📍 A true story from San Jose

I moved to a new city and trusted Google Maps. Here's how that went.

Four stops. Four lessons. One tool I wish I had from the start.

The journey that broke my trust in reviews

🏢 Week 1 · Finding an apartment

The apartment search that wasted my entire weekend

New city, no connections. Searched Google Maps for apartments, sorted by rating. Found several with 4.5+ stars and hundreds of reviews. "Great management!" "So quiet!" "Perfect location!"

Spent my entire weekend visiting them.

⏰ What I learned

One place had broken AC units visible from the parking lot. Another had "secure" mailroom doors that didn't lock. A third had management that didn't return calls. The reviews didn't help me filter out any of these.

47 five-star reviews posted in 7 days — right before rental season. All vague. All strikingly similar. The pattern was there, but I couldn't see it.

Okay, lesson learned. Read reviews more carefully next time, right?

Wrong.

🏥 Month 3 · Healthcare

The urgent care that charged me for a FaceTime "diagnosis"

Sprained my leg during a climbing session. Needed to check if it was broken. Searched "urgent care near me" and picked the 4.7-star clinic closest to my house — highest rated in the area.

💰 What happened

They charged me for a FaceTime call where a doctor looked at my leg through the screen and said "no fracture." No X-ray. No in-person exam. Just a bill for telling me what I could have guessed myself.

The reviews made it sound professional. The experience was anything but.

~60d cycle of review bursts. Same vague praise, same timing pattern. Critical reviews about overcharging and poor service were far less visible.

This one scared me. Healthcare decisions based on reviews that didn't reflect my experience? That's not annoying — that's risky.

✂️ Ongoing · Everyday services

Even a haircut. Even that.

Important event coming up. Needed to look sharp. Found a 4.8-star barber — "best fade in the city!"

✂️ The result

Uneven sides. Neckline like an EKG reading. "It'll grow out" he said. 🙃

12 generic 5-star reviews in 48 hours. No photos. No details. Just "Great haircut!" on repeat.

It wasn't bad luck. It was a pattern. And I finally realized: I can't spot unusual patterns with my eyes alone.

💡 The realization

I needed a tool that sees what humans can't

The questionable reviews looked genuine. The critical reviews were far less visible. I couldn't tell the difference by reading.

But data reveals patterns humans miss. Review spikes. Timing patterns. Unnatural rating distributions. These things are mathematically detectable.

So I built something to highlight those patterns.

That's why FakeReviewRadar exists.

One click reveals the patterns humans miss. So you don't have to learn these lessons the hard way.

Get FakeReviewRadar — Free

This story reflects my personal experiences and observations. FakeReviewRadar analyzes statistical patterns in publicly available reviews and does not make factual claims about businesses or reviewers.