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[Matrix Moments] Why network effects are important for any startup

In this week’s Matrix Moments, Avnish Bajaj, Founder and Managing Director, Matrix Partners India talks about the importance of network effects.

[Matrix Moments] Why network effects are important for any startup

Saturday July 24, 2021 , 2 min Read

Many organisations and people have written and talked a lot of things about network effects. But it remains a topic that has very little lay understanding, and its importance is often overlooked.


Summarising in a nutshell by using the textbook definition, Network Effects is a phenomenon where a product service gains additional value as more people use it. For example – instant messaging is a market with strong network effects. 

Avnish Bajaj, Founder and Managing Director, Matrix Partners India explains, “Often, when people look at cohorts, they are used to looking at — 'I started at this month and how does it decay over the next 12 months,’ and so on and so forth. People call the first month as M0 or M1 (month zero or month one), where we have the first engagement, and that adds on.” 

Citing an example, he said in the network effects businesses, as M1 started going up, 100 people came in the first month – M0, and 35 came back in M1. Next month, 100 came in month 0, and 40 came back in month 1. So, the second batch of 100 is seeing more value than the first 100 – that’s called a Network Effect. 


“Because essentially, they are seeing something by virtue of more people getting engaged. The whole thing is seeing more value. That’s the classic definition of Network Effects. That’s also the definition of a brand, because as a brand builds, people tend to want to come back. That’s also the definition of your product. It is all about finding more and more salience but, I think the ultimate measure of network effects is vertical cohorts and the best example will be Ola and Uber.”  


He explains the minute the liquidity in the market goes up, users can find a cab sooner. This will repeat more and that would show up in the first month’s behaviour – and that’s why it’s a network effect.


Edited by Kanishk Singh