Growth related chart experiments
PS: All charts here were created using Plot.ly

This is what you want eventually. How do you get there and how do you start thinking about growth ? I’ve added some thoughts below.
Pick a metric and target 8% week-over-week growth
In the early days of your startup, you don’t necessarily need a big bang growth event. Small, incremental growth, “doing things that don’t scale” is what is sufficient as you go along the journey to reach product/market fit. This will keep you focused — press coverage, launch events, and other pretend to be a successful startup actions are distractions from a systematic approach in getting an increasing small number of customers using your product, week after week.
If you choose the metric of 8% week-over-week growth, the below chart should make you feel good about it. This chart is purely theoretical and no startup actually has a consistent growth rate like this — but it signifies the qualitative difference between a 5% and a 8% week-over-week growth in customers. Its job is to help pinpoint this metric which you can focus on in the very early days — it is a good path to be on.


Design product with inherent network effects
Network effect happens when existing users derive higher value from more members joining the network. It is not a result of growth, though it would be a key factor in causing it if the product design supports it.
For instance, Facebook in its early days targeted having >80% penetration in the colleges it operated in, but more importantly, having >50% retention.
They discovered that Facebook really became a social utility to their users when they reached at least 7 friends within 10 days of signing up. Twitter and LinkedIn are reported to have followed similar focus: a user getting to X connections in Y days.
Facebook in its very early days tried to reach this goal by pre-populating user profiles and suggesting friends you may know.
http://www.richardprice.io/post/34652740246/growth-hacking-leading-indicators-of-engaged
Chamath spoke about how his growth team discovered the “7 friends in 10 days” leading indicator. He said that they looked at cohorts of users that became engaged, and cohorts of users that did not become engaged, and the pattern that emerged was that the engaged cohorts had hit at least 7 friends within 10 days of signing up.
Chamath said that, when he was running the growth team at Facebook, he focused on four things:
Acquisition: how to acquire users.
Activation: how to get users to their ‘Aha’ moment as quickly as possible
Engagement: how to ensure users experience the core product value as often as possible
Virality: how to get people to get more people onto the platform
He said there had been a tendency in growth teams he was aware of to measure the time to the “Aha” moment in days. His view is that it should be measured in hours, and ideally minutes and seconds. The idea is that a user should get an “Aha” moment as soon as humanly possible after signing up.
Design product with an inherent viral loop, maximizing on # of invites, conversion rate and minimizing time spent in each loop
Virality needs to be built in the product from day 1. Consistent week-over-week growth is good to start with but not practical/sustainable over a longer period, at some point the startup’s growth needs to take off significantly. That is feasible only through virality. It can be either non-paid (“hey try this product — it is really good”) or paid (“hey try this product — both of us get $X each if we do use it”). Without users referring others to use your product, you can’t grow fast enough as a startup.
There are three key factors to optimize while building this into your product:
- Maximize number of referral invites sent out by each new customer
- Maximize conversion rate of those referrals into actual customers
- Minimize the time spent end-end in each viral loop
Below charts illustrate these points..
Viral Growth Scenario #1: 10 new invites by each new customer with a 20% conversion rate

Viral Growth Scenario #2: 10 new invites by each new customer with a 5% conversion rate
As you can see — this is not viral growth. Low conversion rate doesn’t work — it needs to be optimized.

Viral Growth Scenario #3: 4 new invites by each new customer with a 20% conversion rate
As you can see, this is not viral growth either. Low number of invites sent out by each customer doesn’t help — this needs to be optimized.

Key element missing above is time
The viral loops need to run much quicker — the time between each cycle needs to be minimized. Think about the difference between coming across and sharing a Youtube video link vs getting and using, then referring Uber to others.
..and that’s all for now. Maybe some day I will add more charts here; or not.
