More Data = Better Decisions

You need real customer data to make an educated choice on which vertical to focus your business on.

Choosing a vertical to target without supporting customer data is a guess at best.

That's why early-stage start-ups shouldn't be too choosy.

Roughly speaking, there are two revenue tiers:

•Pre-500k: don't be too choosy, experiment, say yes a lot

•Post-$500k: mine your customer data, figure out who to start saying no to

Frequently Asked Questions

Why is choosing a vertical without customer data considered just a guess?

Because without real evidence from actual customer patterns, the decision is based on assumption rather than confirmed fit, retention, revenue, and satisfaction data that only comes from real experience with real clients.

Why shouldn't early-stage startups be too selective about which clients they take on?

Because before reaching around $500K in revenue, there isn't yet enough customer data to reliably identify which vertical is genuinely the best fit. Saying yes broadly during this stage allows real patterns to emerge.

What should happen once a business crosses the roughly $500K revenue threshold?

Mining existing customer data to identify patterns, then figuring out who to start saying no to, using real evidence rather than continuing to accept any client indiscriminately.

Why does this two-tier approach make sense as a business grows?

Because the earliest stage lacks the data needed to specialize confidently, while a business with more revenue and history has accumulated enough real customer information to make a genuinely informed vertical decision.

What's the practical takeaway from this revenue-based framework?

That vertical specialization decisions should be timed to actual data availability, experimenting broadly pre-$500K, then narrowing deliberately based on real patterns once enough customer history exists to support that choice.