shady vs ethical: how the top apps got their first 1000 users
shady vs ethical: how the top apps got their first 1000 users
what founders are willing to do to achieve early network effects
network effects are embedded in every popular app we use. uber, airbnb, dropbox, slack, instagram, and more.
it’s what happens when products get more valuable as more people use them. for example, uber becomes better for both drivers and riders as more of them are available. riders wait less time to get from point a to b, and drivers stay busy and increase their earnings.
even when telephones first came out, they were more valuable with the more people you were able to call.
the network is defined by people using the product to interact with each other, and the effect is how the value increases as more people use the product.
and the first 1000 are always the hardest to get.
more competition than ever
if you’re building a product today, there’s more competition than ever with copycats everywhere ready to undercut you.
in 2008, iphone screens were empty as there weren’t many useful apps. at that time, people would have downloaded and bought any half decent game or productivity app. there was less competition and no standards from experience.
now there are hundreds of apps for each niche, so how do you stand out and take competition away? since one person likely won’t be using two different apps of the same niche.
in Andrew Chen’s book, the cold start problem: how to start and scale network effects, he writes about the five stages companies go through in building their network.
cold start problem - most new networks fail. if a video-sharing app launches and doesn’t get early users uploading good content, other users wont stick around. the creators arent getting engagement and the viewers arent getting value. some products like zoom can work with just 2 people, but others need more to be useful.
tipping point - as the network grows, its compounding effects make it grow faster and faster as more users join. tinder and facebook are an example from one college to another. each one getting easier and easier to grow.
escape velocity - strengthening the network and sustaining growth through viral loops, acquisition efforts (referral programs), engagement efforts (incentives), and economic effects (like notion selling team plans and fortnite selling costumes becoming easier as more people join).
hitting ceiling - it’s not always up and to the right. most of the time you grow, then you’re flat, you try something new, it works a little or it doesn’t, you iterate, then you grow some more.
moat -
make it harder for competitors through brand, tech, and partnerships
building brand helps when going up against goliaths.
atomic networks - one network that can self sustain, then you build another one close to it to expand.
building your network through spam
they were invite-only at first, which was a great strategy to make it feel exclusive. people without an invite will ask for one and people with the invite will want show it off.
linkedin saw explosive growth from the first week. invite-only provided a better welcome experience for new users. every new user is connected to at least one person, so it’s like walking into a party with a good friend opening the door for you, making your entrance smoother and better experience.
but the unethical thing they did they got access to your email contacts list, and spammed everyone in it, multiple times, and eventually had to settle the lawsuit
airbnb
Nathan Blecharczyk, co founder of airbnb, and once on FBI 100 wanted as a top spammer on US soil
according to joering2 on hackernews, “[they] posted unrealistically (fake) cheap rentals of beautiful apartments in places where normal rent should be 10x more. once people reply to these offers he auto-responded that the unit has been rented, but they should be looking for another unit on AirBNB website.
its first users submitting links to the platform were the founders, Steve Huffman and Alexis Ohanian.
in the early days, it was our job each to make sure there was good content on the front page. we would post it ourselves, using dozens of dummy accounts.
- Steve Huffman speaking to Andrew Chen
they eventually wrote code that would scrape news websites and post them with made-up usernames.
how companies built their networks brick by brick
wikipedia
it was the few dedicated and selfless volunteers that built, and are still building wikipedia. since wikipedia was found in 2001, more than 55 million articles have been written.
all written by a small group of users. with 500 million unique visitors per month, there are only about 100,000 active contributers per month, and they don’t get paid
Steven Pruitt has made nearly 3 million edits on wikipedia, wrote 35k original articles, and was named one of the most influential people on the internet by time magazine.
tinder
tinder made online dating easier and no one had to face rejection.
tinder started by making everyone connect their facebook account, so that they could show the number of mutual friends you had to build trust. and also made it so you would never be shown to friends to avoid any awkward moments.
their biggest gains came from throwing mansion parties. starting with USC for well connected popular kids, you could only come to the party if you downloaded the app. someone may see someone they liked but didnt get a chacne to talk to, then the next day see if they can match on tinder. and the app can stick that way.
come for the tool, stay for the network. hipstamatic was a similar app that came before instagram, and it grew to millions of users in a very short time, but it had its downfalls that instagram capitalized on.
the app had a lot of features that caused friction. you had to interact with a virtual camera, swiping through different lenses, and required multiple taps to see a filter’s effect on your photos. it also cost $1.99
but there was no social aspect to it. the photos would just save to your camera roll and you would have to post it yourself on social.
instagram was built with a network from day one. user profiles, feed, friend requests, and features to share on fb, with a link back to instagram to drive viral growth.
first week on the app store it was downloaded 100k times. and within 2 months, 1 million.