4 Promising Start-up Trends from my pitch (deCk) Diligence

I review 100s of pitches and pitch decks every year and typically write about mistakes others make – in their pitches or businesses. Last week, I was asked to share my take on what founders are doing well in their pitches and businesses.

Win #1: Founder-Product Fit

Founders who’ve lived their customers’ pain and understand this underserved market are already building products they will pay for from the beginning.

• These founders have the moat of knowledge! AI is not the moat!

• For some VCs, investing in founders with lived customer pain is a core part of their thesis. 

• Bonus: Combining that with an understanding of how the product is actually solving your customers' pain points will help you find your niche and product-market fit! Please see my talk from LATechWeek 2024 for more details.

Win #2: Revenue Model Aligns Incentives

It’s easy to say that we’ll charge our customers $10 per month! But is the value proposition clear?

• It’s much easier to charge $10 per month when you save your customer $100/month. 

• It’s also much easier to charge $100 per month when that’s only a (very small) percentage of additional revenue you bring/save your customers each month!

The more clearly a start-up explains its pricing structure in terms of incentives for all sides, justifying the “no-brainer” for its customers, the easier it will be to sell and scale it.

Win #3: Product Focuses on Efficiency

This one is more controversial! One way to align incentives and tie the product into customer workflows is to focus on efficiency. This directly translates into time/money saved and makes it easier to justify the revenue model.

• If this efficiency is repeatable and scalable with technology, and you can show how it will become a $100M+/year business [NFX], it will be more attractive to investors!

Win #4: Realistic about AI

In a world where everyone seems to have an “AI” start-up, whether “AI” is needed or not, it’s clear that you’re GTM is not via AI but with a product that solves a pressing customer need for customers, one they’re willing to pay for; technology/AI is just a (simple) tool to help you get there.

• The team (which includes advisors and contractors) has developed data-driven algorithms to solve a similar/same customer problem previously and knows what it will take to execute beyond academia or a POC.

What trends are you seeing?

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