How AI Can Accelerate Product Testing and Distribution Strategies

If you're truly ambitious, burn your resume. If you define your ambition in the eyes of your consumer, not your peers, you're not trying to win awards and respect from your peers, you're trying to win the hearts and minds of nurses in Indiana, like for Farmville.
If you do Proven Better New right, the product has much better odds of succeeding in the market, not failing for the wrong reasons.
I believe if I offered you a free, 24/7 travel agent that was always there for you, knows your travel context, knows you, and will actually book, not just book travel, but I think the most valuable part is when you're in the middle of a travel, a trip, be ready to rebook your flight and be on top of, you know, your travel logistics as they're happening and often failing.
- Your human instincts are right 95% of the time, but the ideas you put on top of those instincts are usually wrong 75% of the time. The 'Proven, Better, New' framework helps to come up with and refine product ideas, increasing the odds of success.
- The best product makers are 'collecting winnings,' not 'making bets.' They already *know* they have a hit before launching, focusing on an 'MLP' (maximum launchable product) rather than an 'MVP' (minimum viable product).
- AI is currently being used more to build *one* idea in three months rather than enabling rapid experimentation by testing 100 ideas in a day. The optimal approach is to 'build it wrong before you know it's right,' prioritizing learning over initial perfection.
- Distribution is crucial and cannot be an afterthought. It must be baked into the product strategy from the beginning. If you're just hoping your product spreads virally, that's a 'hope strategy,' not a 'belief strategy.'
- Many successful companies find a pro-sumer approach by targeting power users or 'whales' who are willing to pay upfront for value, allowing for sustainable business growth before needing mass consumer adoption.
- Meeting your children where they are, engaging with them at their current altitude as human to human, leads to teaching them sophisticated concepts far beyond their expected age level.
- In the AI era, it's crucial to teach children critical thinking and how to ask better questions, rather than simply knowing more answers. They need to understand how to be 'generative' and contribute something new to the world, not just be 'consumptive.'
- The number one job of a CEO is to be right. Being in the right 'body of water' (market/strategy) matters more than having the best 'boat' (execution). Prioritizing strategic correctness over flawless execution leads to better outcomes.
- 95% (Human instincts are right 95% of the time.)
- 75% (Ideas put on top of instincts are wrong 75% of the time.)
- $1.6 trillion (Hypothetical future valuation of a company if an instinct were pursued correctly.)
- 10/10 (The proportion of existing users who should say 'F yeah!' about a 'better' product improvement.)
- 14 million (Daily active users (DAUs) for Words with Friends.)
- 45 (Number of games Rovio made before Angry Birds was a hit.)
- 60 days (Draw Something was the #1 game and app in the App Store for 60 days.)
- 50 (Maximum number of employees Zynga had when Mark Pincus micromanaged daily stand-ups.)
- 2 hours (Duration of daily stand-up calls at Zynga with 50 employees.)
- $25 million (Amount invested in Pincus's 'Daughter Project' (metaverse vision).)
- 4 years (Duration Pincus worked on his 'Daughter Project'.)
- 3 months (Time to build a 'viable' AI product, compared to 3 years before.)
- $19 million (Value of early access keys sold for a Farmville expansion pack, showing marketing can become a revenue stream.)
- $23 billion (Size of the video gaming industry in 2007 when Zynga started.)
- $280 billion (Current size of the gaming industry.)
- +35 to -35 (NPS score drop when users quit Facebook/Instagram, indicating negative sentiment.)
- 0 (Average app installs per user per month today, highlighting the challenge of discovery.)
- 40,000 (Number of new games launched last year in the App Store, with zero becoming top 10 hits.)
RevBots.ai View:
- AI Sprinkler teams often misuse AI for incremental gains rather than transformative experimentation.
- ARM-stage companies integrate distribution into product strategy from inception.
- Pro-sumer approaches align with SaaS Hoarder strategies of targeting niche, high-value users.
- AI Sprinkler leaders should focus on teaching teams to ask better questions, not just find answers.
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