See how Beltmar reads behavior as narrative
This walkthrough uses fictional sample data to show how raw events become narrative views of daily momentum, individual journeys, and audience patterns. Beltmar describes how behavior appears to be changing — it does not predict intent or recommend actions.
All data is illustrative. Real workspaces use your own imports and tracking.
5
New actors
6
Momentum shifts
4
Returns
alex@example.com
High priority · strong signalPrimary pattern
Deep research across 4 themes (16 events) · 3 returns in 7 days
Decision context
Why this matters
Behavior suggests evaluation-phase research around pricing and implementation.
How to read this
This pattern often reflects structured exploration rather than casual browsing, especially when return visits cluster across a short window.
What to watch for next
Whether returns continue over the next 3–5 days, and whether exploration expands into implementation themes.
How to work with this pattern
Do we have clear explanations of our approach? Is there enough context around value?
View full journey for deeper interpretation →
What changed
- · 3 actors shifted from stable to warming
- · 2 actors returned after 10+ days of inactivity
- · Pricing and onboarding themes saw the largest depth increase
01
A daily narrative of momentum
The Daily Brief gives you a narrative snapshot of how attention is shifting. Instead of charts and funnels, Beltmar surfaces patterns — warming curiosity, cooling engagement, meaningful returns after inactivity.
What you're seeing
A sample brief for one high-priority actor. Notice the three layers: primary pattern (what happened), decision context (how to read it), and interpretive guidance (questions worth sitting with).
How teams use this
Teams open the Brief to understand where attention is moving — not to trigger automation. The framing shifts conversations from “what should we do?” to “here’s how to think about this.”
Last 10 days
Day 1 · Lands on "What is Beltmar" and reads overview
Discovery · 2 page views
Day 3 · Returns to read "How it Works" and "Audience Research"
Early research · 4 page views
Day 6 · Focuses on pricing, guarantees, and onboarding
Evaluation-leaning · 6 page views
Day 10 · Brief return to "Audience Research" after 4 days quiet
Return after gap · 3 page views
Narrative interpretation
Curiosity has moved from broad exploration into focused evaluation.
Initial visits were exploratory. Subsequent visits concentrated on pricing and implementation — suggesting evaluation rather than casual browsing.
The short gap followed by a focused return to Audience Research indicates the actor is still actively considering fit.
Beltmar describes these shifts as they appear. It does not assert intent or recommend actions.
02
One person's story over time
Actor Journeys show how curiosity develops for an individual. Rather than reducing behavior to a score, Beltmar presents a timeline and a calm narrative of how exploration, research, and returns are unfolding.
What you're seeing
A fictional journey for a single actor — timeline on the left, narrative interpretation on the right. The interpretation describes phase, not intent.
How teams use this
Teams use journeys when they want to understand not just that someone is active, but how their behavior is evolving and what kind of phase they appear to be in.
Cohort
Deep Research Explorers
Smaller group, high depth across 3–5 themes, frequent returns after gaps.
Why this matters: often represents people actively evaluating fit rather than casually browsing.
What to watch: shifts in which themes they revisit as their evaluation narrows.
Theme roles
- Discovery · "What is Beltmar" · attracts early exploration and first visits.
- Research · "How it Works" · supports deeper understanding of the model.
- Evaluation · Pricing, guarantees, onboarding · appear near focused evaluation behavior.
Audience Research does not rank “best segments” — it describes recurring engagement patterns and how themes participate in those patterns.
03
Patterns across many people
Audience Research zooms out from individual journeys to show recurring behavioral cohorts and the roles themes play across them. Interpretive observations, not optimization advice.
What you're seeing
A fictional cohort of “Deep Research Explorers” and a mapping of how themes tend to function in their journeys.
How teams use this
Teams use Audience Research to understand how different kinds of visitors behave as a group, which themes tend to matter most, and how those patterns shift over time.
Full platform
Everything in the same interpretation flow
Link Library + Campaign Calendar
deterministicOutbound identifiers, campaign windows, and quick link operations in one source-of-truth surface.
Inbound Sources
provenanceSource mix and entry context with content-linked traces when IDs or labels are present.
Journey Overview
Workspace-level progression patterns — visit-shape distribution, return intervals, and common first-to-second touchpoint transitions.
Research Artifacts + Diffs
Snapshot artifacts provide print/share output and delta views across time windows.
External Content Library
Annotate content IDs, titles, and notes so inbound entries and journeys are tied to outside-world content context.
Observations Feed
Detected shifts logged with confidence and uncertainty notes, plus neutral questions to explore over the next window.
Early access
Ready to see your own audience through this lens?
Connect your data with CSV, tracking links, or a website snippet. Beltmar will begin constructing Daily Briefs, journeys, cohorts, and theme roles based on real behavior — not lead scores.
Beltmar does not trigger outreach or automation. It exists to help you understand behavior more clearly.