Move 01
Read
JourneyOS reads purchase events, reviews and NPS verbatims, session paths, and field-level friction. All from data you already have; no new instrumentation, no third-party enrichment.
Your analytics is aggregate. Your customers aren't.
Distinct customer types. Distinct reasons they leave. One aggregate metric hides them all. JourneyOS separates them from the aggregate, using the data you already have.
The aha moment
Same drop-off. Different reasons.
- A
Opens competitor tabs mid-checkout. Returns with a smaller basket, or never returns.
- B
Repeats the size chart three times. Leaves when the chart is in inches and their measurement is in centimeters.
- C
Reads every word on the refund policy page. Twice.
- D
Completes checkout through shipping selection, then bounces at payment method.
How it works
Read, simulate, recommend.
Move 02
Simulate
The method runs segment-level simulation against the read. Each customer type walks through your specific funnel with its own probability weights, not one averaged scenario.
Move 03
Recommend
The method returns confidence-scored recommendations, not deterministic prescriptions. Each recommendation carries a confidence score and a named source of that confidence.
Common questions
How JourneyOS fits with what you already use.
-
What data does JourneyOS need from my business?
JourneyOS works with customer reviews, support tickets, NPS verbatims, and funnel event data you already have. No third-party data enrichment or scraping.
-
How is JourneyOS different from Google Analytics or Mixpanel?
Analytics tells you WHERE customers drop off (the step). JourneyOS tells you WHO drops off at that step and WHY, decomposing each aggregate metric into distinct customer types.
-
Does JourneyOS replace my CDP?
No. JourneyOS is a diagnostic layer on top of your existing analytics and CDP. It explains why each customer type behaves differently at each step.
-
Can JourneyOS run without sharing our customer data?
Yes, for the walkthrough. JourneyOS demonstrates the method on a sample simulation in your vertical before any data exchange. Data access is only needed for a pilot.
Differentiation
Your analytics tells you who left. This tells you which of them would have stayed.
| Dimension | Analytics | CDP | JourneyOS |
|---|---|---|---|
| Resolution | Aggregate drop-off view. | Individual customer records view. | Segmented behavioral resolution. |
| Cadence | Daily or real-time dashboards. | Per-event stream, per-profile. | Per-type simulation, refreshed per cohort. |
| Output | One aggregate conversion rate per step. | Profile exports and audience lists. | Per-type recovery estimate with a confidence score. |
Your analytics tells you WHERE. JourneyOS tells you WHO, and WHY.
Method, grounded
Every inference ships with a confidence score. The method abstains when evidence for a segment is thin, rather than filling the gap with majority patterns.
Across verticals
Where the patterns look different.
Each vertical below shows how those positional patterns appear in its specific customer behaviors.
E-commerce
Pattern A: competitor-comparison shoppers who open other tabs at checkout. Pattern B: fit or spec uncertainty around size and product detail. Pattern C: refund-policy readers who stall before payment. Pattern D: payment-method dropouts who complete every step except the last.
Fintech
Pattern A: rate-comparison users who stall at credit-decision moments. Pattern B: fee-sensitivity scrutinizers who churn before auto-debit. Pattern C: trust-cautious applicants who re-read terms-of-service. Pattern D: documentation-anxious filers who abandon at the verification step.
Consumer health or patient-education
Pattern A: symptom-anxious readers who re-read clinical content. Pattern B: provider-comparison users who hop across listings. Pattern C: privacy-cautious users who stall at consent or intake forms. Pattern D: prescription-readiness dropouts who abandon at scheduling.
Subscription
Pattern A: value-comparators who bounce between plan tiers. Pattern B: trial-end procrastinators who churn one day before renewal. Pattern C: feature-anxious users who stall at advanced setup. Pattern D: payment-prepay refusers who pick monthly over annual.
See JourneyOS on your funnel.
Book a walkthrough. JourneyOS runs the method on a sample funnel and steps through what it surfaced; you decide what happens next.