Stop Starting From Scratch—Build on What You've Learned
Testing in Circles
You've run hundreds of tests, but each new one feels disconnected. Are you building on wins or just running random experiments?
Repeating Past Mistakes
New team member suggests a test that flopped last year. Without historical context, you're doomed to repeat failures.
Missed Iteration Opportunities
You found a winner but never explored variations. How much bigger could that lift be with a few iterations?
Hours Spent Planning
Every roadmap planning session involves digging through old reports and debating what to test next. Time you could spend running tests.
AI-Powered Recommendations That Build on Your History
GrowthLayer learns from every test you run and surfaces intelligent next steps—so you're always building on what works.
Smart Suggestions
AI analyzes your test history and recommends iterations on winners, follow-up tests for inconclusive results, and new directions based on learnings.
Avoid Duplicates
Never accidentally re-run a failed test. Get warnings when a proposed test is similar to something you've already tried.
Compound Your Wins
Turn a 5% lift into a 15% lift by systematically iterating. GrowthLayer suggests variations that could amplify your successes.
Why Teams Love Smart Recommendations
Save Hours on Planning
Stop debating what to test. Get prioritized recommendations in seconds, not hours.
Clarity on Next Steps
Every test result comes with recommended follow-ups. Never wonder "what now?" again.
Compounding Wins
Build iteratively on successes. Stack small wins into major conversion improvements.
Faster Time-to-Value
New team members get up to speed instantly with contextual test suggestions.
AI That Learns
Recommendations get smarter as you run more tests. Your history becomes your advantage.
How It Works
Who Uses Iteration & Recommendations
Systematic Iteration
Build a culture of continuous improvement. Every test leads to the next logical step.
Data-Driven Roadmaps
Let test results inform your product roadmap. Know which features to double down on.
Onboard Fast
New hires get instant context on what's been tried and what to explore next.
Stop re-running failed tests
GrowthLayer flags duplicate experiments before you launch them. When a test wins, AI suggests follow-up iterations to compound the lift. When it loses, you get alternative hypotheses to try instead.
Part of a Complete Testing System
Recommendations work best when paired with your full test library and insights.
Frequently Asked Questions
How does the AI generate recommendations?
Our AI analyzes your entire test history—outcomes, hypotheses, page types, and more—to identify patterns. It surfaces opportunities to iterate on winners, suggests follow-ups for inconclusive tests, and warns you when a proposed test is too similar to something that already failed.
Do I need a lot of past tests for recommendations to work?
The more tests you have logged, the smarter recommendations become. However, even with a small library, you'll get value from duplicate detection and iteration suggestions. As you run more tests, the AI learns your specific context and patterns.
Will it recommend tests that don't fit my site?
Recommendations are personalized to your testing history and context. The AI considers what you've tested before, your page types, and your industry. You can also filter recommendations by category or page type to focus on what's most relevant.
How is this different from a test ideas library?
A test ideas library gives you generic patterns. Iteration & Recommendations is personalized—it looks at YOUR past tests and suggests specific next steps based on what YOU have already learned. It's the difference between a cookbook and a personal chef who knows your tastes.