We need to go viral
Why spend money on ads when we can just go viral? Thousands of failed startups assumed their product was so good users would tell their friends about it. Virality doesn't work that way: it has to be engineered by understanding, modeling and optimizing all the inputs.
Viral Growth
Word of mouth is the oldest and still the most important marketing channel, and has only accelerated in the age of social media...More
We're going to do an initial beta test and launch to 20,000 users at a university campus
That'll buy us time to fix any bugs and iterate on what's working
We'll have 1,000 initial test users who are on our email list, and from there we expect to spread virally through the school
Can you make a few assumptions and build a viral growth model I can present to the board?
Once we know what to expect, we can track our progress against your model
This course is a work of fiction. Unless otherwise indicated, all the names, characters, businesses, data, places, events and incidents in this course are either the product of the author's imagination or used in a fictitious manner. Any resemblance to actual persons, living or dead, or actual events is purely coincidental.
It's easy to find the concept of viral growth appealing: who doesn't want to grow their product via word of mouth and save on advertising costs? In reality true virality is rare: often what we call 'viral' is really the result of a large influencer sharing to their audience. True virality is when each person that uses the product tells more than one person about it, recruiting new users via word of mouth or social media.
If you achieve viral growth your product will grow exponentially – like a biological virus – as 1 user gets 3, and 3 get 9, 9 get 27, then 81, 243... fast forward 10 cycles and that 1 initial user has 'infected' over 20,000. Keep growing at this rate for 12 more cycles and you've reached 10 billion users, more than the population of Earth. Of course in reality exponential 'hockey-stick' growth doesn't continue forever, it's just the first part of an S-Curve. Growth flattens out as the audience becomes saturated, and most people who get invited have already joined.
To calculate virality a handful of metrics are important. The number of invites each user sends out is key: this doesn't have to be actual invite messages, they could be simply telling their friends about a new app, or using it in a prominently visible way. Next is the conversion rate from users being exposed to the product and actually signing up as a new user. Finally the carrying capacity is what gives us our S-Curve, as we can use it to adjust the conversion rate downwards as the audience becomes saturated.
I am going to show you how to model viral growth. So this is what we're going to end up with. I'm just going to create a new tab, a which will be here, and we need to put a few different assumptions into the model first. So the assumption. The kind of inputs that you hard-code into the model the convention is you want to do these in blue.
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