The large players (Match, eHarmony, etc.) had ignored the college market.
But 18-24 year olds were craving a mobile-first option that didn't require an annoying questionnaire to get started.
Tinder used this phenomenon to turn college hookups into $1.4B in sales:
Network Effects
What they are & how to use them: 🧵
The large players (Match, eHarmony, etc.) had ignored the college market.
But 18-24 year olds were craving a mobile-first option that didn't require an annoying questionnaire to get started.
Early users.
No one would use a dating app that had few eligible candidates on the platform.
Traction is an issue that every platform business must overcome.
It's a classic "chicken or egg" problem.
It's when the utility of the platform becomes greater with each new user.
As the user base gets larger each user receives additional benefit (more dating options) leading to rapid growth.
But tapping a network effect is much more nuanced than that.
There needs to be:
A high degree of trust, common interests, and incentive to tell others about the platform.
Physical proximity and a (somewhat) even split of gender to make the platform appealing for everyone.
As a fledgling startup Tinder didn't have the cash to advertise across several markets.
So, what did they do?
They sponsored a birthday party at USC and required app downloads to gain entry.
The results were shocking...
After the first party hundreds of users were hooked.
Co-founder Sean Rad would drive to other schools in LA and help users sign up.
Then once they hit 20K users it was a tipping point - they scaled to over 500K less than a month after.
In 2021 Tinder owned 32% of the online dating market and had 75 million monthly active users.
And it's worth billions.
Tinder's success can be traced to their "college party strategy" because they created a network effect.
Here's how to do it:
To open a powerful network there needs to be multiple commonalities within that group.
Being a "college student" isn't enough.
That's a diverse group. You need a deeper level of trust to trigger a network.
Tinder used 3 layers:
Students
At USC
Greek Life
Word-of-mouth will help expand your network because it's in users best interest to spread the word.
Let passionate customers sell for you. It's cheaper and more effective.
In the mid 2010s smartphone popularity was skyrocketing for 18-24 yos. To appeal to this group, Tinder used a mobile app.
Contrast that to the web-based services of the leaders of that time.
It reduces friction for onboarding, makes sharing easier, and eliminates competition.
Find a way to be convenient for your ideal customer and they'll reward you.
Tinder launched to students because they thought they'd be the hardest to turn from users to promoters.
The idea was:
Please the critics first and growth will accelerate even more when it naturally leaks to tangential markets.
Once you pass their test you should have uninterrupted growth as your customer base grows.
This strategy helps to avoid a plateau in growth after an initial bump.
In networks, a "central node" is one that has multiple points of connection.
In human terms -- a strong reputation.
Tinder chose popular Greek Life students as their central nodes who then convinced marginal nodes (less valuable) to join.
The more central nodes you have, the stronger your network will be due to overlapping connections.
You'll speed up growth while simultaneously strengthening your customer base.
A win/win.
To do the same, find the RIGHT people with overlapping interests and built in trust.
Then launch your product, get feedback, and let the network yield exponential growth.
Please RT the 1st tweet (below) and follow @barrettjoneill for more content on business and growth! https://t.co/IQ61ISwmmL
Tinder used this phenomenon to turn college hookups into $1.4B in sales:
— Barrett O'Neill (@barrettjoneill) April 28, 2022
Network Effects
What they are & how to use them: \U0001f9f5
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In the spring and summer of 2016, as reported by the Times, activity we traced to GRU was reported to the FBI. This was the standard model of interaction companies used for nation-state attacks against likely US targeted.
In the Spring of 2017, after a deep dive into the Fake News phenomena, the security team wanted to publish an update that covered what we had learned. At this point, we didn’t have any advertising content or the big IRA cluster, but we did know about the GRU model.
This report when through dozens of edits as different equities were represented. I did not have any meetings with Sheryl on the paper, but I can’t speak to whether she was in the loop with my higher-ups.
In the end, the difficult question of attribution was settled by us pointing to the DNI report instead of saying Russia or GRU directly. In my pre-briefs with members of Congress, I made it clear that we believed this action was GRU.
The story doesn\u2019t say you were told not to... it says you did so without approval and they tried to obfuscate what you found. Is that true?
— Sarah Frier (@sarahfrier) November 15, 2018
In the spring and summer of 2016, as reported by the Times, activity we traced to GRU was reported to the FBI. This was the standard model of interaction companies used for nation-state attacks against likely US targeted.
In the Spring of 2017, after a deep dive into the Fake News phenomena, the security team wanted to publish an update that covered what we had learned. At this point, we didn’t have any advertising content or the big IRA cluster, but we did know about the GRU model.
This report when through dozens of edits as different equities were represented. I did not have any meetings with Sheryl on the paper, but I can’t speak to whether she was in the loop with my higher-ups.
In the end, the difficult question of attribution was settled by us pointing to the DNI report instead of saying Russia or GRU directly. In my pre-briefs with members of Congress, I made it clear that we believed this action was GRU.
