Inspired by Derek Sivers and nudged on by my friend Ryan Martinsen, I’ve added a /now page to this site which I’ll try to keep up to date with what I’m up to. It was fun putting it together and I think it will help me stay focused.
Check out Derek’s guidance on how to create one of your own.
If someone asked you about your site’s conversion rates, you could probably tell them what the conversion rates are (right?). But what if someone asked you what % convert within an hour, a day, or a week?
We’ve been looking at this at Automattic and I wound up putting together an R script to help with the analysis. Because everything needs a fancy name, I dubbed it Chronos and you can check it out on Github.
All you need to do to use it is generate a CSV containing two columns: one with the unix timestamp of the first event and another with the unix timestamp of the second event:
1350268044,1408676495 1307322538,1350061315 1307676110,1340667657 1307661905,1337311786 1307758702,1428877904 ...
The script will then show you the distribution of time between the two events as well as the percent that occur prior to a few fixed points (30 minutes, 1 hour, etc):
Distribution: 5% within 2 minutes 10% within 5 minutes 15% within 1 hour 21 minutes 20% within 1 day 38 minutes 25% within 3 days 2 hours 58 minutes 30% within 6 days 9 hours 20 minutes 33.33333% within 11 days 35% within 14 days 40% within 23 days 45% within 42 days 50% within 67 days 55% within 95 days 60% within 148 days 65% within 210 days 66.66667% within 232 days 70% within 288 days 75% within 390 days 80% within 550 days 85% within 677 days 90% within 920 days 95% within 1288 days 100% within 1715 days Percentage by certain durations: 13% within 30 minutes 14% within 1 hour 17% within 5 hours 20% within 1 day 30% within 7 days
In addition to analyzing conversion rates, you can use this to measure things like retention rates. The data above, for example, looks at how long between when users logged their first beer and last beer in Adam Week‘s handy beer tracking app, BrewskiMe (thank you again Adam for providing the data).
If you run into any issues or have any suggestions for how to improve it just let me know.
I love learning about other people’s daily schedules because it often helps me improve my own. With that in mind, here’s what my typical weekday looks like these days:
7am/8am – I wake up when my 14-month old son Mason wakes up and starts complaining. I experimented with waking up at 6am for the first two weeks of January, but really don’t like getting up earlier than I have to so it didn’t last. My wife is 8 months pregnant so I try to let her sleep in.
7:30am – 8:30am/9am – Take care of Mason, make breakfast, shower.
9am – 12pm – Work. At Automattic we all work remotely so I’m very fortunate not to have a commute. One day a week I cowork at Canvs in Orlando. Some days I work from local coffee shops, mainly Starbucks. I have 2 to 3 meetings per week (via Zoom or Google Hangouts) all of which usually last less than an hour. Most of the time I’m reading about other things going on at Automattic, participating in discussions relating to whatever I’m working on, or coding.
12pm – 1pm – These days, I take an hour midday to eat lunch (a salad), stretch (via the Yoga Studio app), meditate (via the Calm app), and watch a TED talk (on Netflix).
1pm – 4pm/5pm – Work. Some days I hit the gym around 4pm, but most days I work until around 4:30pm or 5pm.
5pm – 9pm/9:30pm – Family time.
9pm/9:30pm – 10:30pm/11pm – Some mix of reading, side projects, straightening up the house, and TV before heading to bed.
Not every day as structured as this might make it seem, but this is a pretty good approximation for how my weekdays go.
Our second kid is due in mid-March… it will be interesting to see how all of this changes after he or she arrives 🍼.
If you’re open to sharing your schedule, please drop me an email or message me on Slack. Maybe we can get a few ideas from each other to experiment with in our own schedules.
At the beginning of January I posted about my goal to drop 5 pounds by the end of the month and offered to pay my friend Tom $300 if I didn’t reach it.
Today is February 1st and the final number is… down 4.4 pounds. Whomp whomp. The “good” news is that Tom fell short of his goal as well and because I was close, we’re just going call it even.
For February, I’m going to do something similar but iterate on the rules because the ones outlined above have some weaknesses:
With these in mind, here’s my bet with Tom for February:
My goal is to get to 184 pounds (down 4.6 pounds from this morning). For the last week of the month, I’ll weigh in each morning then we’ll use an average so that the day to day fluctuations even out. For every pound I’m over 184, I’ll pay Tom $50. For every pound under 184, he’ll pay me $50. If I’m successful, that will put me down 9 pounds from the beginning of the year.
I’ve been experimenting with a lot of lifestyle and diet changes over the last few weeks.
What went well
What went alright
What went poorly
I’m happy with the progress I made in January and am looking forward to continuing to build healthier habits going forward. Writing about it here helps keep me accountable and lets me share what I’m learning so thank you for reading :). If you have any recommendations that might help, don’t hesitate to drop me a note.
Matt Mazur 