Minute Monday #1: The impact of failing fast

Grow faster by accelerating learning

Why is it important for product and growth teams to find ways to fail fast?

Assumptions:

1. Failing = learning (don’t bork your experiments)

2. 25% mean experiment win rate (75% of hypotheses disproven)

3. 20% baseline metric

4. 5% mean relative uplift for winning experiment

5. Team A runs 1 test per month

6. Team B runs 2 tests per month

Let’s see what happens over the course of 24 months.

It’s an overly simplistic example, but illustrates the point:

Team A lifts the metric from 20% to ~27%

Team B lifts the metric from 20% to ~36%

What’s the lesson here?

Prioritise learning

Experimentation is relatively expensive. You may or may not have sample size volume to go faster with formal testing. So diversify the testing techniques you use to get valid learnings faster.

• Minimum viable tests (Painted door etc)

• Observations

• Prototype studies.

• Surveys

• …

Ask yourself - what’s the cheapest, fastest way we can test our hypothesis?