Predictive Analytics
Predictive Analytics uses machine learning to forecast user behavior, identify trends, and provide actionable recommendations.
Overview
SiteData's predictive features analyze your historical data to:
- Forecast future traffic trends
- Identify high-value visitors
- Predict conversion likelihood
- Detect anomalies and issues
- Suggest optimization opportunities
Enterprise Feature: Full predictive analytics is available on Enterprise plans. Pro plans include basic trend analysis.
Prediction Types
Traffic Forecasting
Predict daily, weekly, and monthly visitor volumes based on historical patterns.
Conversion Probability
Score visitors based on their likelihood to convert.
Churn Risk
Identify users who may stop engaging with your site.
Peak Time Prediction
Forecast when your busiest periods will occur.
Traffic Forecasting
The traffic forecast model considers:
- Day-of-week patterns
- Seasonal trends
- Historical growth rates
- Recent momentum
Conversion Scoring
Each visitor receives a conversion score (0-100) based on:
- Pages viewed and engagement depth
- Time on site and return visits
- Similarity to past converters
- Traffic source quality
AI Insights
The Predictive tab surfaces automated insights:
| Insight Type | Example |
|---|---|
| Trend Alerts | "Traffic from Google up 23% this week" |
| Anomaly Detection | "Unusual drop in mobile conversions" |
| Opportunities | "Users from email convert 2x better" |
| Forecasts | "Expect 15% more traffic next Monday" |
Using Predictions
Marketing Planning
- Schedule campaigns during predicted high-traffic periods
- Allocate budget to high-converting traffic sources
- Plan content around seasonal forecasts
Sales Prioritization
- Focus on visitors with high conversion scores
- Trigger outreach for engaged prospects
- Personalize experiences based on intent
Infrastructure Planning
- Scale resources before predicted traffic spikes
- Schedule maintenance during low-traffic windows
- Monitor anomalies for potential issues
Best Practice: Review predictive insights weekly and integrate them into your planning process.
Accuracy & Data Requirements
Data Requirements
Predictive models improve with more data:
| Feature | Minimum Data | Optimal Data |
|---|---|---|
| Traffic Forecast | 30 days | 90+ days |
| Conversion Scoring | 100 conversions | 1,000+ conversions |
| Anomaly Detection | 14 days | 60+ days |
Improving Accuracy
- Ensure consistent tracking across all pages
- Track key conversion events
- Allow time for pattern learning
- Review and validate predictions regularly
Note: Predictions are probabilistic and should inform decisions, not replace judgment. Unusual external events (holidays, news, etc.) may affect accuracy.