Prepared by Yuliia Shvetsova

Before you burn budget on campaigns, you have to run a few tests. That is before placing big bets on sth you’re not sure will work.

Over the years, I’ve worked with B2B founders on getting the strategy right before scaling — which almost always means getting the experiments right first.

The hypothesis framework in this guide is what I use with clients to bring structure to channel testing without turning it into a bureaucratic exercise.

What a hypothesis actually is

Where hypotheses come from

The experiment sequence

The two approaches to testing

Types of marketing campaigns

What to track

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When to stop an experiment

If after 3–4 weeks and 50+ contacts you have under 3% reply rate on outbound, under 20% open rate on email, or zero meetings booked from a month-long campaign — it failed. That's data, not a disaster. Change one variable at a time and test again. The mistake is running the same failing experiment for three months hoping something changes.

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