Smart Summary
A feature that automatically analyzes heatmap data with AI and presents key page insights. Even without specialized heatmap knowledge, you can quickly understand your page's situation.
About This Feature
Traditional heatmap analysis required switching between multiple heatmap types, checking metrics for each block individually, and deriving insights manually.
Smart Summary automates this analysis process with AI. It analyzes page data from 3 perspectives and presents major findings and action directions.
Using Smart Summary, you can discover:
A summary of attention and exit points for users on the page
Performance comparisons by advertising channel
Behavioral trends across visitor segments
How to Use
Click the "Smart Summary" tab in the heatmap toolbar to display AI analysis results in the right panel.
The right panel contains 3 sub-tabs:
3 Analysis Modules
User Behavior Analysis
Analyzes user behavior on the page in block-level detail.
What You'll Learn
Key Insights: Overall analysis conclusion (e.g., "36% exit at first view, suggesting insufficient specificity in value proposition")
Phase-by-Phase Behavior Analysis: Breaks the page into 4 psychological stages and explains user behavior at each
Attention Points: High-interest areas and their reasons
Exit Points: Common exit locations and potential causes
Automatic Page Type Identification
When conducting user behavior analysis, Smart Heatmap first automatically identifies the page type. Since visitor intent and browsing patterns differ by page type, the analysis framework optimizes to match the page type.
Ad Landing Page
No navigation, single CTA, long-form text layout
Article Landing Page
Editorial article-style layout, educational content, soft CTA
Product Detail Page (PDP)
Buy box, user reviews, product gallery
Homepage
Full navigation, hero banner, brand story
Campaign Page
Event-driven, coupons/countdowns, time sales
Other
Login pages, contact forms, etc.
4-Stage Psychological Model
Based on the identified page type, block content is classified into 4 psychological stages for analysis. The basic framework for the 4 stages is:
Phase 1
"Is this relevant to me?"
Establishing relevance and first impression
Phase 2
"Do you understand my challenge?"
Building empathy, reducing comprehension cost
Phase 3
"Why should I buy this?"
Presenting rationale and proof, building trust
Phase 4
"Is it really safe?"
Reducing risk, encouraging action
Phase Names by Page Type
With the same Phase 1, a PDP user checks "Do I have the information needed to buy?" while an article LP user decides "Is it worth continuing to read?" Therefore, phase names are optimized by page type.
Ad Landing Page
Establish First Impression
Build Empathy
Give Purchase Reason
Ease Concerns
Article Landing Page
Build Reading Trust
Strengthen Problem Empathy
Convince with Solutions
Lower Action Barriers
Product Detail Page
Gather Purchase Info
Convey Product Value
Show Trust Basis
Push Purchase Action
Homepage
Clarify Brand and Target
Guide to Next Steps
Strengthen Trust and Rationale
Connect to Ongoing Relationship
Campaign Page
Focus on Campaign Value
Explain Participation Rules
Enable Quick Category Selection
Push to Order Completion
Phases 1-4 are universal alignment keys across all page types. Phase names are display labels matched to page type; analysis reports use names corresponding to the page type.
This classification is not simply dividing the page from top to bottom, but automatically determined by the psychological role each block's content plays. Since specialized classification logic is applied per page type, the same "reviews" block becomes Phase 3 (showing trust basis) for PDPs but Phase 3 (giving purchase reason) for ad LPs, reflecting contextual relevance.
Main Metrics Used
Block Average Stay Time
Determining user interest level
Block Exit Rate
Identifying exit points
Impression Rate
Confirming block reach status
Block Conversion Rate
Supporting judgment on content's CV contribution
Ad Effectiveness Analysis
Compares and analyzes performance of advertising channels driving traffic to the page.
About the conversion-rate basis: Conversion rates in this analysis are calculated using only the Primary Conversion — the conversion at the top of the conversion settings panel. Even with multiple conversion goals configured, only the Primary Conversion is referenced here. To change which conversion drives the analysis, drag the target conversion to the top in the conversion settings panel. See Block & Element Setup — Conversion Settings.
What You'll Learn
Key Insights: Comparison of highest-performing and lowest-performing ad channels (e.g., "Google search achieves 2.1% conversion rate, most effective; Instagram ads at 0.3% need improvement")
Overall Overview: Traffic composition and main ad channel performance summary
Analysis Mechanism
Ad effectiveness analysis evaluates each advertising channel on 2 axes: session count and conversion rate.
High
High
Effective Channel
Maintain and strengthen; expand success factors to other channels
Low
High
High-Potential Channel
Carefully increase distribution volume
High
Low
Requires Attention
Verify landing page alignment; reduce if not improved
Low
Low
Under Investigation
Continue small-scale testing; assess effectiveness
When a specific channel represents over 95% of traffic, it's treated as overall overview rather than comparative analysis.
Main Metrics Used
Session Count (visits)
Traffic volume
Conversion Rate
Channel quality evaluation
Bounce Rate
Landing page alignment
Click Rate
Page engagement
CTA Click Rate
Action intent indicator
Average Stay Time
Content involvement
Audience Analysis
Analyzes behavioral trends across visitor segments (region, device, visitor type, etc.).
About the conversion-rate basis: Like Ad Effectiveness Analysis, conversion rates here are based on only the Primary Conversion (the conversion at the top of the conversion settings panel).
What You'll Learn
Key Insights: Comparison of highest-quality and improvement-needed visitor segments (e.g., "Repeat visitors convert at 3x the rate of new visitors; consider strengthening repeat visitor initiatives")
Overall Overview: Visitor composition and main segment performance summary
Analysis Mechanism
Audience analysis uses the same session count × conversion rate 2-axis approach as ad effectiveness analysis to evaluate each segment.
Example analyzable segments:
Visitor Type
New visitors, repeat visitors
Device
Mobile, PC, Tablet
Region
Country, prefecture
Traffic Source
Organic search, campaigns, direct traffic
Bounce/Non-Bounce
Bounce visitors, non-bounce visitors
Main Metrics Used
Uses the same metric set as ad effectiveness analysis (excluding CTA click rate).
Analysis Tips
Use Smart Summary as Your Starting Point
Smart Summary is perfect as an analysis starting point. Based on AI-generated insights, dig deeper into areas of interest using other heatmap tabs.
"High exit in Phase 1"
→ Check Exit Heatmap around first view in detail
"Specific block shows high attention"
→ Check detailed Stay Heatmap for that block
"Specific ad channel has low conversion"
→ Use Toolbar segmentation to check that channel's heatmap
"Repeat visitors have high conversion"
→ Create initiatives for repeat visitors in Experience
Important Notes
AI analysis results show "possibility hints," not definitive causal relationships
Analysis for segments with low visit counts should be treated as reference only
Regular review reveals time-series changes
Related Features
Heatmap Comprehensive Guide — Overall view of 6 features
Stay Heatmap — For detailed attention point review
Exit Heatmap — For detailed exit point review
Toolbar Features — For narrowed-down segment analysis
Metrics Reference — Detailed metric definitions and formulas
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