Understanding AI Recommendations
Learn how our AI analyzes products and provides actionable insights to help you make informed e-commerce decisions.
How Our AI Works
Our AI system processes vast amounts of data to provide you with intelligent recommendations
Market Analysis
AI analyzes market trends, competition, and demand patterns
Product Scoring
AI evaluates products based on multiple success factors
Smart Recommendations
AI suggests optimal strategies and next steps
Best Practices
Get the most out of our AI recommendations by following these best practices
Ask Specific Questions
Be specific about what you want to know about a product or market
“Instead of 'Is this product good?', ask 'What are the profit margins for this product in the electronics category?'”
Provide Context
Give the AI context about your business goals and constraints
“Tell the AI about your budget, timeline, and target audience for better recommendations.”
Review Multiple Insights
Don't rely on a single recommendation - review all available data
“Look at market trends, competition analysis, and profitability metrics together.”
Validate with Research
Use AI insights as a starting point, then do your own research
“Cross-reference AI recommendations with external market research and competitor analysis.”
Understanding AI Scores
Learn what the different scores and metrics mean in our AI analysis
Profitability Score (1-100)
This score indicates the potential profitability of a product based on current market conditions, competition, and pricing trends.
Competition Level
Measures the level of competition in the market for a specific product or category.
Related Articles
Continue learning with these related help articles
Still Have Questions?
Our support team is here to help you understand and make the most of our AI recommendations.