The clearest sign of finding product-market fit is feeling "pull" from the market.

But what does "pull" look like?

👇 Read on 👇

1/ Sign 1: A sudden inflection in organic growth

Netflix: "Where before we were struggling to get traffic, all of sudden we couldn’t keep up." - @mbrandolph

Tinder: "Downloads started to skyrocket" – @badeen

Uber: "Word of mouth was uncontrollable" – @ryangraves
2/ Sign 2: Customers ask to pay for the product before you ask

Carta: "I've been trying to get to your sales people for weeks!!! Why won't you take my money???" – @henrysward

Github: "To our surprise, users started writing to us asking ‘Can we pay for this??’" – @mojombo
3/ Sign 3: Users flip from excited to upset

Datadog: "When we hit early product-market fit, our users switched from being excited at all the things our product could be to them to being upset about all the things it didn't do yet." – @oliveur
3b/ Segment: "The thing that flipped was, people would previously tell us they wanted a feature, but not use it. Whereas now, people were using it and they would want a second feature." – @reinpk
4/ Sign 4: Customers complain when your site is down

Nextdoor: "10 minutes after taking the servers offline, I started getting emails/calls from users. What happened to Nextdoor? One user called me in a panic because she needed to contact a neighbor immediately." – @sarahleary
5/ Sign 5: People use the product even when it’s broken

Gusto: "A pretty good sign for PMF was when in spite of the obvious gaps in our marketing, product and care, we saw consistently high NPS (80+), low churn, and record high MoM organic growth.” – @tomerlondon
6/ Sign 6: Consistent and accelerating growth

Datadog: "We started seeing a regular influx of sign-ups, and as we added key features (such as alerting), we saw them use our product more and more actively" – @oliveur
6b/ Superhuman: "I asked our Head of Growth to update all our analytics. What we saw was that every single metric was amazing — growth, DAU/MAU, PMF score, NPS, virality, CAC payback, CAC:LTV, activation rates, long-term retention rates, and so on" – @rahulvohra
6b/ Substack: "We've just been growing fairly consistently, and gradually the how-do-we-keep-up anxiety got bigger and bigger until there wasn't time left in the day to worry about whether we had product-market fit." – @cjgbest
7/ For much more check out the full post https://t.co/R5RvHrUNeZ

More from Lenny Rachitsky

More from Startup

https://t.co/l8WgaAnWg7 launch day!

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2/
With 5 validation blocks,
https://t.co/ePe7HTa9of will help you understand if your idea is viable:

- Validating The Market

- Validating The Problem

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3/
Have no idea on how to validate?

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4/
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I've got you. Inside every check, you'll find:
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A THREAD ON @SarangSood

Decoded his way of analysis/logics for everyone to easily understand.

Have covered:
1. Analysis of volatility, how to foresee/signs.
2. Workbook
3. When to sell options
4. Diff category of days
5. How movement of option prices tell us what will happen

1. Keeps following volatility super closely.

Makes 7-8 different strategies to give him a sense of what's going on.

Whichever gives highest profit he trades in.


2. Theta falls when market moves.
Falls where market is headed towards not on our original position.


3. If you're an options seller then sell only when volatility is dropping, there is a high probability of you making the right trade and getting profit as a result

He believes in a market operator, if market mover sells volatility Sarang Sir joins him.


4. Theta decay vs Fall in vega

Sell when Vega is falling rather than for theta decay. You won't be trapped and higher probability of making profit.