Line in the Sand
What is a line in the sand?
Drawing a line in the sand means setting a specific, predetermined threshold for success before you run a test or experiment—essentially deciding in advance what results would make your hypothesis pass or fail. This number determines in black and white terms whether your hypothesis passes or fails and should dictate how you act on the results.
Without this clear boundary, teams fall prey to rationalization. If you hypothesize that a change will improve conversion rates by 10%, then a 9% increase means your hypothesis fails—even though it's close. The line in the sand prevents you from convincing yourself that 9% (or 2%, or even -2%) is "good enough" simply because you like the change or invested time in it.
Why draw a line in the sand before testing?
Setting a threshold upfront serves two critical purposes. First, it protects you from your own biases. After seeing results, it's human nature to rationalize any positive change as worthwhile. But that 2% improvement might not justify the investment or opportunity cost when you could have pursued a solution that cleared a higher bar.
Second, an aggressive line in the sand motivates better solutions. If your threshold is low, you'll settle for incremental improvements. If your threshold is high enough to make the investment worthwhile, you'll push your team to find solutions that truly move the needle.
How do teams use lines in the sand?
When running assumption tests or experiments, work as a team to define success before you test. Ask: What results would we need to see for this solution to succeed? What increase makes this investment worthwhile given the cost and opportunity cost?
Then commit to that number. Use it to compare and contrast different solutions against each other, asking "Which solution looks best?" instead of "Is this result good enough?" This shifts evaluation from subjective judgment to objective comparison.
Learn more:
- The 5 Components of a Good Hypothesis
- How to Estimate the Expected Impact of a Product Change
- Assumption Testing: Everything You Need to Know to Get Started
Related terms:
- Hypothesis
- Assumption Testing
- A/B Test
- Compare and Contrast Decisions
Last Updated: October 25, 2025