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My First MillionMy First Million

The 5-Step Process To Build & Sell A $100M Business | ft. Jason Lemkin

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Jason LemkinguestSam Parrhost
Apr 10, 202444mWatch on YouTube

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At a glance

WHAT IT’S REALLY ABOUT

Jason Lemkin's Rules for Reverse Engineering a $100M Software Business

  1. Lemkin recounts his path from a $50M nano-battery exit and the EchoSign sale to Adobe through investing and running the SaaStr conference business.
  2. He lays out reverse-engineering rules: reach $300-400K revenue per employee, build a second product bigger than the first by about 10,000 customers, and get roughly 30% of revenue from outside North America.
  3. He says founders should localize products, price near comparable products, relentlessly remove sales friction, and work toward 100% net revenue retention, using HubSpot as an example.
  4. Lemkin and Parr discuss the hard economics of conferences and high-churn newsletters, noting that churn of 3-5% a month becomes crushing around $10M in revenue.
  5. Lemkin argues founders should raise little or nothing, and avoid double-digit millions unless they are committed to a billion-dollar outcome, citing his own worst investing loss.

IDEAS WORTH REMEMBERING

5 ideas

Revenue per employee must reach $300-400K

Lemkin says old software giants made about $1M per employee, ZIRP-era unicorns fell to about $100K, and public SaaS companies like HubSpot and Cloudflare now sit at $310K and $400K. Funding only bridges the gap to that level, or the model isn't scalable.

The second product must be bigger than the first

Founders default to easy extensions like shampoo and conditioner, but if the first product keeps growing, a small add-on never catches up. Lemkin says you want a bigger second product by about 10,000 customers, and Parr admits he made this mistake with his Trends product.

Founders usually underprice, and good sales leaders fix it

Lemkin says about 80% of founders underprice, and a strong VP of Sales can lift revenue 30 to 100%. Parr says his own Trends subscription at $300 a year should have been far higher.

Let international demand find you, then support it

Lemkin says to invest once an area passes 5% of revenue, and to localize the product into more languages even though most engineers resist it. He cites Salesforce, which got dragged into Japan and reached 10% of revenue there.

Anchor pricing to comparables and remove friction

Lemkin says customers know what software should cost, so price at or slightly below similar products rather than claiming there is no comp. A founder's daily job is to remove friction, such as easier sign-up, single sign-on and faster support.

WORDS WORTH SAVING

5 quotes

If you wanna reverse engineer things, you have to have a model with economies of scale that gets you to 3 to $400,000 per employee, or your model is not real. It is not scalable.

— Jason Lemkin

The second one has to be bigger than the first, and this is, it's too, it, we all default to the easy second product, and you actually have to do the harder one.

— Jason Lemkin

Your job as a founder, if you wanna scale, if you wanna reverse engineer things, your job, 'cause no one else in your company will do this, your job is every day to relentlessly remove friction from your customer acquisition process.

— Jason Lemkin

If you raise more than 10 million, you're signing up for a billion-dollar exit.

— Jason Lemkin

If you don't feel it in your bones, then don't raise double digit millions. Just don't do it.

— Jason Lemkin

Read the available transcript
Revenue per employee benchmarksMulti-product expansionPricing and removing frictionInternational expansion and localizationNet revenue retention and churnConference business economicsHow much venture capital to raise

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SPEAKERS

  • Jason Lemkin

    guest

    Founder of SaaStr and former CEO/founder of EchoSign, a SaaS operator and investor known for scaling and go-to-market expertise.

  • Sam Parr

    host

    Entrepreneur and co-host of My First Million; founder of The Hustle newsletter (acquired by HubSpot).

High quality AI-generated summary created from speaker-labeled transcript.

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