN from scratch I thought I’d write this up because, while there are plenty of AN guides around, I couldn’t find many that actually documented the journey from day to day.
This isn’t a “do these exact things and you’ll get 7★” guide.
It’s a summary of what I tested, what worked, what didn’t, and—most importantly—how I approached improving the company.
Hopefully it helps someone else.
My Philosophy
I didn’t chase one magical setup.
I treated the company like an experiment.
Every change had a reason behind it, and I tried to isolate variables wherever possible.
That meant:
- Change one thing.
- Let several ticks pass.
- Compare against the previous baseline.
- Decide whether it genuinely improved the business.
One good tick proves nothing.
One bad tick proves nothing.
Trends matter.
My Objective
Interestingly, my goal wasn’t profit.
Profit was a by-product.
My goal was stars.
Sometimes that meant making decisions which weren’t necessarily optimal for today’s income if I believed they would improve the business over the following weeks.
Recruitment Was Everything
If I had to pick the single biggest factor, it was recruitment.
I constantly upgraded staff whenever stronger applicants appeared.
I didn’t become emotionally attached to employees.
If someone significantly stronger became available, they replaced somebody weaker.
Employee effectiveness compounds across the entire company.
Better employees make almost every other decision more effective.
Constantly Testing Staff Layouts
I went through multiple structures including:
- 2 Sexperts
- 3 Sexperts
- 4 Sexperts
- Store Manager
- HR Officer
I didn’t just copy YATA recommendations.
I tested them.
For me, the setup that consistently produced the strongest overall results on the journey to 7★ was:
3 Sexperts
1 HR Officer
5 Sales Assistants
That doesn’t necessarily mean it’s universally the best setup, but it repeatedly produced good results for my company.
Advertising
I was much more aggressive with advertising than many people seem to be.
I tested everything from relatively modest spending all the way up to around $1.3 million per day.
The biggest lesson?
Popularity is slow.
Advertising doesn’t always show immediate returns.
If you’re changing ad spend every day because one tick looked disappointing, you’re probably measuring noise instead of performance.
Pricing
I spent quite a while experimenting with prices.
Eventually I settled on pricing nearly everything at around $1 below RRP.
The goal wasn’t squeezing every last dollar out of each customer.
It was encouraging consistent sales volume while maintaining healthy income.
Addiction Matters More Than People Think
Addiction quietly destroys effectiveness.
I made rehab a priority.
I even introduced bonuses for employees who maintained 0 addiction.
Losing effectiveness across several employees adds up surprisingly quickly.
Data Beats Guesswork
This was probably my biggest advantage.
I took screenshots almost every single day.
Every tick.
Every popularity change.
Every staffing change.
Every advertising adjustment.
Looking back over weeks of data made patterns obvious.
Without data you’re mostly working from memory, and memory is terrible at spotting trends.
Don’t Panic After One Tick
This is probably the biggest mistake I see.
One bad tick isn’t a disaster.
One amazing tick doesn’t prove your latest change worked.
There are simply too many variables.
I normally waited several ticks before deciding whether something had actually improved the company.
That patience probably saved me from undoing good decisions too early.
Mistakes I Made
Not everything worked.
Some of my biggest mistakes included:
- Changing multiple variables at once, making it impossible to know which one caused the result.
- Reacting emotionally to single ticks.
- Leaving employees with addiction penalties for too long.
- Overthinking stock levels.
- Trying to optimise daily profit instead of focusing on long-term growth.
Those mistakes taught me more than the successful experiments did.
What Surprised Me
A few things genuinely surprised me during the climb:
- Sometimes I’d have fantastic daily performance and miss the Sunday star.
- Other weeks I’d receive a star when I wasn’t expecting one.
- Recruitment often had a bigger impact than tweaking prices.
- Small improvements stacked together much faster than searching for one huge breakthrough.
My Advice
If I had to boil everything down, it’d be this:
- Recruit aggressively.
- Keep addiction at zero.
- Test changes properly.
- Don’t chase single ticks.
- Record your data.
- Be patient.
There’s no magic button.
Stars come from dozens of small improvements compounding over time.
Final Thoughts
Reaching 7★ wasn’t the result of one discovery.
It was the result of consistently asking:
“Can I make the company 1% better today?”
Some experiments failed.
Some worked brilliantly.
But every experiment taught me something.
Hopefully some of that trial and error saves someone else a few weeks on their own journey.
If anyone has questions about the testing or wants me to dig out data from specific experiments, happy to help.