Insights Panel
When you select an entity in Intelligence, the right-side panel displays contextual information plus recommendations. Some recommendations are AI-generated by the agent runtime; others are computed by deterministic heuristic rules. The panel labels them differently so you always know which is which.
01Customer detail
Selecting a Customer shows:
- Contact info: name, email, associated platforms
- Timeline: ordered list of touchpoints and interactions
- Current stage: position in the campaign funnel with progress percentage
- Opportunities: any detected buying signals for this customer
- View in Pipeline: button to jump to the corresponding CRM record
02Campaign insights
Selecting a Campaign shows:
- Reach: number of customers connected to this campaign
- Funnel stages: Awareness, Consideration, Decision, Conversion with counts
- Attribution: revenue and conversions attributed to this campaign
- Recommendations: suggested optimizations (timing, audience, frequency)
03Recommendation types
The panel surfaces two kinds of recommendations, visually distinguished:
| Badge | Source | Example |
|---|---|---|
AI INSIGHT | LLM-generated by an agent buddy. Grounded in the current graph + brand context. | "Your Series-B segment responds 34% better to Tuesday 10am sends. And I've noticed three just hired VPs of Marketing in the last week." |
| Insights (heuristic flare, no AI badge) | Deterministic rules computed server-side from the graph. Timing, frequency, audience overlap. | "This campaign sent 4× to the same segment in 7 days. Consider reducing frequency." |
The heuristic path is always on; it's free, fast, and runs on every campaign. The AI path runs on demand or when a buddy is asked for a deeper read.
04Types of heuristic recommendations
Waypath's heuristic engine generates these recommendation categories:
- Optimize timing: adjust send times based on engagement patterns
- Expand audience: identify similar segments that may respond well
- Reduce frequency: detect over-communication that leads to drop-off
- Optimize content: flag subject lines / CTAs with low click-through
- Adjust audience: prune uninvolved segments from a campaign
- Content strategy: longer-horizon content recommendations
- Segmentation: flag overlapping segments that should be consolidated
All recommendation types are modeled as Recommendation nodes in the graph
with RECOMMENDS_FOR and BASED_ON edges pointing to the relevant
Campaign and supporting Touchpoints.