AI-Powered Recommendations

Pro Plan

AI recommendations give you actionable suggestions to improve your analytics, optimize your site, and grow your business.

What Are AI Recommendations?

Intelligent suggestions based on your data:

Type	Example
Optimization	"Mobile conversion is low - investigate"
Opportunity	"Traffic from LinkedIn converts well - invest more"
Best Practice	"Consider adding goals for key actions"
Warning	"Bounce rate trending up - take action"

Types of Recommendations

Conversion Optimization

Improve conversions:

• "Checkout abandonment is 65% - review friction points"
• "Top landing page has no clear CTA"
• "Mobile users struggle at step 3"

Traffic Growth

Grow your audience:

• "Organic traffic has momentum - double down on SEO"
• "Social referrals convert well - increase social presence"
• "Content gap: Consider topics your competitors rank for"

Engagement Improvement

Increase engagement:

• "Average session is short - add engaging content"
• "Most visitors see only one page - improve navigation"
• "Video content increases time on site 3x"

Technical Health

Fix technical issues:

• "Page load time is slow on mobile"
• "JavaScript errors increasing - review recent changes"
• "Several 404 errors detected"

Viewing Recommendations

Recommendations Feed

Access all recommendations:

1. Go to AI Insights → Recommendations
2. View prioritized list
3. Click for details
4. Take action

In-Context Recommendations

See relevant suggestions:

• On dashboard pages
• In specific reports
• During analysis
• Near related metrics

Priority Indicators

Priority	Meaning
🔴 High	Significant impact, act now
🟡 Medium	Important, address soon
🔵 Low	Good to do when possible

Recommendation Structure

Each Recommendation Includes

Element	Purpose
Title	Brief description
Context	Why this matters
Evidence	Supporting data
Impact	Expected benefit
Action	What to do
Difficulty	Effort required

Example Recommendation

📊 RECOMMENDATION

Title: Improve Mobile Checkout Experience

Context:
Mobile users have 45% lower conversion rate than
desktop users, primarily dropping at checkout.

Evidence:
• Mobile checkout completion: 28%
• Desktop checkout completion: 52%
• 1,200 mobile users abandon weekly

Impact:
Fixing this could increase conversions by ~20%,
adding approximately $8,000/month in revenue.

Suggested Actions:
1. Review mobile checkout flow in sessions
2. Simplify form fields for mobile
3. Add mobile payment options (Apple Pay)
4. Test one-page checkout

Difficulty: Medium
Estimated Effort: 1-2 weeks

Acting on Recommendations

Evaluate First

Before acting:

1. Review the data
2. Confirm the issue
3. Assess feasibility
4. Consider alternatives

Take Action

Options when viewing:

• Implement - Start working on it
• Schedule - Plan for later
• Dismiss - Not applicable
• Investigate - Need more info

Track Progress

Enterprise Plan

Mark implementation status:

• Not started
• In progress
• Completed
• Deferred

Measure Results

After implementing:

• AI tracks if metrics improve
• Before/after comparison
• Success confirmation

Recommendation Categories

Quick Wins

Easy to implement, high impact:

• Adding missing tracking
• Fixing broken links
• Simple UX improvements

Strategic Changes

Larger initiatives:

• Major redesigns
• Platform changes
• New features

Experimental

Worth testing:

• A/B test suggestions
• New approaches
• Optimization experiments

Personalized Recommendations

Learning Your Business

AI adapts to:

• Your industry
• Your goals
• Your patterns
• Your history

Context-Aware

Recommendations consider:

• Recent changes
• Current performance
• Historical patterns
• Your capabilities

Feedback Loop

AI improves from:

• Which you implement
• What works
• Your dismissals
• Your feedback

Common Recommendations

For E-commerce

Issue	Recommendation
Cart abandonment	Simplify checkout
Low product views	Improve navigation
High bounce	Better landing pages
Mobile drops	Mobile optimization

For SaaS

Issue	Recommendation
Low trial conversion	Improve onboarding
High churn indicators	Engagement campaigns
Feature adoption	In-app guidance
Pricing page exit	Clear value props

For Content Sites

Issue	Recommendation
Low engagement	Interactive content
Short sessions	Related content
High bounce	Better headlines
Low subscriptions	Clear CTA

Scheduled Recommendations

Regular Cadence

AI provides:

• Weekly top recommendations
• Monthly strategic review
• Quarterly opportunity scan

Triggered Recommendations

Based on events:

• After significant changes
• When anomalies detected
• At milestones

Team Collaboration

Sharing Recommendations

Share with team:

• Send via email
• Post to Slack
• Add to tasks
• Discuss in meetings

Assignment

Enterprise Plan

Assign to team members:

1. Open recommendation
2. Click "Assign"
3. Select owner
4. Set deadline

Discussion

Enterprise Plan

Collaborate on recommendations:

• Add comments
• Discuss approach
• Track decisions

Recommendation Settings

Customization

Control what AI suggests:

Setting	Options
Focus areas	Traffic, Conversion, Engagement
Difficulty filter	Easy only, All
Frequency	More/fewer recommendations
Notification	Email, In-app, Both

Muting Categories

If some aren't relevant:

• Mute specific types
• Reduce frequency
• Focus on priorities

Best Practices

Review Regularly

• Weekly recommendation review
• Prioritize by impact
• Track implementation
• Measure results

Don't Ignore Low Priority

Low priority still valuable:

• Quick improvements
• Technical debt
• Foundation building

Give Feedback

Help AI improve:

• Rate recommendations
• Explain dismissals
• Share results

Troubleshooting

Recommendations Not Useful

If suggestions miss the mark:

• Provide more feedback
• Adjust focus areas
• Check data quality
• Wait for learning

Too Many Recommendations

If overwhelmed:

• Filter by priority
• Bulk dismiss noise
• Adjust sensitivity
• Focus on categories

Same Recommendations Repeating

If seeing duplicates:

• Mark as implemented
• Dismiss if done
• AI will update

Next Steps

• Understanding insights
• Anomaly detection
• Visitor value scoring