While I think that the keynote presentations were better than in the last few years, the overall narrative still felt incredibly unexciting. It’s fascinating to see how clearly marketing isn’t baked into the Google’s DNA and how much it struggles with products that don’t sell organically like Search (Cloud is another good example of this).
Related: It’s telling that the most exciting announcement of the event wasn’t new hardware but the new recorder app. I can’t wait for this to roll out beyond Pixel phones (Side note: I’m still confused by Pixel-exclusive software features .. I doubt that they have an actual impact on Pixel sales and Google’s strategy has always been fundamentally about reach)
I’ll be switching back to an iPhone this year after being an Android user for the last five years. In those years I’ve owned about five Nexus and Pixel phones of which every single one broke after at most six months (stuck in boot loop, display stopped working, camera bugs, etc). I still prefer Android over iOS, but I just can’t justify spending another 700 bucks on a phone I constantly have to worry about dying on me. (Request for product: An iPhone that runs Android)
I was a little disappointed to see that Google ditched the fingerprint sensor in favor of face-unlock. The backside fingerprint sensor is not just more convenient but also way underrated as a secondary interface in my opinion (see: swipe for notifications).
Speaking of secondary interfaces: I love that Google is experimenting with Motion sense – even though this will face the same dilemma as the recorder app: If you keep this a Pixel exclusive, no app developer will seriously build features based on it. Why didn’t Google build this into its Nest speakers instead?
Great to hear that there finally a more serious competitor to Apple’s Airpods. I wonder why it took Google so long to start competing in this space given how much effort they put into smart speaker adoption.
Related to the previous point: I’m surprised that there’s still no Pixel watch. Feels like a necessary addition not just to the Pixel Buds but the entire ambient computing narrative.
This is a list of things and questions I’m currently interested in. I define these at the beginning of each quarter and then spend the next 3 months learning as much as possible about them. If you have any good resources (books, articles, videos, podcasts) on any of these topics, please let me know.
Charter cities
Payment processing infrastructure Related questions:
What explains the adoption of different payment methods across different countries?
We now live in a world where pretty much everything is subscription based. Listen to music? Monthly subscription. Start a meditation habit? Monthly subscription. Faster Amazon deliveries? Monthly subscription. Life as a service, essentially.
While recurring revenue streams are great for the businesses offering them, as a consumer I find it increasingly harder to keep track all my active subscriptions. Free trials, different billing periods and automatic renewals have made it really difficult to stay on top of my finances.
So I created a little subscription tracker in Notion.
In this database I save all of my subscription services including their current status (active / paused / canceled), billing period (yearly / monthly) and calculate monthly and yearly costs.
Most importantly, I save the renewal date of each subscription and add a 1 week reminder so that I still have the option to cancel before a new payment hits my credit card.
This is my quantified self report for 2018. Since 2013 I’ve been tracking various life metrics to learn more about myself and improve my productivity, health and well-being. Last year I kept track of about 50 metrics across 5 categories. Some data are captured automatically via applications such as Last.fm (music), Fitbit (steps, sleep), RescueTime (productivity) or Moves (location) – I log the rest manually in a Google Sheets spreadsheet.
>_ Physical Activity
fig 01Steps per day & Monthly Average
I took a total of 4,477,138 steps last year, which is an average of 12,226 steps per day. My most active day was May 19 with 30,147 steps. On 88 days I didn’t hit my daily step goal of 10,000. I walked less than average in colder months of the year (Jan-Apr, Dec). You can also see a dip in September where I was down with the flu for about a week.
fig 02Swim distance per week
My 2018 goals included going for a swim at least once per week and increasing the total swim distance. I didn’t miss a single week in 2018 and I swam a total of 128.5 kilometers which is a 27% increase compared to 2017. I swam in 6 different pools and 1 lake across 6 different cities in 4 different countries. The London Acquatics Centre was the nicest pool I swam in this year.
>_ Media Consumption
fig 03Time spent per medium per month
I consumed a total of 30 books last year of which I finished 18 (60% completion rate). I read 11 books on my Kindle (55% completed), 6 in paper format (33% completed) and listened to 13 as audiobooks (77% completed).
I spent 73.5 hours reading books on my Kindle, 14.5 hours reading paper books and 89 hours listening to audiobooks. That an average of roughly 29 minutes of book consumption per day.
Listening to 84 podcast episodes took up 85 hours of time last year, while watching TV and movies made up 193 and 56 hours, respectively.
Additionally, I read 361 long-form articles.
fig 04Number of songs per day
I spent 21 days and 10 hours listening to 8.820 songs (of which 3.334 were unique) from 1491 different albums by 930 different artists.
I haven’t consumed this much music since 2013 (9403 songs), which is a positive sign since I suspect that music consumption is a good proxy for productivity (my job between 2014-2017 was quite meeting-heavy).
fig 05Most popular artists & songs
More than 60% of the songs I listened to last year were electronic, ambient or contemporary classical music (ideal for productive work). I listen to most music on Fridays (a day that usually has less meetings).
