hypothesis-tree

• Validating new product or feature ideas
• Investigating why metrics are underperforming
• Planning user research or experiments
• Breaking down ambiguous strategic questions
• Prioritizing what to test first
• Communicating analysis structure to stakeholders

Structure of a Hypothesis Tree

```

Main Question

"Why is X happening?"

|

+---------------+---------------+

| | |

Hypothesis A Hypothesis B Hypothesis C

| | |

+--+--+ +--+--+ +--+--+

| | | | | |

Sub- Sub- Sub- Sub- Sub- Sub-

hyp hyp hyp hyp hyp hyp

```

MECE Principle

Mutually Exclusive: No overlap between branches Collectively Exhaustive:

All possibilities covered

```

Good MECE: Bad (not MECE):

+----------------+ +----------------+

| New users | | Mobile users | <- Overlap

|----------------| |----------------|

| Returning | | New users | <- Overlap

| users | |----------------|

+----------------+ | Some users | <- Vague

+----------------+

```

Hypothesis Format

Strong hypotheses are:

| Element | Description | Example |

| --------------- | ----------------------- | ---------------------------------------- |

| Specific | Clear, measurable | "Checkout abandonment is >70% on mobile" |

| Testable | Can be proven/disproven | Not "users don't like it" |

| Falsifiable | Could be wrong | Has clear failure criteria |

| Actionable | Leads to decision | If true → do X, if false → do Y |

Step 1: Frame the Question

Convert vague concerns into structured questions:

| Vague | Structured |

| ----------------------- | --------------------------------- |

| "Growth is slow" | "Why is our MoM user growth <5%?" |

| "Users aren't engaged" | "Why is D7 retention below 20%?" |

| "Feature isn't working" | "Why is feature X adoption <10%?" |

Step 2: Generate First-Level Hypotheses

Brainstorm potential explanations, then organize MECE:

```

Question: "Why is signup conversion <30%?"

Level 1 Hypotheses:

├── Awareness: Users don't understand the value proposition

├── Ability: The signup process is too difficult

├── Motivation: The perceived benefit isn't worth the effort

└── Technical: Bugs/errors prevent completion

```

Step 3: Decompose to Testable Level

Keep breaking down until hypotheses are directly testable:

```

Ability: The signup process is too difficult

├── Too many fields required

├── Password requirements unclear

├── Form validation confusing

└── Mobile experience broken

```

Step 4: Prioritize and Test

| Hypothesis | Evidence Available | Test Effort | Impact if True |

| ---------- | ------------------ | ----------- | -------------- |

| [Hyp 1] | [None/Some/Strong] | [L/M/H] | [L/M/H] |

| [Hyp 2] | [None/Some/Strong] | [L/M/H] | [L/M/H] |

Priority = High Impact + Low Effort + Little Existing Evidence

```markdown

Central Question: [Clear, specific question] Date: [Date] Owner:

[Name]

Hypothesis Tree Structure

[Main Question] ├── H1: [First major hypothesis] │ ├── H1.1: [Sub-hypothesis] │

└── H1.2: [Sub-hypothesis] ├── H2: [Second major hypothesis] │ ├── H2.1:

[Sub-hypothesis] │ └── H2.2: [Sub-hypothesis] └── H3: [Third major hypothesis]

└── H3.1: [Sub-hypothesis]

Prioritized Testing Plan

| Priority | Hypothesis | Test Method | Timeline | Owner |

| -------- | ---------- | ----------- | -------- | ----- |

| 1 | [H1.2] | [Method] | [Time] | [Who] |

| 2 | [H2.1] | [Method] | [Time] | [Who] |

Current Evidence Summary

| Hypothesis | Status | Evidence |

| ---------- | ---------------------------- | --------- |

| [H1] | [Confirmed/Rejected/Testing] | [Summary] |

```

Example 1: Low Feature Adoption

Question: "Why is our new reporting feature only used by 8% of users?"

```

Low Feature Adoption

├── Awareness

│ ├── Users don't know it exists

│ └── Announcement wasn't clear

├── Value

│ ├── Feature doesn't solve their problem

│ └── Existing workarounds are "good enough"

├── Ability

│ ├── Feature is hard to find

│ └── Feature is hard to use

└── Timing

└── Users don't need reports frequently

```

Example 2: Churn Investigation

Question: "Why did monthly churn increase from 5% to 8%?"

```

Increased Churn

├── Product Changes

│ ├── Recent feature change caused issues

│ └── Performance degradation

├── Market Changes

│ ├── Competitor launched better alternative

│ └── Economic conditions changed

├── Customer Mix

│ ├── Acquired lower-quality leads

│ └── Channel mix shifted

└── Service Issues

└── Support quality declined

```

Do

• Start with clear, specific question
• Check MECE at each level
• Get to testable hypotheses quickly (3 levels usually enough)
• Update tree as evidence comes in
• Share tree with stakeholders for alignment

Avoid

• Overlapping hypotheses (not mutually exclusive)
• Hypotheses that can't be tested
• Going too deep without testing
• Confirmation bias (seeking to prove favorite hypothesis)

| Method | Combined Use |

| ----------------------- | --------------------------------- |

| Five Whys | Go deep on confirmed hypotheses |

| Jobs-to-be-Done | Frame hypotheses around user jobs |

| Fogg Behavior Model | Structure behavioral hypotheses |

• [The Pyramid Principle - Barbara Minto](https://www.amazon.com/Pyramid-Principle-Logic-Writing-Thinking/dp/0273710516)
• [Bulletproof Problem Solving - Charles Conn](https://www.amazon.com/Bulletproof-Problem-Solving-Changes-Everything/dp/1119553024)