I'm excited to share a new growth framework that @danhockenmaier and I have been developing (with help from the amazing @reforge crew)
I've been finding myself coming back to this framework often when talking to founders about growth.
Thread
2. 💥 Turbo boosts: One-off events that accelerate growth temporarily but don’t last (e.g. PR, events, Super Bowl ads)
4. ⛽ Fuel: The input that your engine requires to run (e.g. capital, content, users).
Companies grow primarily through four possible Growth Engines:
• Performance marketing: FB, AdWords, TV, etc.
• Virality: Word-of-mouth, referrals, inviting friends, etc.
• Content: SEO, shareable videos, or newsletters, etc.
• Sales: Salespeople
• Uber/Lyft: Virality + Performance marketing
• Snapchat: Virality
• Zoom: Virality + Sales
• Slack: Virality + Sales
• Salesforce: Sales
https://t.co/djWwLzhqOk
Next, we have Turbo Boosts. Similar to a turbocharger in a car, these are tactics that can accelerate growth for a period of time but don’t deliver ongoing acceleration. They include things like:
• PR
• Events
• Brand marketing campaigns
Third, we have lubricants. Lubricants don’t drive growth directly, but instead optimize the efficiency of your engine. Also, without enough lubrication, your engine will stop. There are 3 broad categories of lubricants:
• Conversion
• Activation
• Retention
https://t.co/MlrmElVjF0
Finally, we have Fuel. Without it, even the most optimized engine won’t run. The type of fuel required is specific to the type of growth engine you’re running:
• Paid marketing and sales engines primarily need capital, which can be invested in ads or salespeople
• Content engines unsurprisingly need more content, which can be used to attract users.
• Viral engines require only more users, who in turn refer additional users.
Huge shout-out to @bbalfour and @onecaseman for their help with this post, and to my brother-from-another-mother @danhockenmaier
https://t.co/ZGW1qWT5zC
More from Lenny Rachitsky
Matt Mochary has been CEO coach to @naval, the founders of OpenAI, Notion, Rippling, Robinhood, Coinbase, Reddit, Plaid, Flexport, Opendoor, partners at Sequoia, YC, Benchmark, and many others.
He also open-sourced his entire curriculum, templates and all. Here's a link 👇
The Mochary Method Curriculum ➔ https://t.co/A8J51IzYhz
My recent conversation with @mattmochary where we talk about fear, anger, innovation, how to lay people off well, and his coaching practice ➔
Also in podcast form ➔
For more from Matt, buy this book
He also open-sourced his entire curriculum, templates and all. Here's a link 👇
The Mochary Method Curriculum ➔ https://t.co/A8J51IzYhz
My recent conversation with @mattmochary where we talk about fear, anger, innovation, how to lay people off well, and his coaching practice ➔
Also in podcast form ➔
For more from Matt, buy this book
More from Tech
Machine translation can be a wonderful translation tool, but its uses are widely misunderstood.
Let's talk about Google Translate, its current state in the professional translation industry, and why robots are terrible at interpreting culture and context.
Straight to the point: machine translation (MT) is an incredibly helpful tool for translation! But just like any tool, there are specific times and places for it.
You wouldn't use a jackhammer to nail a painting to the wall.
Two factors are at play when determining how useful MT is: language pair and context.
Certain language pairs are better suited for MT. Typically, the more similar the grammar structure, the better the MT will be. Think Spanish <> Portuguese vs. Spanish <> Japanese.
No two MT engines are the same, though! Check out how human professionals ranked their choice of MT engine in a Phrase survey:
https://t.co/yiVPmHnjKv
When it comes to context, the first thing to look at is the type of text you want to translate. Typically, the more technical and straightforward the text, the better a machine will be at working on it.
Let's talk about Google Translate, its current state in the professional translation industry, and why robots are terrible at interpreting culture and context.
Straight to the point: machine translation (MT) is an incredibly helpful tool for translation! But just like any tool, there are specific times and places for it.
You wouldn't use a jackhammer to nail a painting to the wall.
Two factors are at play when determining how useful MT is: language pair and context.
Certain language pairs are better suited for MT. Typically, the more similar the grammar structure, the better the MT will be. Think Spanish <> Portuguese vs. Spanish <> Japanese.
No two MT engines are the same, though! Check out how human professionals ranked their choice of MT engine in a Phrase survey:
https://t.co/yiVPmHnjKv
When it comes to context, the first thing to look at is the type of text you want to translate. Typically, the more technical and straightforward the text, the better a machine will be at working on it.
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https://t.co/enzOXDCogV
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Facebook was launched on Feb 4th, 2004.
Many of the LifeLog team became execs at FB.
Zuckerberg is a figurehead.
CIA allowed Cambridge to help Trump win
https://t.co/enzOXDCogV
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Facebook began the exact same day.
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Pentagon Kills LifeLog