❝Story00:00
Renting a Stadium to Hire 60,000 Gojek Drivers in Weeks
Crystal recounts one of Gojek's most audacious early growth moves: renting an actual stadium, staffing long lines with boxes of pre-loaded phones and SIM cards, and onboarding tens of thousands of motorcycle-taxi drivers in a couple of weeks. She admits the risk of joining felt huge when she arrived to find the company operating out of a house, but the product was already growing fast at ~4,000 orders a day.
- Gojek ran mass driver hiring by literally renting a stadium (a couple of football fields).
- Roughly 60,000 drivers were onboarded in a couple of weeks.
- Setup was long lines, boxes of phones and SIM cards handed to drivers.
- Company was still tiny (in a house) but already growing at ~4,000 orders/day.
“we ended up renting a stadium to just hire like 60 000 drivers in a couple of weeks”
“when i got there it was in a house and i realized i've probably made a huge mistake”
#growth#hiring#gojek#scrappy#operations
❝Story13:00
Wizard-of-Oz Tests: Validating Features Without Building Them
Crystal describes Gojek's scrappy playbook for testing ideas before writing code. To test a subscription feature, they added 100 drivers to a WhatsApp group, had them sell the package on rides, and manually processed vouchers in the backend. For a new onboarding screen, a designer overlaid a mockup on a screenshot and shipped it as an in-app message. The point: manifest the desired user experience as fast as possible, then build only what works.
- Tested a subscription feature via a WhatsApp group of 100 drivers selling manually, with interns processing vouchers in the backend.
- Faked a new onboarding screen by overlaying a designer mockup on a screenshot and sending it as an in-app message.
- Used Typeform surveys and quizzes as fake features to gauge demand.
- Built in-app web deployment so web-testable features didn't wait on mobile app releases.
“this concept of doing things that are somewhat crazy but validate a point doing stuff that don't scale especially i think is really the bread…”
“it's really this wizard of oz experience we don't have to build anything”
#experimentation#scrappy#wizard-of-oz#product#gojek
❝Story19:00
Hacking Trust: Using Friends' Orders to Sell New Restaurants
For GoFood, Crystal's team realized users needed trust before ordering from an unfamiliar merchant. Using existing Facebook Connect permissions, they surfaced food that a user's friends had purchased and liked. Users shown a friend's purchase were twice as likely to order from a brand-new restaurant lifting GMV by solving for trust rather than optimizing conversion directly.
- Diagnosed that trust, not conversion mechanics, was blocking orders from new merchants.
- Leveraged existing Facebook Connect permissions to see friends' past purchases.
- Showed users food their friends had bought and liked as social proof.
- Users with the feature were 2x more likely to order from a brand-new restaurant, raising GMV.
“we actually looked at the food that their friends had purchased and used that as a data set of hey here's food that lenny purchased…”
“you would be twice as likely to purchase from a brand new restaurant than users who did not have this feature”
#growth#trust#social-proof#gofood#conversion
❝Story32:00
Turning Drivers Into GoPay Salespeople With a Captive Audience
To drive GoPay adoption, Crystal's team built a small service that detected when a driver was allocated a customer with no digital balance, then messaged the driver an incentive to get the customer to top up with cash. Trapped together in the car, drivers became remarkably effective salespeople and customers felt the benefit explained directly. It became ~60% of acquisition with no change to the product's physics, just a new use of an existing lever.
- A backend service checked whether an allocated customer had ever used GoPay.
- If not, it messaged the driver an incentive to convert them via cash top-up.
- Drivers' captive attention in the car made them highly effective salespeople.
- Drove ~60% of GoPay acquisition once released, with no change to product physics.
“you wouldn't believe how great of a salesperson someone can be when you were literally trapped in a car with them going somewhere”
“it was huge it was like 60 of acquisition once we released that”
#growth#gopay#incentives#distribution#gojek
❝Story38:00
Beat Subscription Churn With a Pause Button, Not a Cancel
Advising a beer D2C brand, Crystal found the top cancellation reason was "I still have too much beer." The app let users cancel or resume but not pause a permanent solution to a temporary problem. Adding a pause button alleviated churn that was otherwise hard and expensive to reacquire. Lenny notes the same pattern powered one of Airbnb's biggest wins: a snooze/pause feature for listings.
- Top cancellation reason for a beer subscription was simply having too much beer.
- App only allowed cancel or resume, forcing a permanent fix for a temporary problem.
- Adding a pause button solved churn at the exact constraint where users dropped off.
- Airbnb's listing snooze/pause was one of its biggest wins for the same reason.
“canceling the subscription is a permanent solution to having too much beer how do you make a temporary solution that solves the actual problem”
“this is actually one of the biggest wins is adding a snooze feature to your listing”
#churn#retention#subscriptions#product#d2c
❝Story53:30
Hiring Growth: A Take-Home Experiment-Design Case Study
To hire growth people, Crystal screens for first-principles bias with a case study: given a claimed result, how do you know it's true, and how would you design an experiment to test it? She wants candidates who sample randomly and take a measured approach, not those who assume their feature will work. She gives a take-home (about four hours over five days), not a live test, and specifically values candidates who admit they had to Google it and read white papers.
- Screens for first-principles bias: "how do you know this is true?" plus an experiment design.
- Wants random sampling and a measured, deliberate approach over assuming a feature will work.
- Uses a take-home (~4 hours over 5 days), not a live test, to see real quality.
- Values candidates who admit they Googled it and read white papers to figure it out.
“i actually look for that first principle bias so i'll give people case studies of like here's what we see how do you know that…”
“we like to hear people say that they literally had to google this and read a bunch of white papers”
#hiring#growth-team#interviewing#experiment-design