Exactly half of the music I consumed were songs I listened to for the first time.
>_ Travel
I traveled 12,626 kilometers last year visiting 15 cities in 5 countries (DE, AT, CH, PL, GB). I spent the vast majority (+90%) of my time in Berlin:
fig 06Berlin Movement patterns Yellow: Walking / Red: Public Transport, Car, Taxi
I visited roughly 5 places per day (down 7% YoY) and explored 633 new locations that I hadn’t been to before.
>_ Nutrition
fig 07Coffee consumption over time Dark gray: Filter / Light gray: Espresso
I had 471 cups of coffee last year. 58% of which were filter-, 42% espresso-based.
fig 08Beer consumption per month
I drank 113.85 liters of beer last year (which is less than I drank in 2017, but still above the average per capita consumption in Germany).
fig 09Beer consumption vs. Soccer vs. Temperature Left: Soccer Games (in min) / Right: Average temperature (in °C)
I compared the data to the time I spent watching soccer and the average temperature, which are the two factors I assume have the highest influence on my beer drinking behavior.
fig 10Old Fashioned’s consumed per month
As if the number of beers wasn’t concerning enough, I additionally had 43Old Fashioned’s and 101 glasses of wine. (I decided to cut down my alcohol consumption this year.)
I ate 12 bowls of Ramen, 15 Burgers, 14 Gemüsekebabs, 7 Bibimbaps, 2 Poke Bowls, 4 Schnitzels, 78 slices of Pizza and 82 dishes of Pasta.
I limited my meat consumption to 24 meals, but had fish or seafood on 83 occasions.
>_ Wellbeing
fig 11Perceived Happiness Daily Scores + Monthly average
I rate each day on a scale of 1-5 with 1 being “Very Unhappy” and 5 being “Very Happy”. I evaluate this in the morning of the next day. I’m aware that this method far from perfect (recency bias, etc) and will probably switch to a tool like Felix Krause’s Mood Tracker.
My average happiness score last year was 3.49. March and October were my happiest months, but I don’t have a good explanation for why this is the case.
I keep similar scores for Perceived Stress (1 = Very relaxed, 5 = Very stressed), Perceived Sleep Quality (1 = Hardly slept, 5 = Slept really well) and Perceived Back Pain (1 = No Pain, 10 = Very Painful).
fig 12Perceived Stress Weekly Average
On average I reported a daily stress level of 2.47. Unsurprisingly, weekends were less stressful (1.69) than work days (2.78). My stress levels also decreased whenever I took a vacation.
fig 13Time Asleep Weekly Average
I spent 2859 hours and 50 minutes asleep last year. That’s 32.64% of the entire year or 7:50 hours per day.
fig 14Perceived Sleep Quality Left: Monthly Average | Right: Weekday Average
I reported an average daily sleep score of 3.68. I slept best in March (4.03) and in nights between Thursday to Friday (3.92). May (3.26) and nights between Sundays and Mondays (3.36) received the lowest perceived sleep quality scores.
fig 15Perceived Back Pain Weekly Average
After suffering from chronic back problems for a few years, I started tracking my pain levels in 2017 to get a better understanding of which treatments actually had a positive impact.
In 2018, my average reported daily back pain was 1.45 – down from 4.2 in 2017.
fig 16Backpain vs. Swim Distance vs. Stationary Time Left: Swim Distance | Right: Stationary Time
I compared my back pain numbers to my swim activities (which seem to have some impact) as well as the time I spent stationary (no physical activity).
>_ Productivity
fig 17Time Spent on Computer Weekly Duration
I spent 1709 hours in front of my MacBook last year – that’s 19.51% of the entire year.
fig 18Top Activities Time spent per application / website
Twitter was by far my most used application in 2018: I spent (wasted?) a total of 161hours on the platform last year (note that this doesn’t include phone screen time).
98 hours were spent reading and writing emails in Google Inbox – my second most used app last year. I switched to Superhuman at the end of last year and I’m curious if my 2019 data will support the company’s promise of making email faster and more efficient.
fig 19Productivity Scores Time spent per category
Every app and website is tagged with a productivity label ranging from Very Productive to Very Unproductive. I spent the majority of the time (907 hours) doing either Very Productive or Productive work. 602 hours were marked as Unproductive or even Very Unproductive.
fig 20Productivity over time Average Weekly Productivity Score
Based on the applications’ productivity labels and the time I spent in them, a productivity score between 0 (Very Unproductive) and 100 (Very Productive) is calculated. My overall 2018 productivity score was 56 – down from 62 in 2017.
fig 21Productivity Scores vs. Perceived Stress vs. Perceived Productivity Left: Perceived Stress | Right: Perceived Productivity
My productivity score follows a similar pattern to my perceived stress levels as well as my perceived productivity (which is an additional 1-5 score with which I rate each working day manually).
>_ Meta
I worked on this report for 13 hours and 25 minutes 🙂
