I A/B Tested My Daily Walk To The Office

Every single day I’ve been walking the same path to my office and back home, let’s call it route A. But a little while ago I found that there’s an alternative route (B) that might be faster and I should consider changing my daily routine and choose the new route. But I wasn’t so sure about that.

I only have 24 hours a day, and every second is important to me. I’m really sensitive of my time and that’s why I really wanted to optimize my routines and do the best I can to save more time each day.

Why not use Google Maps or any other GPS to determine the duration of each route? 🤔

I did, I tried and Google showed that my current route (A) is faster by about one minute. But I knew I couldn’t relay on that because these maps don’t take in account the time wasted in red traffic lights at crosswalks, nor certain corners and roads I can cut through, and some other parameters.

So I decided to A/B test it

For 10 days, I walked to the office each day through one of the two different routes. Route A on Monday, route B on Tuesday, again A on Wednesday and so on. I used my iPhone’s stopwatch to record the duration of each walk and kept all my data on a note.

I needed lots of data

Since there are many dynamic parameters that influence my speed, I knew I needed at least 20 walks (10 through each route) to start getting data I can rely on. Lots of things are affecting the duration of my walk:

  1. Crosswalk traffic lights are dynamic 🚦 and even a single long red light might be a game changer.
  2. Unexpected things on the road such as constructions and people that walk slowly in front of me are changing my speed.
  3. My current mood and my energy is dynamic and sometimes when tired I walk a bit slower than usual.
  4. The weather is also a parameter since walking in cold weather is always faster.
  5. The time of day is meaningful since there is a chance my speed is different between the morning and the evening.

I tried to walk naturally

Acting like no one is measuring me was the biggest challenge. It was really hard to stop thinking about my speed and the ticking stopwatch. I knew I had to keep my speed consistent without trying to adjust or compensate my steps. When I was concentrated on it, my walking speed wasn’t natural and reliable.

But I made it. 🙌 After 3 days I started to pay no attention to the test and stopped being focused on my speed.

During these 10 days of testing I knew there is a chance I might not get enough indicative data to come to a conclusion, and maybe I’ll have to continue my test for a longer time. Luckily, I started to notice some results after few days, but continued the test to collect more data and make it more accurate and reliable.

All the data I’ve collected by walking through two different routes every day

Result: Route B was faster!

Google Maps was wrong. I was surprised to realize that for a full year I was spending my time on route A, without knowing that there is a faster alternative route. In average, route A’s duration was 11:49 minutes, while route B was 11:11 minutes. That means I could’ve save 38 seconds each morning and each evening which equals to 6.5 minutes per week!

The new route (B) was 38 seconds faster in average (based on 20 walks data)

38 seconds are not a dramatic difference, but definitely enough time that’s worth saving. As I said in the beginning, I’m really sensitive about my time.

In addition, I discovered another interesting fact: my average evening walk duration is 11:09 minutes among both routes combined. This is way faster than my morning walk which is 11:51 (42 seconds slower).

My evening walk duration was 42 seconds faster in average

What I’ve learned?

  1. You know nothing, Google Maps.
  2. I should always look towards alternative routes and solutions for every little thing in my life. The trick is to figure out how to measure and analyze each option in the most reliable way.
  3. Beside the challenge, the curiosity and the excitement of making the test, I realized that A/B testing is an easy and practical tool everyone can use in their day-to-day life to optimize different activities without much effort.
  4. Data is objective and the more data there is, the more accurate the conclusion. I‘m considering testing some other activities in my life which I can optimize such as my workout sessions, nutrition, the amount of money I spend, my sleep and more.

Thanks for reading!

Please hit the clap button 👏 if you liked this story! Let me know if you have any comments or if you ever tried A/B test in your day-t0-day life.

I’m Gal, a product designer and art director. You can subscribe to my mailing list and receive my next articles directly to your inbox.

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