Customer journey analytics
Journey orchestration lets brands build multi-step, multi-channel flows. Complexity grows fast and drop-off is rarely where the brand assumes.
PROBLEM
Clients would ask why a journey 'wasn't working' with no shared definition of working, and no per-node visibility into where users actually exited.
HYPOTHESIS
Most journey underperformance is concentrated at one or two nodes — usually a wait condition or an over-narrow branch predicate.
RESEARCH
Reconstructed node-level entry and exit counts for live journeys and built a per-node conversion view, then compared against the brand's intended funnel.
DATA USED
Journey node events · branch evaluation logs · channel send outcomes · conversion events
DECISION MAKING
Reported drop-off per node rather than overall journey conversion, because an aggregate number tells a brand they have a problem but not where to spend effort.
SOLUTION
Node-level drop-off analysis delivered per account, and a repeatable query pattern the team could run for any journey.
BUSINESS OUTCOME
Conversations with clients shifted from 'the platform isn't working' to 'this branch condition is too narrow' — a far more productive place to start.
REFLECTION
Giving people the right unit of analysis changes the conversation more than giving them more data.
SQL INVESTIGATION
SELECT node_id, node_type,
count(*) AS entered,
count(*) FILTER (WHERE exited_forward) AS advanced,
round(100.0 * count(*) FILTER (WHERE exited_forward) / count(*), 1) AS pct
FROM journey_node_events
WHERE journey_id = :journey
GROUP BY node_id, node_type
ORDER BY node_id;