Growth requires testing. Most businesses guess. They don’t test. They waste resources.
Experiments enable learning. Controlled tests reveal truth. Data drives decisions.
This hub provides templates, ideas, and tracking sheets for running controlled growth experiments.
Key Takeaways
- Understand experiments—learn testing methods
- Use templates—follow proven formats
- Track results—measure what matters
- Test systematically—run controlled tests
- Learn continuously—improve from data
Table of Contents
Experiment Overview
Experiments test hypotheses. They reveal truth. They enable learning.
Experiments are controlled: They isolate variables. They measure results. They prove causality.
Experiments are systematic: They follow process. They use templates. They track results.
Why this matters: Experiment understanding enables testing. If you understand experiments, testing becomes possible.
Experiment Templates
Templates standardize experiments. They ensure completeness. They enable comparison.
Hypothesis Template
Structure:
- Hypothesis statement
- Expected outcome
- Success metrics
- Test duration
- Resources needed
Why this matters: Template structure ensures completeness. If you use template, completeness improves.
Experiment Plan Template
Structure:
- Hypothesis
- Test design
- Variables
- Metrics
- Timeline
- Resources
Why this matters: Plan template enables execution. If you use template, execution improves.
Results Template
Structure:
- Results summary
- Data collected
- Analysis
- Conclusions
- Next steps
Why this matters: Results template enables learning. If you use template, learning improves.
Pro tip: Use our TAM Calculator to evaluate market opportunity and inform growth experiments. Calculate market size to understand potential.
Experiment Ideas
Experiment ideas spark testing. They provide direction. They enable action.
Pricing Experiments
Test pricing strategies:
- Price points
- Pricing models
- Discount strategies
- Payment terms
Why this matters: Pricing experiments optimize revenue. If you test pricing, revenue optimizes.
Channel Experiments
Test growth channels:
- Marketing channels
- Sales channels
- Partnership channels
- Referral channels
Why this matters: Channel experiments find best channels. If you test channels, best channels emerge.
Product Experiments
Test product changes:
- Features
- Positioning
- Packaging
- Messaging
Why this matters: Product experiments improve fit. If you test products, fit improves.
Process Experiments
Test process improvements:
- Sales processes
- Onboarding processes
- Support processes
- Operations processes
Why this matters: Process experiments increase efficiency. If you test processes, efficiency increases.
Tracking Sheets
Tracking sheets organize data. They enable analysis. They support decisions.
Experiment Log
Track experiments:
- Experiment name
- Hypothesis
- Status
- Results
- Learnings
Why this matters: Experiment log enables organization. If you track experiments, organization improves.
Results Dashboard
Track results:
- Key metrics
- Performance data
- Trends
- Comparisons
Why this matters: Results dashboard enables analysis. If you track results, analysis improves.
Learning Log
Track learnings:
- Insights gained
- Patterns identified
- Decisions made
- Actions taken
Why this matters: Learning log enables improvement. If you track learnings, improvement improves.
Pro tip: Use our TAM Calculator to evaluate market opportunity and inform growth experiments. Calculate market size to understand potential.
Your Next Steps
Growth experiments hub provides templates, ideas, and tracking. Understand experiments, use templates, track results, test systematically, then learn continuously to improve from data.
This Week:
- Begin understanding experiments using our TAM Calculator
- Start using experiment templates
- Begin generating experiment ideas
- Start setting up tracking sheets
This Month:
- Complete experiment setup
- Run first experiments
- Track results systematically
- Begin learning from data
Going Forward:
- Continuously run experiments
- Use templates consistently
- Track all results
- Learn and improve
Need help? Check out our TAM Calculator for market evaluation, our starter kit for levers, our strategy selection guide for matching, and our scaling guide for growth.
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FAQs - Frequently Asked Questions About Growth Experiments Hub: Templates, Ideas, and Tracking Sheets for Testing New Ta
What should a growth experiment hypothesis template include?
Include a clear hypothesis statement, expected outcome, success metrics, test duration, and resources needed.
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A hypothesis template structures your experiment so you know exactly what you are testing and how to measure success.
The hypothesis statement should be specific and follow the format: If we do X, then Y will happen, measured by Z.
Define success metrics upfront so you can objectively evaluate results rather than interpreting them after the fact.
Include test duration and resource requirements to ensure the experiment is feasible and time-boxed.
What categories of growth experiments should a small business test first?
Start with pricing experiments and channel experiments since they have the highest potential revenue impact with relatively low risk.
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Pricing experiments test different price points, pricing models, discount strategies, and payment terms to optimize revenue.
Channel experiments test marketing channels, sales channels, partnership channels, and referral channels to find what works best.
Product experiments test features, positioning, packaging, and messaging to improve product-market fit.
Process experiments test improvements to sales, onboarding, support, and operations to increase efficiency.
How do I set up an experiment tracking sheet to organize multiple tests?
Create an experiment log with columns for experiment name, hypothesis, status, results, and key learnings for each test.
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An experiment log tracks every test you run with its name, hypothesis, current status (planned, running, complete), results, and learnings.
Add a results dashboard that tracks key metrics, performance data, trends, and comparisons across experiments.
Maintain a learning log capturing insights gained, patterns identified, decisions made, and actions taken from each experiment.
This three-part tracking system ensures no experiment goes unrecorded and every insight is captured for future use.
What makes a growth experiment controlled versus just trying something new?
A controlled experiment isolates variables, measures specific results, and proves causality rather than just correlation.
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Controlled experiments follow a systematic process: define hypothesis, isolate the variable being tested, measure results against a baseline.
Simply trying something new does not isolate what caused the result. Multiple changes at once make it impossible to know what worked.
Use templates to standardize experiments so they are comparable across different tests and time periods.
Track results systematically using defined metrics so you can objectively determine success or failure.
How do I use an experiment plan template to design a test before running it?
Fill in your hypothesis, test design, variables being tested, metrics to track, timeline, and required resources before launching.
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Start with a clear hypothesis stating what you expect to happen and why.
Define the test design: what you will change, what you will keep the same, and how you will measure the difference.
List the specific variables you are testing and the metrics you will use to evaluate success or failure.
Set a timeline with start and end dates, and allocate resources needed so the experiment runs without interruption.
How should I document and apply learnings from completed growth experiments?
Use a results template capturing the results summary, data collected, analysis, conclusions, and specific next steps.
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After each experiment, document the results summary with actual numbers compared to your hypothesis predictions.
Record all data collected during the test and your analysis of what it means for your business.
Draw clear conclusions: did the experiment validate or invalidate your hypothesis? What surprised you?
Define specific next steps, whether to scale the tactic, iterate with a new test, or abandon the approach entirely.
How many growth experiments should I run simultaneously?
Start with one experiment at a time until you build confidence, then scale to 2-3 concurrent tests as your tracking systems mature.
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Running too many experiments at once makes it hard to isolate what is working and overwhelms your tracking capacity.
Begin with a single experiment to learn the process. Use templates, track results, and document learnings.
Once you have reliable tracking sheets and experience analyzing results, add a second and third concurrent experiment.
Ensure each experiment tests a different variable so results do not contaminate each other.
Sources & Additional Information
This guide provides general information about growth experiments. Your specific situation may require different considerations.
For market size analysis, see our TAM Calculator.
Consult with professionals for advice specific to your situation.
