Growth related chart experiments

PS: All charts here were created using Plot.ly

Varun
Varun
Sep 4, 2018 · 5 min read

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

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:

  1. Maximize number of referral invites sent out by each new customer
  2. Maximize conversion rate of those referrals into actual customers
  3. 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.

Varun

Written by

Varun

Marketplaces, AI, UI/UX, Behavioural Economics & Community Building. Founded/built 4 products. ~10 yrs w/ Wall Street data.

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